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July 2014

South Carolina Bankers SchoolJuly 13 - 18, 2014

Pricing Bank Products and Services

Sandy Petrowski

July 2014 1

Class Dynamics & Ground Rules

• Presentation is geared to community banks and large regional organizations

• Ground rules Expect class participation - learn from each other Take advantage of this time - ask questions There is no perfect answer - each bank and situation

is different Respect others while they are speaking

• If not covered in class, come see me or contact me [email protected] 843-714-9323 (c)

July 2014 2

Course Objectives

• Progress from a typical pricing process to a Best Practice

• Key Pricing Assumptions• Current Environment and its Impact• Definitions and Fundamentals• How the Asset Liability Process Impacts Pricing• Key Fundamentals for an Effective Pricing

Management Program• Deposits• Commercial Loan Pricing

Large Bank Example How a Community Bank can enhance its process

• Consumer Loan Pricing• Concluding Remarks

July 2014 3

Typical Pricing Process at Most Banks

Get assumed cost of funds from ALCO or the Money Desk

Get credit loss assumptions from Risk Mgt.

July 2014 4


Then we get Marginal or Fully Loaded Expense Assumptions

from Finance

Next – We Add a Profit Margin or Spread Equal to what the CEO

Wants

July 2014 5


Now we can Calculate the Price

July 2014 6


• Then set our Price according to the Rates in our Market

• Then set our Price according to the Rates in our Market

We go through all that work and then eyeball markets rates

Why is this a Poor Practice in Pricing?

July 2014 7

Basic Pricing ModelBORROWER: ABC Company DATE: 11/1/13Profit/Rate Summary Notes:

ROA ROEInterest Rate Proposed 4.25% 1.14% 14.22%- with Proposed Compensating Balance -$ 1.14% 14.22%

Hurdle Rate = 17% ROE

Inputs OutputsLoan Info No Compensating BalanceLoan Amount 1,000,000$ Interest Income 4.250% 42,500$ Loan Type C&I Fee Income 0.000% - Internal Rating 5 Cost of Funds 1.850% (18,500) Fixed Loan Rate 4.250% Net Margin 2.400% 24,000$ Origination Fee (in dollars)New or Existing Loan new Credit Cost 0.3000% 3,000 Maturity (months) 60 Servicing 0.3500% 3,500 Amortization Schedule (months) 300 NIE 0.6500% 6,500$

Settlement Date 11/1/13Maturity Date 11/1/18

Monthly Payment (using Amortization Schedule) 5,417 Contribution Margin 1.7500% 17,500$ Average Life/Duration Est. 4.53Monthly Payment (using Maturity) $18,520 Net Income 1.1375% 11,375$ Cost of Funds InfoBrokered CD Cost of Funds - use Duration (callable CD) 1.750% ROA 1.138%

ROE 8.00% 14.22%Liquidity Premium: 3-5 years 0.100% 0.100%

5-8 years 0.250% 0.000% Contribution Margin 17,500$ 8+ years 0.500% 0.000% Deposit Scenario 1Total 0.100% Deposit Comp Balance -$

Total Cost of Funds 1.850% Funds Transfer Rate 2.0000% -$ Steady State Basis Deposit Costs:

Expected Loss Adj. C&I 0.300% 0.300% Interest Paid 0.0000% - CRE OO 0.250% 0.000% Servicing 0.2500% - CRE NOO 0.350% 0.000% -$ C&D 0.500% 0.000%Lot 0.500% 0.000% Deposit Contr. Margin 1.7500% -$ Total 0.300%

Total Contr. Margin 1.7500% 17,500$ Compensating BalancesType of Deposit Checking Total Relationship Net Income 11,375$ Balance -$ 1.1375%Interest Rate Paid on Deposit 0.000% Relationship ROA 1.14%Compensating Balance Required ? no Relationship ROE 14.22%

Key: Capital Deployed 80,000$ Inputs ROE Hurdle Rate 17.0% Tax Rate 35%Key Ratios ROE Hurdle - Cash 13,600$ Excess/(Shortfall) (2,225)$

July 2014 8

Key Pricing AssumptionsCost of Funds

• Why Brokered CDs and not FHLB rates?• Should we use the Callable CD rates?• What period of time should the cost of funds use?

Maturity, Duration, or Weighted Average Life (WAL)?• Why don’t we just use the average cost of our Deposits?• What is the Liquidity Premium and why is it used?

July 2014 9

Key Pricing AssumptionsCredit Cost or Expected Loss Assumptions

• Loss Assumptions? Expected loss over the life of the loan? Industry-wide or market loss rates? Use recent financial crisis loss rates? Other ideas?

Steady State BasisExpected Loss Adj. C&I 0.300%

CRE OO 0.250%CRE NOO 0.350%C&D 0.500%Lot 0.500%Total

July 2014 10

Other Key Pricing Assumptions

• What ROA target should we use?• Should we care about the “Hurdle Rate?”

How do we set that level?• Costs:

Should we include origination costs? What about costs to service and collect? Fixed and/or variable? Direct and indirect allocations? Should they be “fully loaded” or “marginal” costs?

• What capital allocation should we use? Regulatory based? Which one?

• What about Funds Transfer Pricing?

July 2014 11

Net Interest Margins Peaked Early in 2002

3.10%

3.20%

3.30%

3.40%

3.50%

3.60%

3.70%

3.80%

3.90%

4.00% 1Q

99

3Q99

1Q00

3Q00

1Q01

3Q01

1Q02

3Q02

1Q03

3Q03

1Q04

3Q04

1Q05

3Q05

1Q06

3Q06

1Q07

3Q07

1Q08

3Q08

1Q09

3Q09

1Q10

3Q10

1Q11

3Q11

1Q12

3Q12

1Q13

3Q13

NIM % for all FDIC Insured Institutions Source: FDIC QBP

What is the Key Driver for the Decline?

Huge Level of Lost Revenue and Capital

July 2014 12

Key Metrics for High Performing BanksBanks < $1 bil in Size

Source: FIS analysis of bank Call Reports from SNL – Banks < $1 Bil

How is this Accomplished?

July 2014 13

This can be Accomplished Through PricingCommit to a Pricing Discipline and Strategy

• Know your balance sheet and what it needs• Know the profitability of your products

Keep your product menu simple, easy, and well-designed• Know your customer and what they want and need

Customized bundles by segment and/or relationship or a la carte• Know your channel capabilities – develop more• Learn how to price and incent by segments

Incent to cross-sell for deeper “share of wallet”• Learn how to price using a 2-tier risk rating process• Know your operational capabilities and Improve• Know how to provide true service quality and how

to build and maintain relationships• Track performance and revise as you “learn”

July 2014 14

Quick ExampleHow we can use Pricing to increase NIM

• $500 mil Bank with $450 mil in earning assets Included in earning assets is $50 mil of Fed Funds that only

earns 19 bps• Current NIM% = 3.25%

That equates to $14.625 mil of annual interest income• So how can we increase revenue and utilize our

excess Fed Funds more effectively? Use price to drive more loans that by itself doesn’t make sense Do a loan sale of – say Auto Loans at 2.99% (below prime)

• Do the Math If we were to obtain $40 mil of 2.99% auto loans we replace the

19 bps Fed Funds or 280 bps more in yield That equates to an additional $1.120 of interest income $14.625 + $1.120 = $15.745 Divide that by our earning assets of $450 mil Result is our NIM% grows to 3.50%

July 2014 15

Definitionsand

Fundamentals

July 2014 16

Key Concepts and Definitions

ALCO• (Asset/Liability Committee) responsible for managing assets and liabilities, primarily the institution’s interest rate risk

Duration• Indicates the approximate price sensitivity (when will the instrument reprice) of a loan, investment, or deposit. Duration analysis compares the duration of the assets to the duration of the liabilities. If they are the same, then the bank is balanced/matched and immune to market rate changes.

Interest rate risk•The risk that a change in market rates will affect a financial institution's income and the market value of its assets and liabilities.

Liquidity• Institution’s ability to meet its needs for cash to fund loan and deposit outflows.

Marginal effect•The incremental effect on income or expense caused by a pricing change to a product. Change in income or expense divided by the change in balances.

Asset/Liability Sensitivity•Either assets or liabilities are repricing faster than the other. Asset sensitive (+) is where assets are repricing faster than liabilities. Liability sensitive (‐) is where liabilities are repricing faster than assets.

July 2014 17

Key Concepts and Definitions

Option adjusted spread•Captures the value of options embedded in financial instruments even when they are not affecting cash flows.

Prepayment/Option risk•This is where a customer has the ability to prepay loans at their option without penalty. This creates uncertainty in the amount and timing of principal and interest cash flows of a loan. Difficult to calculate since it represents the customer’s propensity to prepay.

Securitization•The conversion of loans into a security. Accomplished by underwriting loans to secondary market guidelines. Delivered to the market for either securities or cash (helps with liquidity) and creates gain accounting recognition in most cases.

Price elasticity•Measures how much consumers respond to price changes. Not linear. Products that have good substitutes have a higher elasticity of demand.

ROA•Return on Assets ‐measures how efficiently the bank is using its assets to produce net income

ROE•Return on Equity ‐measures how effectively a bank is using stockholder capital to produce income

July 2014 18

Key Concepts and DefinitionsFunds Transfer Pricing (FTP)

FTP addresses the issue of how to provide a funding charge for assets and a funding credit for liabilities. In a simple sense, a cost of funds “window” is

hypothetically created for the bank and lenders borrow from the window and funds gatherers sell to the window. The window buys and sells according to

duration and matches the product to minimize interest rate risk.

Treasury then manages interest rate from an overall perspective and the rest of the bank doesn’t

have to worry about their position ‐ in most cases.

Lock at the date of loan or deposit origination and remain

unchanged through the life of the loan.

Deposits may change according to movements in core deposit

assumptions

Components of FTP

Base funds transfer pricing rate (SWAP curve, brokered

CDs, etc.)

Overnight funds ‐

midpoint of bid‐ask spread on Fed Funds

< 1 Year ‐ a market

based index

> 1 Year ‐LIBOR swap

rates

Liquidity Premium ‐ intended to account for the cost of holding funds to support assets for the estimated lives of those assets. Vary based on the maturities for the underlying

instruments.

May also include basis risk due created by using the LIBOR curve with products that follow another index.

July 2014 19

What Causes Below Market Pricing ?

Inadequate Sales

Training

Loan Officer

Incentives

Pricing policies

and practices

Relationshippricing and subsidies

Over-reliance on Profitability

Models

Lack of Market

Intelligence

Below Market Pricing

Source: AFS Perspective, September 2005 Issue 4

Banks can strengthen their performance:

• Through bank-wide implementation of best practices

• Ongoing tracking of loan and deposit market trends

• Provide accurate and enhanced market intelligence to the line

• See the Appendix for Definitions

July 2014 20

Summary of the Critical DriversGood Matrix of the Key Drivers in Pricing Models

Source: FMCG

July 2014 21

Asset / LiabilityProcess

July 2014 22

Asset/Liability Committee – ALCOWhat does the Committee do?

• Asset/Liability Process Dedicated to the analysis of balance sheet data to define

and manage interest rate and liquidity risk• Key Issues for the Committee

Interest rate risk evaluation and rate risk tolerance Liquidity and Capital management Product pricing and design Risk management and contingency planning Can identify strengths and weaknesses in the balance

sheet and target areas where changes should be made• Develops Key Strategies to meet your Target

balance sheet Retail vs. Wholesale strategies Impacts your pricing, selling, borrowing, even incentives,…

July 2014 23

How can ALCO be More Effective?

• Become a profit oriented, action-biased function Asset and Liability pricing Peer and performance analysis Annual profit planning and strategic planning

• Make your ALCO the key catalyst for profit enhancement Where else in the bank is this done? Its the best way to focus the bank Drives discipline and best execution

July 2014 24

Pricing CommitteesNatural Sub-Committee of ALCO or a part of ALCO

• Natural extension of ALCO Retail, Commercial, Deposit,… ALCO sets the tone and direction of all pricing committees ALCO reviews, monitors, and ratifies Pricing Committee

decisions and marketing campaigns Keeps everything in alignment

• Pricing Team Expectations Know the competition, their products, rates, strengths, etc. Know your customer’s response to pricing changes Know your balance sheet Retention/attrition rates, target mix, concentrations, etc.

Know your products and services and their attractiveness Know your strengths, capabilities, and culture Know your system capabilities and operating throughput

July 2014 25

Let’s Define What We are Trying to doThe Financial Management Process

Tactical

Long Range Outlook

Asset/Liability Mgt.

Budgeting Process

Org. Profitability

Product Profitability

Customer Profitability

Strategic Where are we going?

How will we get there?

How are we doing?

Performance Measurement

Tools

Source: AICPA conference with ProfitStars

July 2014 26

Rate Sensitivity Simulations

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6.00%

7.00%

30 Day 90 Day 6 Month 1 Year 2 Year 5 Year 10 Year 30 Year

200bp Shock

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9.00%


Twist

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Twist

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Twist

Chart I Chart II

Chart IIIChart IV

July 2014 27

Historical Treasury Yield Curves

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%


5/23/08

6/03/03

6/11/09

5/14/10

5/26/06

6/07/07

12/31/07

5/27/05

5/05/04

12/31/13

5/23/14

7/25/12

5/10/13

5/31/11

July 2014 28

From Normal to Flat

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5.00%

6.00%


6/03/03

5/27/05

5/05/04

July 2014 29

Flat to Inverted and then to Lower Short-Term

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1.00%

2.00%

3.00%

4.00%

5.00%

6.00%


5/23/08

5/26/06

6/07/07

12/31/07

July 2014 30

Crisis – 5 Years of Low Rates

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5.00%

6.00%


5/23/08

6/11/09

5/14/10

12/31/07 12/31/13

5/23/14

7/25/12

5/10/13

5/31/11

July 2014 31

Periods of Sustained Fed TighteningWhat is in our Future

Cycle Number of Cumulative Beginning EndingDuration Prime Rate Change Prime Prime

Start Date End Date (months) Increases in Rates Rate Rate1960's

Dec-65 Aug-66 9 4 150 4.50% 6.00%Dec-68 Jun-69 7 5 225 6.25% 8.50%

1970'sFeb-72 Oct-73 20 22 550 4.50% 10.00%Mar-74 Jul-74 5 13 325 8.75% 12.00%Jul-75 Sep-75 3 4 100 7.00% 8.00%

May-77 Dec-78 19 21 500 6.75% 11.75%Jul-79 Dec-79 6 14 425 11.50% 15.75%

1980'sFeb-80 Apr-80 3 9 475 15.25% 20.00%Aug-80 Dec-80 5 18 1050 11.00% 21.50%Apr-81 May-81 2 6 350 17.00% 20.50%Aug-83 Jun-84 11 5 250 10.50% 13.00%Apr-87 Oct-87 7 5 175 7.50% 9.25%May-88 Feb-89 9 6 300 8.50% 11.50%

1990'sMar-94 Feb-95 11 6 300 6.00% 9.00%Jun-99 May-00 11 6 175 7.75% 9.50%

2000'sMay-04 Jun-06 24 17 425 4.00% 8.25%

Cycle Number of Cumulative Beginning EndingDuration Prime Rate Change Prime Prime

Start Date End Date (months) Increases in Rates Rate Rate1960's

Dec-65 Aug-66 9 4 150 4.50% 6.00%Dec-68 Jun-69 7 5 225 6.25% 8.50%

1970'sFeb-72 Oct-73 20 22 550 4.50% 10.00%Mar-74 Jul-74 5 13 325 8.75% 12.00%Jul-75 Sep-75 3 4 100 7.00% 8.00%

May-77 Dec-78 19 21 500 6.75% 11.75%Jul-79 Dec-79 6 14 425 11.50% 15.75%

1980'sFeb-80 Apr-80 3 9 475 15.25% 20.00%Aug-80 Dec-80 5 18 1050 11.00% 21.50%Apr-81 May-81 2 6 350 17.00% 20.50%Aug-83 Jun-84 11 5 250 10.50% 13.00%Apr-87 Oct-87 7 5 175 7.50% 9.25%May-88 Feb-89 9 6 300 8.50% 11.50%

1990'sMar-94 Feb-95 11 6 300 6.00% 9.00%Jun-99 May-00 11 6 175 7.75% 9.50%

2000'sMay-04 Jun-06 24 17 425 4.00% 8.25%

July 2014 32

IRR Summary1st Rolling 12 Months After Tax

% Change $ Change % ofRate Scenario Net Interest Income Over Base/Static Over Base/Static Net Income

Rate Shock +400 18,021 41.83% 3,349 40.72%Rate Shock +300 16,629 30.88% 2,477 30.12%Rate Shock +200 15,252 20.04% 1,614 19.62%Rate Shock +100 13,961 9.88% 804 9.78%Base 12,706 0.00% 0Rate Shock -100 11,299 -11.07% (883) -10.74%Rate Shock -200 10,393 -18.20% (1,451) -17.64%Rate Shock -300 (not run)Rate Shock -400 (not run)Base - Assumed Net Income after 12 months 5,017 M

Static 11,006 0.00% 0 0.00%Static up 200 13,343 21.23% 1,482 22.88%Static - Assumed Net Income after 12 months 3,951 M

Base 12,706 0.00% 0 0.00%Up 200 15,252 20.04% 1,614 19.62%Ramp 14,065 10.70% 869 10.57%Steepen 12,887 1.42% 131 1.59%Rate & Steepen - Assumed Net Income after 12 months 5,017 M

2nd Rolling 12 Months After Tax% Change $ Change % of

Rate Scenario Net Interest Income Over Dynamic Over Dynamic Net IncomeRate Shock +100 15,463 10.31% 923 9.68%Rate Shock +200 16,889 20.48% 1,817 19.06%Rate Ramp +300 18,358 30.96% 2,738 28.72%Rate Shock +400 (not run) 19,830 41.46% 3,661 38.40%Base 14,018Rate Shock -100 11,962 -14.67% (1,291) -13.54%Rate Shock -200 10,801 -22.95% (2,019) -21.18%Rate Shock -300 (not run)Rate Ramp -400 (not run)Base - Assumed 24-month After Tax Net Income 5,815 M

July 2014 33

Interest Rate Risk DashboardTrends Help in your Pricing Strategy

‐18.20%

‐11.07%

9.88%

20.04%

30.87%

41.83%

‐36%

‐29%

‐22%

‐15%

‐8%

‐1%

6%

13%

20%

27%

34%

41%

48%

Shock ‐200 Shock ‐100 Shock +100 Shock +200 Shock +300 Shock +400

Earning at Risk% Increase/Decrease in $NIM vs. Static

19.75%

21.94%

18.79%

21.01%20.73%

20.04%

17.00%

18.00%

19.00%

20.00%

21.00%

22.00%

23.00%

1Q12 2Q12 3Q12 4Q12 1Q13 2Q13

Earnings at Risk Trends% Increase/Decrease in $ NIM vs. Static

Up 200

July 2014 34

Sensitivity Analysis (Different Bank – Enhanced Monitoring)2nd Rolling 12 months

% Change $ ChangeRate Scenario Net Interest Income Over Flat Over Flat

Rising Rate Ramp +300 259,507 -5.45% (14,952) Rising Rate Ramp +200 264,992 -3.45% (9,467) Rising Rate Ramp +100 270,737 -1.36% (3,723) Rate Shock +300 262,429 -4.38% (12,030) Rate Shock +200 267,266 -2.62% (7,194) Rate Shock +100 272,069 -0.87% (2,391) Flat 274,459 0.00% - Rate Shock -100 269,138 -1.94% (5,321) Rate Shock -200 258,522 -5.81% (15,937) Rate Ramp -100 274,760 0.11% 300 Rate Ramp -200 266,547 -2.88% (7,913) Steep +100 281,621 2.61% 7,162 Flat -100 262,417 -4.39% (12,042)

Prime Based Loans April 2005

Commercial 1,229,041

Small Business 132,289

Home Equity 617,027

Golden Credit Line 15,952

Total 1,994,309

Short Term Borrowings 911,236

Prime Funding Spread Compression 0.25%

12 Month NII Impact ($ In Thousands) (2,278)

(On Prime/Short Term Borrowings position)

BASIS RISK

1st Rolling 12 months% Change $ Change

Rate Scenario Net Interest Income Over Flat Over FlatRising Rate Ramp +300 269,858 -2.23% (6,159) Rising Rate Ramp +200 272,339 -1.33% (3,678) Rising Rate Ramp +100 274,542 -0.53% (1,475) Rate Shock +300 267,558 -3.06% (8,459) Rate Shock +200 270,950 -1.84% (5,068) Rate Shock +100 274,235 -0.65% (1,782) Flat 276,017 0.00% - Rate Shock -100 272,602 -1.24% (3,415) Rate Shock -200 265,866 -3.68% (10,151) Rate Ramp -100 275,878 -0.05% (139) Rate Ramp -200 273,862 -0.78% (2,155) Steep +100 279,823 1.38% 3,806 Flat -100 269,649 -2.31% (6,368)

Last Month up 200 vs Flat (5,202) Purchase of 100 million FHLB Advances 2,000 Bond portfolio/purch prem amort (550) Non earning assets volume up (240) Money Maker volume down (200) Accelerated Savings volume down (115) CD maturity shortening (600)

Other (161)Current Month up 200 vs Flat (5,068)

EARNINGS AT RISK WALKFORWARD

July 2014 35

Net Interest Margin WalkforwardTracks and Monitors Results and Variances to Forecast

Actual + CurrentInea NII Inea NII Model Results Actual + Previou Difference BetwMonthly Quarterly Monthly Quarterly Model ResultsModel Results Monthly Quarterly

January 22,719 23,017 23,017 0 3.95February 21,382 21,750 21,750 0 3.95March 22,716 66,817 23,465 68,233 23,465 0 3.99 3.96April 22,240 22,718 22,718 0 3.92May 22,884 23,037 22,980 57 3.89June 22,714 67,839 22,591 68,346 22,687 (96) 3.90 3.90July 23,330 23,216 23,131 85 3.91August 23,501 23,184 23,277 (93) 3.90September 23,110 69,941 22,710 69,110 22,837 (126) 3.87 3.89October 23,701 23,317 23,457 (141) 3.88November 23,270 22,971 23,025 (55) 3.89December 23,852 70,823 23,438 69,726 23,611 (173) 3.89 3.89

275,420 275,420 275,414 275,414 275,955 (541) 3.91 3.91

Q2: Presumes Accelerated Savings rate increase of Previous Model Results 275.9

15 bps on average and Business MMIA rate Small Business Loan Volume -12 (0.1)

increase of 15 bps which have not been made yet. Home Equity Fixed Loan Volume -15 (0.2)

Investment Volume -54 (0.1)

Q3: Deposit volume is primary risk. Money Maker Volume -20 (0.3)

Accelerated Savings Volume -60 (0.3)

Deposit Lag 0.9

Prime/ST Borrowing Spread -10 bps (0.5)275.4

Budget NIM % Actual + CurrentModel Results

WALKFORWARDComments On Forecast

Actual

Forecast

Key Driver Notes

July 2014 36

Sample Margin % Walkforward

NIM%

3.99 March Actual

0.01 Deposit Lag & ECR-Related Benefit0.02 Net Non-Accrual Interest

(0.01) Consumer Loan Fees(0.01) Keeper Mortgage Yield (actual 5.35%, should be 5.74%)(0.01) Deposit volume declines and mix changes(0.02) Decline in spread between Prime and Short Term Borrowings cost (mostly Repo)(0.01) Maturity/rollover of 1.90% FHLB advances (funded $500mm expansion)(0.01) Increase in Earning Assets at spreads much lower than 3.99%(0.01) Public Funds MMCA (Feb error, Mar correction, April normal, but lower than Mar)(0.01) Interest Rate Risk Position

(0.01) Other / Rounding

3.92 April Actual

Description

July 2014 37

Next Year’s Maturing CDsUse this Cash Flow to Strategize and set Action Plans

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1.40%

-

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000

12,000,000

14,000,000

16,000,000

18,000,000

20,000,000

5/1/14

6/1

/14

7/1/14

8/1

/14

9/1/14

10

/1/14

11

/1/14

12

/1/14

1/1

/15

2/1/15

3/1

/15

4/1/15

Maturing CDs Average Rates

July 2014 38

Understanding other Cash Flow ItemsFind the future opportunity and plan ahead

4/30/2004 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15May-04 Jun-04 Jul-04 Aug-04 Sep-04 Oct-04 Nov-04 Dec-04 Jan-05 Feb-05 Mar-05 Apr-05 May-05 Jun-05 Jul-05

Cash (000's)GOVERNMENTS $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0AGENCIES 450 20,500 10,000 0 0 0 15,000 20,065 15,046 75,000 0 0 0 0 0Non-Taxable MUNICIPALS 817 2,272 1,297 0 675 394 829 2,153 260 2,272 1,839 1,230 2,110 3,363 1,397Agency CMO 8,036 7,060 6,796 6,429 6,699 6,513 6,096 5,833 4,708 3,427 2,866 2,812 3,462 4,760 19,914Mortgage-Backed Pools 7,031 7,155 7,054 6,957 6,868 6,786 6,710 6,636 6,567 6,504 6,442 6,383 6,326 6,270 6,218ASSET BACKED/CORP CMOS 19 51 7 10 15 7 11 2,793 17 12 17 9 11 15 8OTHER 42 0 0 0 0 0 0 0 3 0 0 0 0 0 0Total CBCF $16,395 $37,038 $25,154 $13,396 $14,257 $13,700 $28,646 $37,480 $26,601 $87,215 $11,164 $10,434 $11,909 $14,408 $27,537

16 17 18 19 20 21 22 23 24Aug-05 Sep-05 Oct-05 Nov-05 Dec-05 Jan-06 Feb-06 Mar-06 Apr-06

$0 $0 $0 $0 $0 $0 $0 $0 $00 40,000 0 0 0 0 0 0 0

3,619 975 1,616 2,113 2,173 1,022 2,038 2,505 1,5115,874 6,414 8,240 13,365 10,099 15,444 11,904 16,099 19,7456,175 6,105 6,027 5,940 5,851 5,758 5,664 5,567 5,470

10 13 7 9 12 6 9 11 60 0 1,000 0 0 0 0 0 0

$15,678 $53,507 $16,890 $21,427 $18,135 $22,230 $19,615 $24,182 $26,732

July 2014 39

Key Fundamentalsfor an

Effective PricingManagement Program

July 2014 40

Seven Key Components of Improved Pricing

These Capabilities are Fundamental to Setting the Stage for an Effective

Pricing Management Program

Align Pricing with Business

Strategy

Align Pricing with Business

Strategy

Price to Customer Value

Price to Customer Value

Price to Manage Risk

Price to Manage Risk

Price to Create

Efficiencies

Price to Create

Efficiencies

Optimize the

Price/Volume

Tradeoff

Optimize the

Price/Volume

Tradeoff

Train Your Sales ForceTrain Your Sales Force

Optimize Good Market

Intelligence

Optimize Good Market

Intelligence

July 2014 41

Link Pricing Strategyand Sales / Marketing Strategy

• First 90 days with a new customer is critical to cross-sales effectiveness• If strategy is to acquire customers with promotional pricing, then it is

critical to have a proven process to ensure cross-sales to broader product set in order to lower overall cost, improve retention

• Without this discipline in place, bank is likely to acquire rate sensitive customers

Year 1 =45% of total cross-sell opportunity

Period after initial purchase when second product is bought. Source: Bank Administration Institute and Peak Performance Consulting Group client data

7-12 months17%

4-6 months10%

1-3 months16%

Within the 1st month57%

July 2014 42

5 Key Segments of Consumer Banking RelationshipsHelp Banks to More Precisely Target Value Propositions

Source: BAI Research Study, April 2012

July 2014 43

Significantly Enhanced Customer Data

Source: Novantas, LLC

July 2014 44

Know Your Customer

July 2014 45

Deposits

July 2014 46

Effective Deposit Pricing

• Fully understand demand across different price points for each deposit product Be flexible in different customer and price segments During the Financial Crisis stronger banks have been refining

goals and pricing strategies for each major type of product• Develop a pricing strategy

Decide where on the pricing curve you want to be Include revenue and balance objectives Decide on a targeted price position to competitors Incorporate elasticity analyses to various pricing scenarios To anticipate the resulting changes to balances and deposit volume

• Good Market Intelligence is the key to set prices on competitor actions – not just the “rumor” or “feel” What are Ways to get Good Market Intelligence?

July 2014 47


• Analyze the pricing strategy against the bank’s value proposition Service levels, branch density, advertising

• Utilize elasticity to optimize segment based pricing Special offers to seniors, health care, high-balance customers Understand how elasticity varies by balance and relationship and

other potential attitudinal and behavioral segments Focus on the customer segments that are less price sensitive

• Develop products that encourage deposit aggregation

• Focus on high average balance segments • Manage the odd-maturity specials to drive customer

expectations

July 2014 48


• Set high standards for your sales force – expect them to grow deposits A true sales culture - identifies customer needs Then provides a complete value proposition of care, service,

price, and other elements• Find the deposit rich and loyal areas of focus

Small Business is one – Healthcare is another• Give your customers a reason to remain a customer

Customer retention drives deposit growth Is the best predictor of earnings growth and stability 70% of all new money comes from existing customers Most of our attention is directed towards acquisition vs. retention

Read the BAI Banking Strategies article “Window of Opportunity,” November/December 2003

July 2014 49

Typical Market Rate Comparison

Rate Comparisons Regular Savings - $1k

Interest Checking -

$5k

Money Market -

$2.5k

Money Market -

$50k

Money Market -

$250k3 Mo CD -

$10k6 Mo CD -

$10k1 Yr CD -

$10k18 Mo CD -

$10k2 Yr CD -

$10k3 Yr CD -

$10k4 Yr CD -

$10k5 Yr CD -

$10kBank of the Ozarks, Inc. 0.10 0.14 0.10 0.31 0.31 0.10 0.15 0.25 0.30 0.35 0.35 0.35 0.35First Financial Holdings, Inc. 0.05 0.01 0.05 0.15 0.15 0.05 0.10 0.10 0.20 0.25 0.35 0.45 0.45Synovus Financial Corp. 0.09 0.06 0.12 0.28 0.29 0.10 0.16 0.22 0.30 0.38 0.56 0.72 0.84BNC Bancorp 0.10 0.05 0.05 0.15 0.25 0.15 0.25 0.30 0.35 0.40 0.45 0.50 0.55Ameris Bancorp 0.10 0.15 0.25 0.27 0.28 0.20 0.25 0.40 0.50 0.60 0.80 0.80 0.80Atlantic Bancshares, Inc. 0.05 0.05 0.10 0.20 0.35 - - 0.30 0.40 0.50 0.60 0.70 0.80Tidelands Bancshares, Inc. 0.35 0.05 0.05 0.15 0.25 0.20 0.30 0.75 0.55 1.00 1.10 - 1.20BB&T Corporation 0.02 0.01 0.03 0.03 0.03 0.03 0.05 0.10 0.15 0.20 0.40 0.45 0.50Regions Financial Corporation 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.05 0.05 0.10 0.15 0.30 0.35SunTrust Banks, Inc. 0.01 0.01 0.01 0.05 0.05 0.03 0.05 0.10 0.10 0.20 0.25 0.30 0.40TD Bank, N.A. 0.05 0.05 0.05 0.25 0.30 0.20 0.15 0.20 - - 0.40 0.60 0.85Wells Fargo & Company 0.01 0.05 0.03 0.03 0.03 0.01 0.01 0.05 0.05 0.16 0.20 0.25 0.35Bank of America Corporation 0.01 0.01 0.03 0.05 0.07 0.02 0.02 0.08 0.14 0.12 0.15 0.17 0.17First South Bank - - - - - - - - - - - - -Ally Financial Inc. 0.87 0.10 0.85 0.85 0.85 0.30 0.61 0.95 0.94 1.10 1.20 1.30 1.60Palmetto State Bankshares, Inc. 0.10 0.10 0.10 0.30 0.30 0.10 0.30 0.35 0.35 0.35 0.35 0.35 -Minimum 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.05 0.05 0.10 0.15 0.17 0.17Median 0.05 0.05 0.05 0.18 0.25 0.10 0.15 0.21 0.30 0.35 0.38 0.45 0.55Average 0.12 0.06 0.12 0.21 0.23 0.10 0.17 0.27 0.31 0.40 0.48 0.51 0.66Maximum 0.87 0.15 0.85 0.85 0.85 0.30 0.61 0.95 0.94 1.10 1.20 1.30 1.60

CoastalStates Bank 0.15 0.05 0.05 0.18 0.23 0.12 0.15 0.25 0.28 0.40 0.50 1.15 1.151 Mo 1 Mo 1 Mo 1 Mo 1 Mo 3 Mo 6 Mo 1 Yr 2 Yr 3 Yr 5 Yr

0.02 0.02 0.02 0.02 0.02 0.03 0.05 0.10 0.39 0.81 1.57Spread 0.13 0.03 0.03 0.16 0.21 0.09 0.10 0.15 0.01 (0.31) (0.42)

CSB to Minimum 0.14 0.04 0.04 0.17 0.22 0.11 0.14 0.20 0.23 0.30 0.35 0.98 0.98CSB to Maximum (0.72) (0.10) (0.80) (0.67) (0.62) (0.18) (0.46) (0.70) (0.66) (0.70) (0.70) (0.15) (0.45)CSB to Average 0.03 (0.01) (0.07) (0.03) (0.00) 0.02 (0.02) (0.02) (0.03) 0.00 0.02 0.64 0.49

UST Treasuries

July 2014 50

Utilize Benchmark PricingTrack against Market Rates and also Track against Wholesale Rates

July 2014 51

Benchmark PricingAfter we showed the Retail Delivery Team the Missed Earnings

Note: There will always be a difference in the “hot zone” due

to competition and market forces

July 2014 52

1 Mo 3 Mo 6 Mo 9 Mo 1 Yr 18 Mo 2 Yr 30 Mo 3 Yr 42 Mo 4 Yr 5 Yr 6 YrCoastalStates Bank 0.15% 0.20% 0.60% 0.65% 0.85% 0.80% 0.90% 1.00% 1.15% 1.25%Internet CDs 0.23% 0.50% 0.50% 0.65% 0.95% 1.00% 1.08% 0.66% 1.25% 1.25% 1.35% 1.50%CenterState Non‐Callable CDs 0.38% 0.35% 0.38% 0.43% 0.53% 0.60% 0.63% 0.68% 0.75% 0.90% 1.18% 1.43%CenterState Callable CDs 0.63% 0.68% 0.73% 0.75% 0.88% 1.20% 1.43%FHLB 0.25% 0.26% 0.28% 0.31% 0.32% 0.36% 0.41% 0.65% 0.90% 1.22% 1.51%

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1.40%

1.60%

Rate

Benchmark PricingTo Wholesale Funding as of Feb 2013

New ComponentNote: the higher cost

July 2014 53

1 Mo 3 Mo 6 Mo 9 Mo 1 Yr 18 Mo 2 Yr 30 Mo 3 Yr 42 Mo 4 Yr 5 Yr 6 YrCoastalStates Bank 0.10% 0.15% 0.20% 0.25% 0.35% 0.45% 0.55% 0.90% 1.15% 1.15%Internet CDs 0.20% 0.45% 0.50% 0.65% 0.95% 0.95% 1.08% 0.51% 1.20% 1.25% 1.30% 1.45%CenterState Non‐Callable CDs 0.33% 0.33% 0.33% 0.35% 0.48% 0.55% 0.58% 0.63% 0.73% 0.83% 1.10% 1.35%CenterState Callable CDs 0.58% 0.63% 0.68% 0.73% 0.88% 1.13% 1.35%FHLB 0.22% 0.23% 0.26% 0.29% 0.31% 0.35% 0.40% 0.59% 0.79% 1.04% 1.31%

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1.40%

1.60%

Rate

Benchmark Pricing To Wholesale Funding as of March 2013

July 2014 54

Benchmark PricingTo Wholesale Funding as of April 2014

1 Mo 3 Mo 6 Mo 9 Mo 1 Yr 18 Mo 2 Yr 30 Mo 3 Yr 42 Mo 4 Yr 5 Yr 6 YrCoastalStates Bank 0.10% 0.12% 0.15% 0.15% 0.25% 0.28% 0.40% 0.50% 1.15% 1.15%

Internet CDs 0.35% 0.45% 0.55% 0.60% 0.80% 0.85% 0.95% 1.00% 1.37% 1.40% 1.75% 2.07%

CenterState Non‐Callable CDs 0.30% 0.30% 0.31% 0.38% 0.48% 0.55% 0.83% 1.05% 1.20% 1.48% 1.88% 2.18%

CenterState Callable CDs 0.65% 0.85% 1.13% 1.20% 1.55% 1.93% 2.28%

FHLB 0.19% 0.21% 0.23% 0.25% 0.27% 0.39% 0.56% 1.06% 1.52% 1.89% 2.22%

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

Rate

Methodically Drove Pricing

Down during the Flat Rate

Environment

July 2014 55

Effective and In-Effective Pricing

Mastery of price elasticity helps

to optimize account

profitability or target balance, depending on

strategy

July 2014 56

Effective and In-Effective PricingTarget Best Practice

Source: Novantas LLC, via conference material

July 2014 57

Marginal Cost PricingDo the Math

• Most Banks use pricing to raise additional funds Need to fully understand the cost of new funds in

evaluating the expense of the new money• Example

$42 million in Regular Savings .20% $84k exp. Want to raise the rate to .50% $210k exp. Estimate that you will raise 5% in new funds or $2.1 mil Increase in cost = $126k divided by new funds $2.1 mil Gives us our Marginal Cost of 6.00% Can we invest funds above 6.00% ??? Can we raise funds at a lower marginal cost than 6.00% ???

July 2014 58

Marginal Cost Pricing - continued

• Low response to the savings pricing change Let’s drop the rates - from .20% to .15%

• Example Balances are assumed to drop by 5% or to $39.9 million Interest expense drops $24.15k - marginal cost = 1.15% If we can replace the lost funds ($42mm-$39.9mm) at a

marginal cost below 1.15% - we are better off Current FHLB rates: .28% 1yr .59% 2yr 1.10% 3yr

• This illustrates we can use FHLB or Brokered CD rates as the benchmark comparisons

July 2014 59

What do We do When Rates Rise?

• Remember – the Biggest driver of deposit price competition is Loan Growth

July 2014 60

Imperatives for BankersIn a Rising Rate Environment

• Know your customer and know who is rate sensitive Reprice without moving the whole book Utilize regional pricing strategies

• Enable segment and even customer targeted pricing

• Be prepared with a set of flexible plans that are responsive to differing scenarios Protect your liquidity and do it in a profitable way

• Execute better by testing now Across various regions, channels, and customer groups

• Improve your online capability as that will be where 60% of your customers will look first for better rates

July 2014 61

Commercial Loan Pricing

July 2014 62

Basic Pricing ModelBORROWER: ABC Company DATE: 11/1/13Profit/Rate Summary Notes:












July 2014 63

Basic Pricing Model - with a 1% FeeBORROWER: ABC Company DATE: 11/1/13Profit/Rate Summary Notes:



Inputs OutputsLoan Info No Compensating BalanceLoan Amount 1,000,000$ Interest Income 4.250% 42,500$ Loan Type C&I Fee Income 1.000% 2,207 Internal Rating 5 Cost of Funds 1.850% (18,500) Fixed Loan Rate 4.250% Net Margin 3.400% 26,207$ Origination Fee (in dollars) 10,000New or Existing Loan new Credit Cost 0.3000% 3,000 Maturity (months) 60 Servicing 0.3500% 3,500 Amortization Schedule (months) 300 NIE 0.6500% 6,500$








Key: Capital Deployed 80,000$ Inputs ROE Hurdle Rate 17.0% Tax Rate 35%Key Ratios ROE Hurdle - Cash 13,600$ Excess/(Shortfall) (790)$

July 2014 64

Basic Pricing Model - with some compensating balancesBORROWER: ABC Company DATE: 11/1/13Profit/Rate Summary Notes:

ROA ROEInterest Rate Proposed 4.25% 1.14% 14.22%- with Proposed Compensating Balance 125,000$ 1.28% 16.00%






5-8 years 0.250% 0.000% Contribution Margin 17,500$ 8+ years 0.500% 0.000% Deposit Scenario 1Total 0.100% Deposit Comp Balance 125,000$

Total Cost of Funds 1.850% Funds Transfer Rate 2.0000% 2,500$ Steady State Basis Deposit Costs:

Expected Loss Adj. C&I 0.300% 0.300% Interest Paid 0.0000% - CRE OO 0.250% 0.000% Servicing 0.2500% 313 CRE NOO 0.350% 0.000% 313$ C&D 0.500% 0.000%Lot 0.500% 0.000% Deposit Contr. Margin 1.7500% 2,188$ Total 0.300%

Total Contr. Margin 1.9688% 19,688$ Compensating BalancesType of Deposit Checking Total Relationship Net Income 12,797$ Balance 125,000$ 1.2797%Interest Rate Paid on Deposit 0.000% Relationship ROA 1.28%Compensating Balance Required ? no Relationship ROE 16.00%


July 2014 65


ROA ROEInterest Rate Proposed 4.25% 1.28% 16.01%- with Proposed Compensating Balance 125,000$ 1.42% 17.79%


Inputs OutputsLoan Info No Compensating BalanceLoan Amount 1,000,000$ Interest Income 4.250% 42,500$ Loan Type C&I Fee Income 1.000% 2,207 Internal Rating 5 Cost of Funds 1.850% (18,500) Fixed Loan Rate 4.250% Net Margin 3.400% 26,207$ Origination Fee (in dollars) 10,000New or Existing Loan new Credit Cost 0.3000% 3,000 Maturity (months) 60 Servicing 0.3500% 3,500 Amortization Schedule (months) 300 NIE 0.6500% 6,500$




5-8 years 0.250% 0.000% Contribution Margin 19,707$ 8+ years 0.500% 0.000% Deposit Scenario 1Total 0.100% Deposit Comp Balance 125,000$

Total Cost of Funds 1.850% Funds Transfer Rate 2.0000% 2,500$ Steady State Basis Deposit Costs:

Expected Loss Adj. C&I 0.300% 0.300% Interest Paid 0.0000% - CRE OO 0.250% 0.000% Servicing 0.2500% 313 CRE NOO 0.350% 0.000% 313$ C&D 0.500% 0.000%Lot 0.500% 0.000% Deposit Contr. Margin 1.7500% 2,188$ Total 0.300%

Total Contr. Margin 2.1895% 21,895$ Compensating BalancesType of Deposit Checking Total Relationship Net Income 14,232$ Balance 125,000$ 1.4232%Interest Rate Paid on Deposit 0.000% Relationship ROA 1.42%Compensating Balance Required ? no Relationship ROE 17.79%


July 2014 66


ROA ROEInterest Rate Proposed 4.25% 1.28% 16.01%- with Proposed Compensating Balance -$ 1.28% 16.01%- Compensating Balance Needed for 17% 69,482$ 1.36% 17.00%

Min Int Rate for 17% ROE 4.37% 1.36% 17.00%

Inputs OutputsLoan Info No Compensating Balance Minimum Rate for 17% ROELoan Amount 1,000,000$ Interest Income 4.250% 42,500$ 43,716$ 4.3716%Loan Type C&I Fee Income 1.000% 2,207 2,207 RateInternal Rating 5 Cost of Funds 1.850% (18,500) (18,500) Needed toFixed Loan Rate 4.250% Net Margin 3.400% 26,207$ 27,423$ equal 17%Origination Fee (in dollars) 10,000New or Existing Loan new Credit Cost 0.3000% 3,000 3,000 Maturity (months) 60 Servicing 0.3500% 3,500 3,500 Amortization Schedule (months) 300 NIE 0.6500% 6,500$ 6,500$


Monthly Payment (using Amortization Schedule) 5,417 Contribution Margin 2.7500% 19,707$ 20,923$ Average Life/Duration Est. 4.53Monthly Payment (using Maturity) $18,520 Net Income 1.2810% 12,810$ 13,600$ Cost of Funds InfoBrokered CD Cost of Funds - use Duration (callable CD) 1.750% ROA 1.281% 1.36%

ROE 8.00% 16.01% 17.00%Liquidity Premium: 3-5 years 0.100% 0.100%

5-8 years 0.250% 0.000% Contribution Margin 19,707$ 8+ years 0.500% 0.000% Deposit Scenario 1 Deposit Scenario 2Total 0.100% Deposit Comp Balance -$ 69,482$ Compensating

Total Cost of Funds 1.850% Funds Transfer Rate 2.0000% -$ 1,390$ balance toSteady State Basis Deposit Costs: equal 17%

Expected Loss Adj. C&I 0.300% 0.300% Interest Paid 0.0000% - - CRE OO 0.250% 0.000% Servicing 0.2500% - 174 CRE NOO 0.350% 0.000% -$ 174$ C&D 0.500% 0.000%Lot 0.500% 0.000% Deposit Contr. Margin 1.7500% -$ 1,216$ Total 0.300%

Total Contr. Margin 1.9707% 19,707$ 20,923$ Compensating BalancesType of Deposit Checking Total Relationship Net Income 12,810$ 13,600$ Balance -$ 1.2810%Interest Rate Paid on Deposit 0.000% Relationship ROA 1.28% 1.36%Compensating Balance Required ? no Relationship ROE 16.01% 17.00%



July 2014 67

Best Practices “Checklist”Key Items for Commercial Loan Pricing

• LIBOR repricing term• Total Commitment Amount• Loan Utilization Percentage• Term/Remaining Term• Annual Amortization• Spread from Index• Unused Commitment Fee• Annual Facility Fees• Commitment/Up Front Fee• Letter of Credit Fees• Syndication Fees• Agency Fees• Annual SWAP Income• Cost of Funds

• Depository Products: Average available DDA balance DDA balances required for

Svcs. DDA service charge fees CD deposit balances

• Fee Based Services: Syndication management fees Private placement, Mezzanine,

and Futures fees M&A/Valuation income Corporate securities income Asset backed finance fees Equity offerings, Muni

• Trust Fees• Sweep Services

July 2014 68

Evolution of Pricing CapabilityMiddle Market Commercial Lending

July 2014 69

Loan Fees SummaryGood List of Fee Opportunities

July 2014 70

Large Bank Example

July 2014 71

Probability of Default - RMA vs. CitizensCitizens

Obligor (Credit) Rating: RMA Low % PD PD% RMA High % PD

1 Highest Quality P 0.00% 0.03% 0.04%2 Superior Quality P 0.05% 0.09% 0.12%3 Above Avg. Quality P 0.13% 0.15% 0.17%4 Average Quality P 0.18% 0.27% 0.35%5 Acceptable P 0.36% 0.94% 1.52%6 Low Acceptable P 1.53% 2.44% 3.34%7 Special Mention W 3.35% 5.68% 8.00%8 Substandard W 8.01% 19.00% 30.00%9 Doubtful W 30.00% 100.00% 100.00%

10 Loss W 30.00% 100.00% 100.00%

RMA- Risk Management Associates P= Pass W=Watch

PD - Probability of DefaultExpected percentage that there will be a default on any given loan

July 2014 72

Best PracticesCommercial Loans Pricing Discussion

• Relationship Pricing vs. Transaction/Product Pricing

• One or Two Tiered risk rating system Obligor rating Assesses the overall condition of the obligor and ability to repay

debt Expected default rating - relative likelihood of a payment default Key drivers - cash flow, liquidity, leverage/debt capacity, size One of the components which generates the level of capital

allocation Facility rating Credit based upon it’s pricing/funding characteristics Loss given default - expected loss that results from defaulted debt Driven by collateral type, amount of collateral, and monitoring of

collateral Prime, LIBOR, Fixed, Bankers Acceptance, Fixed Rate IRB,

Prime-based IRB, LIBOR-based IRB, and Letters of Credit

July 2014 73

Sample Facility Risk Rating Definitions

Rating

Predominant Collateral or Structural Feature

Estimated LGD %

A Cash

Cash equivalents (CDs) U.S. Government securities – at policy advance rate

5%

B Marketable securities at policy advance rate, including Federal agency, municipal and corporate Facilities guaranteed 85% or more by the U.S. and/or government/agency, etc. (e.g. SBA ,FSA

Guaranteed Loan, Wheda Loan) Fully secured by warehouse receipts (marketable security)

10%

C Accounts receivable and inventory – at policy advance rates and monitored on an asset-based borrowing base no less frequently than monthly and validated by satisfactory annual field exams

Facilities guaranteed 80% or more by the U.S. government/agency Marketable securities, including Federal agency, municipal and corporate Assignment of crop proceeds, livestock proceeds, milk proceeds Joint Payable checks (livestock proceeds, crop proceeds) Assignment of government payments Assignment of indemnity of crop insurance and crop revenue insurance proceeds

20%

D Accounts receivable and inventory – at policy advance rates and monitored on an asset-based borrowing base no less frequently than monthly

Fixed assets , including equipment and readily marketable owner-occupied real estate, at policy amortization and advance rates

Facilities guaranteed by U.S. government/agency Crop Insurance above catastrophic coverage level (> 50%) Crop Revenue insurance coverage (locked in price) Accounts receivable, inventory growing crops, breeding and feeding livestock at policy advance

rates with commodity prices forward contracted

30%

July 2014 74

Sample Facility Risk Rating DefinitionsE Accounts receivable and inventory – at policy advance rates but without specific monitoring or borrowing base

control Real estate (Non owner-occupied) at policy amortization and advance rates Commercial R/E owner occupied (limited purpose not readily marketable) Crop insurance minimum catastrophic coverage (50 %) Accounts receivable, inventory, growing crops, breeding and feeding livestock at policy advance rates – no

forward contract Specific Security Interest or Purchased Money Security Interest (PMSI) Equipment without blanket lien at

policy advance rates

35%

F Blanket lien or mixed collateral with shortfall within underwriting standards (<20%) or value of collateral is difficult to ascertain, highly volatile

No crop insurance (catastrophic or revenue?)

40%

G Collateral shortfall in excess of underwriting standards (>20%) Holding company loan (including bank holding company) secured by the stock of a subsidiary Second lien position real estate within policy LTV Collateral is cross collateralized with another bank ( i.e. split financing) Contractor inventory Contractor receivables (bonded and non-bonded) Distressed/substantially illiquid market for collateral Unsecured Highly specialized Ag Facilities ( IE hog buildings, dairy facilities, grain bins, greenhouses)

50%

H Mezzanine, or subordinated Non owner-occupied real estate 75% NOTE: The LGD percentages are subject to periodic review and may be changed from time to time

LGD - Loss Given DefaultExpected percentage of funded exposure that would result in loss if the customer/obligor has a payment default.

July 2014 75

Sample Annual Expected Losses and Capital Factors

Credit A B C D E F G HPD Rating 5.00% 10.00% 20.00% 30.00% 35.00% 40.00% 50.00% 75.00%

0.03% 1 0.00 0.00 0.01 0.01 0.01 0.01 0.02 0.020.09% 2 0.00 0.01 0.02 0.03 0.03 0.04 0.05 0.070.15% 3 0.01 0.02 0.03 0.05 0.05 0.06 0.08 0.110.27% 4 0.01 0.03 0.05 0.08 0.09 0.11 0.14 0.200.94% 5 0.05 0.09 0.19 0.28 0.33 0.38 0.47 0.712.44% 6 0.12 0.24 0.49 0.73 0.85 0.98 1.22 1.835.68% 7 0.28 0.57 1.14 1.70 1.99 2.27 2.84 4.2619.00% 8 0.95 1.90 3.80 5.70 6.65 7.60 9.50 14.25

100.00% 9 5.00 10.00 20.00 30.00 35.00 40.00 50.00 75.00100.00% 10 5.00 10.00 20.00 30.00 35.00 40.00 50.00 75.00

Credit A B C D E F G HPD Rating 5.00% 10.00% 20.00% 30.00% 35.00% 40.00% 50.00% 75.00%

0.03% 1 0.12 0.24 0.48 0.72 0.84 0.96 1.20 1.790.09% 2 0.22 0.45 0.90 1.35 1.57 1.80 2.24 3.370.15% 3 0.30 0.60 1.20 1.79 2.09 2.39 2.99 4.480.27% 4 0.41 0.82 1.64 2.45 2.86 3.27 4.09 6.130.94% 5 0.72 1.44 2.88 4.32 5.04 5.76 7.19 10.792.44% 6 0.99 1.99 3.98 5.97 6.96 7.96 9.95 14.925.68% 7 1.38 2.76 5.52 8.27 9.65 11.03 13.79 20.6819.00% 8 2.67 5.33 10.67 16.00 18.67 21.33 26.67 40.00

100.00% 9 5.07 10.14 20.29 30.43 35.51 40.58 50.72 76.08100.00% 10 5.07 10.14 20.29 30.43 35.51 40.58 50.72 76.08

Effective remaining maturity (M): 3 yearsSize of borrower (S): $5,000,000Note: S is the annual sales of the Borrow er. The above values are derived using the SME (Borrow er Size adjustment) and the EAD (Exposure at Default), M, and S given.Different combinations of these components will create different capital requirements as computed by the capital model.SME is an acronym for Small- and Medium- Sized Enterprises. Note: at S => $50,000,000.00 there is no SME Adjustment

Severity (LGD)Capital Factors as a % of Total Exposure

Annual Expected Losses (%)Severity (LGD)

July 2014 76

Example of Risk Adjusted Capital ProcessExample Obligor: 5, Facility: D

Obligor Rating 4 5 6Probability of Default 0.27% 0.94% 2.44% Outstanding: 1,000,000$ Facility Rating D D DLoss-Given-Default 30.00% 30.00% 30.00%Expected Loss (PD * LGD) 0.08% 0.28% 0.73% Expected Loss $: 2,820$ Capital % 2.45% 4.32% 5.97% Capital $: 43,167$

Example Obligor: 5, Facility: DCredit Rating 4 5 6Probability of Default 0.27% 0.94% 2.44% Line: 1,000,000$ Collateral Rating D D DLoss-Given-Default 30.00% 30.00% 30.00%Current Utilization of Line 55.00% 55.00% 55.00% Utilization: 550,000$ Utilization-Given-Default 90.00% 90.00% 90.00% Capital $ on Utilization: 23,742$ Expected Loss 0.13% 0.46% 1.20% Capital $ on Unused: 15,108$ Capital % 4.01% 7.06% 9.76% Capital $: 38,850$

Expected Loss $: 2,538$

Line versus Loan capital differential 1.56% 2.75% 3.80%

Commercial Loan

Line of Credit

UGD - Utilization Given Default or LEQ - Loan EquivalencyPortion of the unused commitment or other off-balance sheet commitment such as an L/C, expected to be used by the point of default.With a 90% LEQ, the bank does not expect the avg. commitment to fund to the 90% level. Loans that enter into default are normally funded to 90%.

July 2014 77

Sample Relationship – Input Page

Amount 1,000,000 Amount 1,000,000 Ave. Balance 100,000 Annual Revenue $ 10,000 % Revenue Waived 0.00% % Utilized 40% Fixed or Variable Variable Fixed or Variable Variable Spread 2.2500% Spread 2.2500% Rate 0.0000% New or Existing? New New or Existing? New New or Existing? New New or Existing? New Index 1 Mo LIBOR Index 1 Mo LIBOR Balloon? Yes Maturity (months) 60 Maturity (months) 36 Maturity (months) 36 Maturity (months) 36 Amortize to (mos) 120 Credit Grade 5 Credit Grade 5 Facility Grade E Facility Grade E Upfront Fees ($) Upfront Fees ($) Upfront Fees (%) 0.2500% Upfront Fees (%) Annual Fees ($) Annual Fees ($) Annual Fees ($) Annual Fees (%) Annual Fees (%) Unuse Cmmt Fee%

FTP Rate: 3.40% FTP Rate: 3.40% Spread to FTP: 2.15% Spread to FTP: 2.15%

Product #1Loan

Product #4TM/ Acct Analysis Rev

Product #2Line of Credit

Product #3DDA/ Bus. Free Checking

July 2014 78

Sample Relationship – Output (Analysis) PageInterest Rates as of: Product #1 Product #2 Product #3 Product #4 Product #5 Product #6 Product #7

June 21, 2005Loan Line of Credit DDA/ Bus. Free

CheckingTM/ Acct

Analysis Rev TOTAL

RELATIONSHIP

New or Existing? New New New New Amount $1,000,000 $1,000,000 $100,000 Utilization Rate 40% Fixed or Variable VARIABLE VARIABLE FIXED Rate / Spread 2.25% 2.25% 0.00% Index 1 Mo LIBOR 1 Mo LIBOR Maturity (months) 60 36 36 36 Amortize to (mos) 120 Credit Grade 5 5 Facility Grade E E Annual Revenue $10,000 $10,000Waived Revenue

Monthly Payment $10,877 $1,850 Balloon Payment $576,985 $400,000

12 Mo Ave Bal $965,076 $400,000 $100,000 12 Mo Alloc Cap $49,027 $45,721 $2,000 $3,500 $100,248

12 Mo Interest $53,562 $22,200 $75,76212 Mo Upfr Fees $605 $60512 Mo FTP ($32,813) ($13,600) $3,815 ($42,598)12 Mo Acq Cost ($368) ($508) ($876)12 Mo Cap Credit $2,182 $2,035 $89 $156 $4,461NIM $ $23,167 $10,127 $3,904 $37,198NIM % 2.40% 2.53% 3.90% 2.59%Spread to FTP 2.15% 2.15% 3.82% 2.26%

12 Mo Fees Rev $10,000 $10,000Margl Maint Cost ($20) ($7,500) ($7,520)12 Mo Exp Loss ($3,175) ($2,961) ($6,136)Margl Net Income $19,992 $7,166 $3,884 $2,656 $33,698Taxes ($6,997) ($2,508) ($1,359) ($930) ($11,794)A-T Margl Net Inc $12,995 $4,658 $2,525 $1,726 $21,904Capital Charge ($7,354) ($6,858) ($300) ($525) ($15,037)

Margl SVA $5,641 ($2,200) $2,225 $1,201 $6,866Margl ROE 26.51% 10.19% 126.23% 49.32% 21.85%

Fully Loaded Cost ($3,860) ($1,600) ($100) ($5,560)Full Cost Net Inc $16,132 $5,566 $3,784 $2,656 $28,138Taxes ($5,646) ($1,948) ($1,324) ($930) ($9,848)

A-T FC Net Inc $10,486 $3,618 $2,460 $1,726 $18,289Capital Charge ($7,354) ($6,858) ($300) ($525) ($15,037)

Full Cost SVA $3,132 ($3,240) $2,160 $1,201 $3,252Full Cost ROE 21.39% 7.91% 122.98% 49.32% 18.24%

July 2014 79

Sample Relationship – Output (Analysis) Page – Credit Grade 6Interest Rates as of: Product #1 Product #2 Product #3 Product #4 Product #5 Product #6 Product #7

June 21, 2005Loan Line of Credit DDA/ Bus. Free

CheckingTM/ Acct

Analysis Rev TOTAL RELATIONSHIP

PRIOR RELATIONSHIP

INCREMENTAL CHANGE

New or Existing? New New New New Amount $1,000,000 $1,000,000 $100,000 Utilization Rate 40% Fixed or Variable VARIABLE VARIABLE FIXED Rate / Spread 2.25% 2.25% 0.00% Index 1 Mo LIBOR 1 Mo LIBOR Maturity (months) 60 36 36 36 Amortize to (mos) 120 Credit Grade 6 6 Facility Grade E E Annual Revenue $10,000 $10,000 $10,000Waived Revenue

Monthly Payment $10,877 $1,850 Balloon Payment $576,985 $400,000

12 Mo Ave Bal $965,076 $400,000 $100,000 12 Mo Alloc Cap $66,789 $62,286 $2,000 $3,500 $134,575 $100,248 $34,328

12 Mo Interest $53,562 $22,200 $75,762 $75,762 12 Mo Upfr Fees $605 $605 $605 12 Mo FTP ($32,813) ($13,600) $3,815 ($42,598) ($42,598) 12 Mo Acq Cost ($368) ($508) ($876) ($876) 12 Mo Cap Credit $2,972 $2,772 $89 $156 $5,989 $4,461 $1,528NIM $ $23,958 $10,864 $3,904 $38,726 $37,198 $1,528NIM % 2.48% 2.72% 3.90% 2.69% 2.59% 0.10%Spread to FTP 2.15% 2.15% 3.82% 2.26% 2.26%

12 Mo Fees Rev $10,000 $10,000 $10,000 Margl Maint Cost ($20) ($7,500) ($7,520) ($7,520) 12 Mo Exp Loss ($7,938) ($7,403) ($15,340) ($6,136) ($9,204)Margl Net Income $16,020 $3,462 $3,884 $2,656 $26,021 $33,698 ($7,677)Taxes ($5,607) ($1,212) ($1,359) ($930) ($9,107) ($11,794) $2,687A-T Margl Net Inc $10,413 $2,250 $2,525 $1,726 $16,914 $21,904 ($4,990)Capital Charge ($10,018) ($9,343) ($300) ($525) ($20,186) ($15,037) ($5,149)

Margl SVA $395 ($7,093) $2,225 $1,201 ($3,272) $6,866 ($10,139)Margl ROE 15.59% 3.61% 126.23% 49.32% 12.57% 21.85% (9.28%)

Fully Loaded Cost ($3,860) ($1,600) ($100) ($5,560) ($5,560) Full Cost Net Inc $12,160 $1,862 $3,784 $2,656 $20,461 $28,138 ($7,677)Taxes ($4,256) ($652) ($1,324) ($930) ($7,161) ($9,848) $2,687

A-T FC Net Inc $7,904 $1,210 $2,460 $1,726 $13,300 $18,289 ($4,990)Capital Charge ($10,018) ($9,343) ($300) ($525) ($20,186) ($15,037) ($5,149)

Full Cost SVA ($2,115) ($8,133) $2,160 $1,201 ($6,887) $3,252 ($10,139)Full Cost ROE 11.83% 1.94% 122.98% 49.32% 9.88% 18.24% (8.36%)

July 2014 80

Example of How a Community Bank can Develop a Better

Expected Loss Process

July 2014 81

Moving to Improved AccuracyBuilding out your own loss assumptions

Historical Data ‐ From Inception Historical Data ‐ Last 36 MosLoan Category Loss Severity Loss Frequency Expected Loss Loss Severity Loss Frequency Expected Loss DiffCommercial Lot Loans 11.83% 12.63% 1.49% 11.60% 20.20% 2.34% 0.85%Residential Lot Loans 10.45% 10.59% 1.11% 10.56% 18.67% 1.97% 0.86%Home Equity 30.72% 2.70% 0.83% 33.40% 2.97% 0.99% 0.16%Residential ‐ C&D 1.26% 3.87% 0.05% 1.31% 9.43% 0.12% 0.07%Commercial‐ C&D 8.46% 18.08% 1.53% 8.83% 21.88% 1.93% 0.40%CRE ‐ Owner Occupied 7.46% 2.26% 0.17% 8.05% 2.84% 0.23% 0.06%CRE ‐ Income Producing 5.00% 6.80% 0.34% 4.82% 10.48% 0.51% 0.16%Residential 1‐4 Family 8.57% 6.08% 0.52% 8.43% 7.83% 0.66% 0.14%Commercial & Industrial 15.12% 4.48% 0.68% 16.50% 6.50% 1.07% 0.40%Consumer Other 45.84% 1.32% 0.60% 22.02% 2.42% 0.53% ‐0.07%

Inception Recent 36 mosCommercial Lot Loans 1.49% 2.34%Commercial‐ C&D 1.53% 1.93%

Average 1.51% 2.14% 1.82%

Inception Recent 36 mos AverageComercial & Industrial 0.68% 1.07% 0.875%CRE ‐ Owner Occupied 0.17% 0.23% 0.199%CRE ‐ Income Producing 0.34% 0.51% 0.423%

Highest Risk Assets

Must utilize a Facility Rating of F, G, or H

July 2014 82

Convert to PD and LGDCreates a Matrix of Loss Assumptions

Commercial & IndustrialCredit Pass Probability A B C D E F G HRating Watch of Default % 5.00% 10.00% 20.00% 30.00% 35.00% 40.00% 50.00% 75.00%

1 Highest Quality P 0.05% 0.00% 0.01% 0.01% 0.02% 0.02% 0.02% 0.03% 0.04%2 Superior Quality P 0.25% 0.01% 0.03% 0.05% 0.08% 0.09% 0.10% 0.13% 0.19%3 Above Avg Quality P 0.68% 0.03% 0.07% 0.14% 0.20% 0.24% 0.27% 0.34% 0.51%4 Average Quality P 0.87% 0.04% 0.09% 0.17% 0.26% 0.31% 0.35% 0.44% 0.66%5 Acceptable P 1.07% 0.05% 0.11% 0.21% 0.32% 0.38% 0.43% 0.54% 0.80%6 Special Mention W 4.29% 0.21% 0.43% 0.86% 1.29% 1.50% 1.72% 2.15% 3.22%7 Substandard W 16.50% 0.83% 1.65% 3.30% 4.95% 5.78% 6.60% 8.25% 12.38%8 Doubtful W 100.00% 5.00% 10.00% 20.00% 30.00% 35.00% 40.00% 50.00% 75.00%9 Loss W 100.00% 5.00% 10.00% 20.00% 30.00% 35.00% 40.00% 50.00% 75.00%

CRE ‐ Owner OccupiedCredit Pass Probability A B C D E F G HRating Watch of Default % 5.00% 10.00% 20.00% 30.00% 35.00% 40.00% 50.00% 75.00%


July 2014 83

Convert to PD and LGDCreates a Matrix of Loss Assumptions

CRE ‐ Income ProducingCredit Pass Probability A B C D E F G HRating Watch of Default % 5.00% 10.00% 20.00% 30.00% 35.00% 40.00% 50.00% 75.00%


Commercial Lot or C&DCredit Pass Probability A B C D E F G HRating Watch of Default % 5.00% 10.00% 20.00% 30.00% 35.00% 40.00% 50.00% 75.00%


July 2014 84

Consumer Loan Pricing

July 2014 85

Consumer Lending

• Highly regulated with more to come Process has become cumbersome and not client friendly

• Very data intensive• Best practice is to use risk-based scorecards• Multitude of products and components• Origination and underwriting are heavily impacted by

technology Aligns better with online banking

• Multiple channels Branch, phone, internet, direct, indirect, alliance programs, mobile,

mail, etc.• Marketing intensive for many aspects of the loans• Requires more segmentation and behavioral analysis• Constantly changing and needs to improve how

banks respond to local market conditions

July 2014 86

Consumer Loan Profitability – Key Drivers

• Pricing Discipline Risk adjusted pricing, cross-sell focus, and get paid for customer

service Profit oriented relationship management and value added selling Measure officers on risk adjusted profitability and align incentives

• Sales and Negotiating Skills Constant training of sales force Conduct meetings that build solutions that enhance the

relationship Be creative, be responsive, and keep negotiations centered

• Operating efficiency and credit decision timeliness You can’t price or sell your way around poor underwriting and

inefficient loan origination, servicing, collection, and compliance Align operations with sales process, eliminate redundancy

• Management reporting and incentives If you measure “IT” – “IT” will get better

July 2014 87

Consumer Lending Pricing StrategyKey aspects - to drive the right discipline

• Loan profitability reviewed at the “price-point” level: By channel, product, term, tier, lien, utilization, and LTV All assets are priced to earn a minimum ROE and/or ROA

• Pricing models are based on a cash flow analysis Avoid the acctg. treatment for fees, expenses, and

reserves Forecasted volumes and product mix are used to project

the “steady state” portfolio for each product• Expenses - direct and indirect NIE levels

Best Practice is to use “Direct Contribution Margin”• Incorporate efficiencies and project expenses

fixed and variable components

July 2014 88

Pricing Model Output and Validation

Pricing Model Output

• Calculates lifetime loan profitability Risk-based returns Product specific drivers Provides potential steady-state

portfolio $ Product costs, volumes and drivers

updated quarterly Interest rates and FTP updated

weekly• Can be driven down to “price-

point” detail Profitability by channel and product By LTV, lien position, tier and term

• Should supports profit modeling for new product development

Pricing Model Validation

• Actual results are reconciled against pricing forecast

• By product and channel• Monthly interest rate variances

are segmented into different categories

• Tier and LTV mix issues• Timing, exceptions, COF,

premiums, specials and unidentified items

• Serves as an indicator of potential operating or modeling issues

• Pricing model can be adjusted for tier & LTV mix variances.

• Policies and procedures may need to be examined.

July 2014 89

Consumer - Product Pricing Summary

Sample Rates from 2005using projected volume mix Direct Direct Direct HE Loan HE Loan Total Indirect Indirect Indirect Total Total

Auto Marine RV HELOC 80% LTV 90% LTV Direct Auto Marine RV Indirect ConsumerInterest Income (Rate) 8.40% 7.26% 7.41% 6.23% 7.27% 8.24% 6.98% 7.82% 7.03% 7.18% 7.19% 7.06%

Cost of Funds 4.05% 4.31% 4.30% 3.29% 4.63% 4.64% 3.86% 4.05% 4.23% 4.21% 4.20% 4.00%

Dealer Reserve Amort. -0.95% -0.61% -0.67% -0.68% -0.27%

Net Interest Margin 4.35% 2.96% 3.12% 2.94% 2.63% 3.60% 3.11% 2.81% 2.18% 2.30% 2.31% 2.79%

Net Charge Offs 0.84% 0.27% 0.50% 0.10% 0.10% 0.50% 0.25% 0.75% 0.60% 0.65% 0.64% 0.40%

Non Interest ExpenseOrigination/Servicing 1.70% 0.27% 0.40% 0.57% 0.37% 0.37% 0.57% 0.94% 0.12% 0.25% 0.28% 0.46%Marketing

Pre-Tax 1.81% 2.43% 2.22% 2.27% 2.16% 2.73% 2.29% 1.12% 1.46% 1.40% 1.39% 1.93%

ROA on Total Loan ADB % 1.18% 1.58% 1.44% 1.47% 1.41% 1.78% 1.49% 0.73% 0.95% 0.91% 0.90% 1.26%

Return on Allocated Equity 15.95% 24.74% 22.24% 23.33% 22.38% 28.43% 23.44% 12.35% 13.76% 13.90% 13.65% 19.52%

Equity Allocation 7.26% 6.31% 6.35% 6.38% 6.28% 6.28% 6.41% 6.35% 6.48% 6.30% 6.38% 6.40%

% of Portfolio 8% 5% 3% 52% 16% 16% 100% 12% 43% 45% 100%

% of Total Consumer 60% 40%

July 2014 90

Direct Auto Pricing SummaryBased on Projected Volumes and Profitability

using projected volume mixA B C D Avg A B C D Avg A B C D Avg

Interest Income (Rate) 6.93% 6.93% 6.67% 7.38% 10.27% 13.16% 7.65% 7.38% 8.33% 10.69% 13.44% 8.33%

Cost of Funds 4.19% 4.19% 4.13% 4.05% 3.96% 3.74% 4.07% 4.11% 4.02% 3.94% 3.72% 4.05%

Net Interest Margin 2.74% 2.74% 2.54% 3.34% 6.31% 9.42% 3.58% 3.27% 4.31% 6.76% 9.72% 4.28%

Net Charge Offs 0.60% 0.60% 0.60% 0.94% 1.48% 2.43% 0.88% 0.59% 0.94% 1.47% 2.39% 0.88%

Non Interest ExpenseOrigination/Servicing 0.45% 0.45% 0.75% 0.82% 1.07% 2.34% 0.93% 1.22% 1.34% 1.74% 3.80% 1.51%Marketing

Pre-Tax 1.69% 1.69% 1.20% 1.57% 3.76% 4.64% 1.77% 1.46% 2.03% 3.54% 3.52% 1.90%

ROA on Total Loan ADB % 1.10% 1.10% 0.78% 1.02% 2.44% 3.02% 1.15% 0.95% 1.32% 2.30% 2.29% 1.23%

Return on Allocated Equity 18.29% 18.29% 12.96% 12.75% 24.42% 20.13% 14.49% 15.78% 16.50% 23.00% 15.27% 16.42%Equity Allocation 6.00% 6.00% 6.00% 8.00% 10.00% 15.00% 7.43% 6.00% 8.00% 10.00% 15.00% 7.43%

% of Product Mix 100.0% 68.0% 15.0% 8.0% 9.0% 68.0% 15.0% 8.0% 9.0%

% of Direct Auto 7.0% 36.0% 36.0%Direct

A B C D Avg A B C D Avg AutoInterest Income (Rate) 8.30% 8.75% 11.06% 15.40% 9.23% 11.34% 12.23% 13.92% 11.72% 8.40%

Cost of Funds 4.05% 3.96% 3.87% 3.65% 3.98% 3.96% 3.87% 3.78% 3.93% 4.05%

Net Interest Margin 4.26% 4.79% 7.18% 11.74% 5.24% 7.39% 8.36% 10.14% 7.79% 4.35%

Net Charge Offs 0.59% 0.93% 1.46% 2.33% 0.87% 0.58% 0.92% 1.43% 0.71% 0.84%

Non Interest ExpenseOrigination/Servicing 2.27% 2.51% 3.28% 7.05% 2.82% 4.76% 5.26% 6.91% 5.03% 1.70%Marketing

Pre-Tax 1.40% 1.35% 2.45% 2.36% 1.56% 2.05% 2.19% 1.80% 2.05% 1.81%

ROA on Total Loan ADB % 0.91% 0.88% 1.59% 1.53% 1.01% 1.33% 1.42% 1.17% 1.33% 1.18%

Return on Allocated Equity 15.13% 10.98% 15.92% 10.21% 14.13% 22.21% 17.78% 11.68% 20.55% 15.95%

Equity Allocation 6.00% 8.00% 10.00% 15.00% 7.43% 6.00% 8.00% 10.00% 6.68% 7.26%

% of Product Mix 68.0% 15.0% 8.0% 9.0% 75.0% 16.0% 9.0% 0.0% 8.0%

% of Direct Auto 12.0% 9.0% 100.0%

Direct Auto - 48 mo Direct Auto - 36 mo

Direct Auto - 72 mo Direct Auto - 66 mo Direct Auto - 60 mo

July 2014 91

HELOC Pricing SummaryBased on Projected Volumes and Profitability

A B C D Avg A B C D Avg HELOCInterest Income (Rate) 6.86% 7.33% 7.76% 8.90% 6.95% 5.95% 6.44% 6.92% 8.28% 6.05% 6.23%

Cost of Funds 3.31% 3.24% 3.18% 3.04% 3.30% 3.30% 3.23% 3.16% 3.00% 3.29% 3.29%

Net Interest Margin 3.55% 4.09% 4.58% 5.85% 3.65% 2.65% 3.21% 3.76% 5.28% 2.76% 2.94%

Net Charge Offs 0.10% 0.10% 0.10% 0.10% 0.10% 0.10% 0.10% 0.10% 0.10% 0.10% 0.10%

Non Interest ExpenseOrigination/Servicing 1.07% 1.15% 1.44% 2.76% 1.12% 0.41% 0.44% 0.56% 1.09% 0.43% 0.57%Marketing

Pre-Tax 2.37% 2.84% 3.03% 2.99% 2.42% 2.14% 2.67% 3.09% 4.09% 2.23% 2.27%

ROA on Total Loan ADB % 1.54% 1.84% 1.97% 1.94% 1.57% 1.39% 1.73% 2.01% 2.66% 1.45% 1.47%

Return on Allocated Equity 25.66% 23.05% 19.72% 12.95% 25.13% 23.14% 21.67% 20.10% 17.72% 22.88% 23.33%

Equity Allocation 6.00% 8.00% 10.00% 15.00% 6.38% 6.00% 8.00% 10.00% 15.00% 6.38% 6.38%

% of Product Mix 90.0% 6.0% 2.0% 2.0% 90.0% 6.0% 2.0% 2.0% 52.0%

% of HELOC 20.0% 80.0% 100.0%

HELOC ($5,000-$15,000) HELOC ($25,001 and Over)

July 2014 92

Best PracticesScorecards and Risk-Based Pricing

• Good for direct/indirect loans, home equity, and small business

• Scorecards provide guidelines to make credit decisions Applications can be automatically

decisioned Underwriters - determine the

adequacy of the applicant and collateral

• Risk-based pricing models consider: Credit profile of the borrower Age and condition of the collateral Loan-to-value (LTV) ratio and term to

maturity Assigns risk factors to each credit

grade by LTV Segment information helps reduce risk

• To achieve finer levels of “segment granularity,” incorporate: FICO score Debt-to-income ratio Combined LTV Loss-given-default Local housing price index Lien position Depth of overall customer

relationship with the bank• Goal is to test and then

deploy various combinations of market and customer metrics Helps identify distinct customer

groups and the appropriate pricing strategy for each

July 2014 93

Application ScorecardsFast Efficient Process – Faster Decisions

Number of Trade Lines

1 A E E E2 B E E E3 B E E E4 C C F F5 C C F F6 D D D F7 D D D F8 D D D F9 G H I J10 G H I J11 G H I J

Additional Scorecards developed as part of the National Scorecard Project:* No Record, No Trade Line Scorecard * Subprime Scorecard

Never

Maximum Level of Delinquency on Credit Bureau ReportEver 30 Days Delinquent

Ever 60 Days Delinquent or Minor

Public Record

Ever 90 Days Delinquent or Major

Public Record

July 2014 94

Insights about Behavioral DifferencesHome Equity – better targeting, pricing, and portfolio mgt.

Consumer Behaviors

Activation and Utilization

Dig deeper for

immediacy and nature of borrowing

need

Influences activation, level, and pattern of

outstandings

Determine the draw‐down

expectation

For ExampleFunding

education is different than

home improvement

Credit Risk

Borrowing for consumables vs. asset building

Might have different credit risks associated with each

Elasticity of DemandTake‐Up Rate

Quantify how consumer demand varies in accordance with changes in lending rates

Use this information to refine pricing

strategies by segments

Enhances precision marketing and pricing strategies

Duration and Prepayment

Risk

PurposeInfluences length of need and alternatives to refinance

July 2014 95

Decisions with the New InsightsHome Equity – better targeting, pricing, and portfolio mgt

Decisions

Targeting

Identify more profitable prospects

Refine product positioning

Big OpportunityCross‐sell and account

consolidation

Pricing Optimization

Price optimally based on elasticity

and expected profitability

Portfolio Management

Exposure management

Usage stimulation

Retention

Source: Novantas, LLC

July 2014 96

Progressive Home Equity LendersRefine Risk-Based Pricing for Tightly-Defined Segments

• Goal is to achieve finer levels of “segment granularity”

• Through customer-related factors into pricing schematics FICO SCORE Debt-to-income ratio Combined LTV ratio Loss-Given Default Local Housing price index Lien position Depth of overall customer relationship with the bank

• Test and then deploy various combinations of market and customer metrics Identifies distinct customer groups and the appropriate pricing

strategy for each

July 2014 97

Concluding Remarksand

Remaining Questions

July 2014 98

Summary of Lessons Banks Should ConsiderCommit to a Pricing Process and Remain Disciplined

• Make Pricing a Process and Ongoing Practice to Drive Earnings Leverage what you have learned about “Balance Sheet

Management”• Price based on what the customer is willing to pay,

not just your own costs• Improve your ability to forecast volume with

different pricing scenarios• Define and sustain your price image and “stick to it”• Know your best and most profitable clients and

create pricing and service procedures that cater to these clients

• Know how and where to use price as a promotion technique

July 2014 99

Summary of Lessons Banks Should ConsiderCommit to a Pricing Process and Remain Disciplined

• Look at your product line – not just the individual products

• Know how products link in the mind of your customers (“bundles” or a la carte)

• Group and manage branches in demand-based pricing zones

• Anticipate competitor responses to your pricing moves

• Manage pricing strategy as diligently as anything you do

• Leverage technology and the data available to be ahead of your competitors

July 2014 100

Appendix

July 2014 101

Strategies for Non-Maturity DepositsHow do these currently perform? Longer or shorter term in nature ?

Separate the rate sensitive from non-rate sensitive• Goal - retain and pay for the rate sensitive avoiding increases to the non-rate sensitive

Apply account segmentation techniques• Create a Tiered Pricing discipline

Market based pricing, internet specials, bundles, and blitz campaigns

Utilize CD pricing to attract rate sensitive customers to move out of non-maturity deposits

Understand the value of a depositor’s total relationship

Leverage the convenience factor

Free Checking with alignment of fees and penalties• Change to free with no checks, no paper statements, a debit card, ACH or bill-pay, etc.

Incorporate Channel Differentiation

July 2014 102

Strategies for CDs

Break CDs into maturity time bands

• Time bands are designed so that off maturity specials fall within the same time band as competing regular CDs

• Specials need to roll into regular CD maturities and in same time band

Reserve regular CDs for non-rate sensitive customers

• It is possible you may want to offer rates below competition

Place CD specials at or near the top of market rates

• Timing may be the key to special CD rates• Again - design all specials to roll into regular CDs at maturity

Know when your CDs mature and roll

• If many are maturing and rolling into reg. CDs - don’t offer specials

If the maturing CDs are low, that is a better time to offer specials

July 2014 103

Introduction of New Products

• Many times existing products are perceived to be non-competitive So let’s introduce a new one

• Actual Case Small Business Checking had 15,000 accounts Included certain fees for service

Market Mgr. pushed for a new product that was to be a “Business Free Checking”

Guess what Happened? How Long do you think it Took? How Much Annual Revenue was lost? How Does this Happen and Why?

July 2014 104

Key Questions ALCO should AskWhen Introducing New Products

How will we train our workforce on when to use and when to move a client ?

Do we fully understand the impact to service charges ?

How do we avoid moving existing customers too fast ?

How will we incent to generate the right behavior ?

How does this impact our mix and sensitivity ?

What is the profitability of the product ?• Structure, incentives, balance requirements, bundled opportunities

Do we introduce the product in every market or targeted markets ?

See a Discussion of “Teaser Rates” in the Appendix

July 2014 105

Below Market Pricing Notes

• Policies Banks grant lenders broad control over pricing with limited oversight Other extreme is centralized price setting where no one has a clue as to the market drivers

• Incentives Focus on asset growth only – sacrifices yield every time – never ask for deposits

• Lack of adequate training or mentoring Experience teaches a lender he can win without being the lowest price They leverage value-added product or service elements Without adequate negotiating skills – price becomes the only factor

• Relationship subsidies Betting on future ancillary business which may or may not materialize Once the transaction closes – the officer or bank never revisit the promise

• Increase use of profitability models and setting hurdle rates Sometimes creates the minimum which becomes the target Use models to understand the profitability of a price

Then sell the customer based on their needs and willingness to pay• Lack of market information

Most powerful driver of poor pricing Banks that operate without market data often see pricing erosion even when market pricing is

on the rise All lenders see such a limited amount of deal flow but are ready to give their view on the

market Limited market intelligence causes lenders to price new deals based on the last aggressive

bid they saw in the market• Banks can strengthen their performance:

Through bank-wide implementation of best practices Ongoing tracking of loan and deposit market trends Provide accurate and enhanced market intelligence to the line

July 2014 106

Teaser Rates – When Appropriate

• Example: Accelerated Savings created to help be more competitive in the market and to retain and gather new funds…………..90 day rate adjusts to normal rate Understand impact to existing deposits and impact to “rate

sensitive” vs. “non-rate sensitive” clients Impact to competitors products and customers How your work force will sell and how you will incent to sell Fully define the requirements a customer is to meet to get higher

rate Run sensitivity models on what happens – wake the “sleeping

bears” Set target levels based on strategic mix of your balance sheet while

understanding impact to current product mix Be patient before you run campaigns again and until you have all

the data – learn from each test and campaign Know up front if the product is for “new money” or to retain Better understand which markets you sell into which ones you don’t

July 2014 107

Repricing Discipline

Behavior Focus Data Requirements Data Source Application

Your institution’s repricing

Time series of rates paid by category

Institution records Forecasts of your own repricing

Your institution’s deposit balances supply sensitivity

Time series of deposit balances

supplied by category

Institution records Forecasts of your own depositor

supply reactions to rate changes

(elasticity)

Your market’s repricing


Institution records or third-party source

Forecasts of your local market’s

repricing

Each competitor’s repricing


Institution records or third-party source

Forecasts of your specific competitor’s

repricing

Specifics of Behaviors that need to be Analyzed

Source: Bank A/L Management, McGuire Performance Solutions, Inc.

July 2014 108

Repricing and Deposit Supply RelationshipsOld Benchmarks – May or May Not Pertain Anymore

Category

DDA

Typical Repricing

n/a

Balance Sensitivity to Rising Interest Rates

Typically Minimal

Notes & CommentsInsensitivity is very

Common

NOW 5-10 bp Typically Minimal Insensitivity is very Common

Savings 15-25 bp Typically very Limited

Significant Variation among Institutions

Low Tier MMDA 20-35 bp Typically very Limited

Significant Variation among Institutions

High Tier MMDA 75-85 bp Can be quite Sensitive

Repricing is Important to Stability

Indexed Tier MMDA

90-95 bp Can be very Sensitive

Repricing is Crucial to Stability

Values presented are rough central tendencies of

behaviors seen in recent MPS statistical

analyses of client specific

deposit data

Note: Repricing is calculated at 12 months, per

100 bp rate shock. Business categories similar to personal if small business oriented. Balance sensitivity is defined in light of repricing

behaviors

BENCHMARK DEPOSIT BEHAVIORS

Source: Bank Asset/Liability Management, McGuire Performance Solutions, Inc.

July 2014 109

How to get the Pricing Process Started

Reporting Data Pricing

Technology

Price Execution

and Controlling

Price Guidelines

Price Organization

Price Formation

Price Analysis

Analytics• Analysis of competitors, customers, costs and business strategy

• Analysis of pricing org. and price data across several dimensions (channel, customer, region,)

Execution

• Implementation of training and education

• Analysis of transaction prices and client value

• Reporting and interventions

Analytics

• Definition of Pricing Strategy

• Determination of (revised) list prices

• Differentiation and adjustment of list prices for customer segments

• Decision on instruments and

guidelines for practice of price concessions• Determination of

market price

• Decision of price management org.• Staffing of key roles

July 2014 110

South Carolina Bankers School

2007 BenchMark Consulting International, N.A., Inc. All Rights Reserved.

Brian King BenchMark Consulting International Risk-based pricing, in the simplest terms, is alignment of loan pricing with the expected loan risk. Typically, a borrower’s credit risk is used to determine if a loan application will be accepted or declined. That same risk level may also be used to drive pricing. This means charging a higher interest rate for a higher risk transaction and a lower rate for a lower risk transaction. While all large banks have some form of risk-based pricing, small to medium- sized banks are now investigating how to formally leverage this pricing strategy. A balanced pricing strategy is comprised of three critical elements. First, the bank must have solid credit quality. A seasoned bank executive recently commented, “Regardless of the pricing, a bad loan is a bad loan is a bad loan.” If the borrower defaults, the net result is a charge-off that negatively impacts credit reserves and bank earnings. The second important component is profitability. Pricing for closed loans must result in the net spread required for the portfolio to cover expenses and generate desired return. Many banks have found that pricing more aggressively will generate more loans – but are they profitable loans? The final component of a balanced pricing strategy is portfolio growth. There is a constant challenge to grow the portfolio to increase earnings year-over-year. A balanced pricing strategy should support portfolio growth generated by profitable, quality loans. The result is a balanced pricing strategy that can be best summarized as the proverbial three-legged stool of quality, profitability, and growth. Each is important, but if one is missing, the stool will tip over.

Risk of Flat-Rate Pricing While most large banks already have risk-based pricing strategies in place, this is often a new venture for small or medium-sized banks. Even if they “know” to price risky loans higher, implementing a formal strategy is a way to create a process that drives consistent results. Banks without a formal risk-based pricing approach typically use a flat-rate pricing model where all customers receive the same rate. The use of the flat-rate pricing model may be the result of a lack of technology to support a more sophisticated pricing strategy – or just an approach to “keep it simple.” The inherent problem with a flat-rate pricing strategy is that the bank will typically close a disproportionate share of lower credit quality loans since the higher credit quality borrowers can

Risk-Based Pricing – Back to the Basics

BenchMark Consulting International 2 Risk-Based Pricing – Back to the Basics– January 2007

obtain better pricing through other avenues (i.e. banks offering risk-based pricing!). Even if the higher credit quality borrowers apply for a flat-rate priced loan, these borrowers will often have a lower closing rate as they find better pricing elsewhere. Banks can see this for themselves by tracking the percentage of loans approved but not booked divided by total loans approved by credit score band. Lower credit quality borrowers see the flat-rate pricing model as more attractive than a risk-based pricing model and typically will have a higher closing rate. When a bank sets a flat-rate price based on a certain mixture of credit risk customers – and then closes a higher percentage of lower credit quality loans - the bank is not adequately compensated for the risk level of the portfolio. Zions Model One bank who recently moved from flat-rate pricing to a risk-based pricing strategy is Zions Bancorporation. The bank leveraged clearly defined credit acceptance criteria and used that information to establish risk-based pricing. The result was a matrix that outlined the pricing criteria and the associated pricing premium for various risk grades. For example, Zions indicated that for the direct unsecured product, the loss distribution is more than 12 times greater for borrowers with a bankruptcy score higher than 580 or a credit score of less than 670. Zions used this information to classify these loans as ‘auto-decline’. In an interesting twist, the better credit score did not always generate the lower rate. While the credit score of 730 and above did generate the lowest pricing as expected; the credit score of 671 – 699 generated a 22% lower loss distribution than the credit score of 700 – 729. This would result in a lower risk-based price for the 671 – 699 credit score borrowers versus the 700 – 729 credit score borrowers. While this example is uncommon, the due diligence and tracking of actual loan performance is critical when establishing a credible pricing model based on a bank’s actual portfolio results. Zions’ risk-based pricing strategy also analyzes loan originator or sales lender overrides that occur

outside the standard acceptance range. Based on the historical performance of overrides, Zions was able to determine the premium for certain score ranges that is required to drive an acceptable level of return for these credit overrides. This process allows lenders to request an “extension” and enables the bank to make these overrides on an as-needed basis with the appropriate pricing required to maintain profitability.1 Pricing Model Basics While the Zions example used bankruptcy score and credit score, some of the other variables that may be included in a risk-based pricing matrix are collateral, loan-to-value, debt-to-income, and origination channel. Additional variables that impact the overall pricing model are expected loss, pre-payment rate, anticipated fee income, as well as origination cost, servicing cost, capital requirements, and cost of funds. Risk-based pricing is especially valuable when dealing with near-prime (credit score of 630 to 680) or sub-prime lending (credit score below 630). The cost of capital can be appropriately applied by credit grade - which can be calculated as part of a RAROC (risk-adjusted return on capital) pricing model. Ultimately, the bank can modify the pricing based on the amount of increased or decreased risk and associated capital required as part of the risk-based pricing strategy. Generally, pricing models are dynamic and continually updated based on the bank’s experience as well as external factors such as cost of funds. It is important that a bank have the availability of data at the individual loan level over the life of the loan. The bank must be able to assess how they predicted the loan would perform against how the loan actually performed. There are other types of pricing models available. Relationship pricing models evaluate the overall value of the customer to the organization across all products. Marketing models compute competitor offerings and pricing to determine the available pricing ranges for certain products in

1 Padmanaban, Naagesh. Panel Discussion. Consumer Bankers Association Credit & Collections Conference, New Orleans. June 2006.


specific markets. Pricing optimization models determine the price elasticity for each borrower. Regardless of the type of pricing model, an element of risk-based pricing must be included to make sure that the risk taken by the bank is aligned with the rate and fees paid by the borrower. Near-prime & Sub-prime Lending Historically, many banks had a policy of offering lending products only to “prime” borrowers (generally defined as a credit bureau score of 680 to 700 or higher). Many banks now offer loans to near-prime credit borrowers with credit scores of 630 – 680. Some banks have expanded into the sub-prime lending market in an effort to drive more loan volume and recover some of the costs spent on applications already taken or processed. While individual banks have varying thresholds, many define sub-prime lending as a credit bureau score of 630 or lower. The avoidance of sub-prime lending by banks has been shifting. The 2005 BenchMark Home Equity Study found that half of the participants had a sub-prime lending strategy of either a pass-through program whereby they forward declined applications to a third-party for consideration or a portfolio strategy of retaining sub-prime loans on the bank’s books. While the majority of banks have historically avoided sub-prime borrowers “on the books”, virtually all banks have sub-prime home equity loans and lines within their portfolio. How does this happen? Generally, it is exceptions, overrides, and one-time credit policy violations that create additional risk exposure over time. The result is that virtually all banks have some sub-prime loans in their portfolio and those loans may not be priced according to their risk-level. While certain overrides and exceptions are needed based on competitive factors or the value of the bank’s relationship with the customer, it is important to note whether the bank is making a credit underwriting exception or a pricing exception or both.

% of HE Portfolio that contain Subprime (CBR score < 630)

97%

The ability for banks to reach deeper into the credit spectrum provides a way to lift the booked loan volume without necessarily increasing the applications. Because of the costs already incurred in processing the application, the bank’s ability to close more loans also helps to immediately recover those costs. In the 2005 CBA Home Equity Lending Study conducted by BenchMark Consulting International, 11% of home equity loans and 6% of home equity lines of credit booked during the 12–month study period were sub-prime credit. This was approximately a 20% increase in the amount of sub-prime borrowers within the new home equity products booked, year-over-year.

Percentage of New Home Equity Accounts with Credit Score < 630

(subprime)

0%

3%

6%

9%

12%

2005 CBA Home Equity Lending Study

Lines 5% 6%

Loans 9% 11%

2004 2005

2005 CBA Home Equity Lending Study


The credit decision, alone, is challenging for near-prime loans that are between the 630 - 680 credit bureau score range, or even the sub-prime home equity – which is defined as a credit bureau score of less than 630. For banks that choose to lend within these credit score bands, it is essential that an appropriate rate is received in return for the increased risk of default. In addition, the servicing and default management for near-prime and sub-prime require different processes and policies. Banks who extend into this space must be fully aware of the risk associated with these loans and adjust underwriting criteria and loan pricing, as required, to mitigate the risk. Lender Overrides and Exceptions While banks may develop sophisticated pricing models and even pursue opportunities in the near-prime and sub-prime areas with confidence, there is one challenge that seems to continue – loan originator (LO) overrides and exceptions. Many banks put such a high emphasis on the LO and their judgment and evaluation of a borrower that many loans are made which ignore the risk-based pricing models. In some cases, the LO may either approve a loan that the automated underwriting system declines, or the LO may offer a lower than suggested interest rate. In some cases, the LO may do both by approving a lower credit score borrower and providing a lower-than-expected rate and fee. Evidence across multiple banks suggest that while, anecdotally, we would like to believe the LO knows best, these overrides and exceptions perform worse than the loans made within bank guidelines. From BenchMark’s work at 39 of the top 50 US Banks, we have found that credit policy and underwriting overrides and exceptions typically perform at least twice as bad as those loans made within policy. The ability to restrict the LOs from making overrides and exceptions is difficult in a sales-focused environment without completely removing their autonomy and empowerment. By tracking these exceptions and adding a risk-based price premium based on the increased risk, LOs can make fact-based decisions and control behavior that may be negatively impacting future portfolio performance.

Risk-Based Pricing to Increase Loan Growth While some banks find credit officers tightening the credit policies in today’s tough economic times, anticipating the coming storm of increased delinquency and degraded portfolio performance, others are looking to risked-based pricing as a way to drive more volume. One leading industry bank executive recently commented the challenge at his bank is shifting from a risk-avoidance mindset to a risk-return mindset. This particular bank has an average credit bureau score of 730 and a very low charge-off rate but is challenged to continue to grow the home equity portfolio. This bank sees significant pricing competition in the “A” paper where margins have been compressed by heated competition. In this example, one option may be buying slightly deeper with the appropriate credit-risk underwriting and the associated risk-based pricing applied. The bank will generate more loan volume and capture borrowers with a 680 - 700 credit bureau score that are priced according to the risk-level. Another option is to avoid holding these loans in portfolio and pursuing a strategy to refer these applications to a third party or sell the closed loans. If a decision is made to put these loans on the books, it is critical that the bank determine the increased probability of default, increased cost of capital, and other loan pricing variables to calculate the appropriate pricing for these near-prime loans. By appropriately leveraging risk-based pricing, this firm will be positioned to generate more loan volume with interest rates tied to the associated loan risk. FACT Act Recent consumer protection was created by the Fair and Accurate Credit Transactions Act of 2003 (FACT Act). Lenders will likely face additional challenges with the risk-based pricing provisions under Section 311 of the FACT Act of 2003 that will require banks to provide risk-based pricing notices. This means that lenders must issue risk-based pricing notices whenever information in the borrower credit file causes them to pay an interest

rate or fee that is “materially less favorable.” This could create some additional steps for risk-based pricing institutions, but will not substantially curb the appeal or practice of pricing for risk. Conclusion The Federal Reserve has reported a declining trend in delinquency over the past 10 years, which has been further validated by BenchMark’s CBA studies and direct work with bank clients. However, many key leading indicators point to difficult times ahead. With expected increases in delinquencies, interest rates, and expected losses –

some lenders are tightening credit standards because of concern of loan quality. Other banks are extending the reach into near-prime and sub-prime credit as a way to keep the loan volume at prior record levels. There are many variables to consider when evaluating a risk-based pricing strategy. For a balanced strategy, the firm must have an appropriate level of focus on quality, profitability, and growth. Now may be the time to evaluate your firm’s pricing strategy and determine corrective actions that are needed.

J. Brian King is the Mortgage and Consumer Lending practice manager at BenchMark Consulting International. He has extensive background in mortgage and consumer lending, strategic planning and product development. BenchMark Consulting International has specialized in improving the financial services industry since 1988. The company is a management consulting firm that improves the profitability of its financial services customers through the delivery of management decision-making information and change management services to realize the benefits of business process changes. BenchMark Consulting International’s expertise is in the measuring, designing, and managing of operational processes. The firm has worked with 38 of the top 50 (in asset size) commercial banks, all 14 automobile captive finance corporations, several of the largest consumer finance corporations and many regional and community banks throughout the United States. Internationally, BenchMark Consulting International has worked with the five largest Canadian commercial banks, more than 40 European organizations in 11 different countries, in addition to financial institutions in Latin America, Australia and Asia. The company is a wholly owned subsidiary of Fidelity National Information Services, Inc., with clients in more than 50 countries and territories, providing application software, information processing management, outsourcing services and professional IT consulting to the financial services and mortgage industries. BenchMark Consulting International has dual headquarters in Atlanta, Georgia and Munich, Germany. For more information please visit www.benchmarkinternational.com.

BenchMark Consulting International14 Piedmont Center NE, Suite 950

Atlanta, GA 30305 (404) 442-4100

www.benchmarkinternational.com

Why Do We Need a New Pricing Model, Anyway?Intricate evaluation of the profitability of individual

loans and relationships is more cost-efficient today,thanks to advances in technology. It’s fortunate thatcost-efficiency is attainable, because the need to evalu-ate the risk-reward relationship is more critical tobankers than ever. Multiple-pricing alternatives andcross-sold relationships mean that bankers cannot justlook at a single loan. Instead, they frequently must usethe loss-leader marketing philosophy to meet competi-tion.

The entry of unregulated competitors and borrow-ers’ willingness to haggle over the last five basis pointsindicate that managing interest-rate sensitivity, overallreturn, and risk-reward has to be considered at the linelevel, not just on a macro-basis. So banks must providelenders with tools to quickly and efficiently determinethe spreads necessary on loans of various structure,tenor, and pricing level. Whether it’s a customer thebank has supported for 40 years or one that the bankwould like to add to its portfolio, the customer expectsa quick response to alternate pricing quotes.

Who Should Own the Model?The pricing analysis incorporates aspects of com-

mercial lending, finance, credit, accounting, asset liabil-ity committee (ALCO), and risk management. Theinput of all the parties must be obtained, even thoughsome issues will require compromises. The model,

however, must have one owner to ensure proper docu-mentation, training, applications, and future develop-ment. Often, the function with the proper technicalresources and portfolio orientation to manage thisprocess will be risk management. Care must be taken,however, to ensure that the model is viewed as ourmodel instead of that model. It is especially importantthat the commercial lending department accept owner-ship of the model, because the loan officers and ana-lysts will be the people most immediately impacted byits use.

Who Should Calculate Pricing Return?Some institutions may wish to centralize the loan

pricing function and perform pricing analyses forlenders on a request basis. This structure has the benefitof discouraging “gaming” of the model and ensuresconsistency and accuracy in applying the desiredmethodology. However, unless this area is adequatelystaffed and available at all hours (since that is whenbankers work now), it will not provide adequateresponse time for lenders. This structure also could con-vey the concept that management does not trust linestaff to manage this aspect of their relationships. Byallowing lenders to immediately access such a modelduring negotiations with a customer (so that an appro-priate pricing and loan structure can be designed), theyare empowered to add value to the company and servethe customer better.

48 The Journal of Lending & Credit Risk Management June 1999

Developing and ImplementingCommercial Loan Pricing Models

by Michael Fadil and Larry Hershoff

Many banks are re-evaluating their commercial loan pricing models to ensure that they are accu-rately pricing loans in relation to increased competition from other banks and nonbanks. Theauthors were responsible for developing and implementing such a model at Citizens FinancialGroup, a $18 billion multi-bank holding company. The following is a list of various issues thatfinancial institutions must evaluate in this process.

© 1999 by RMA. Fadil is credit risk portfolio manager for Fleet National Bank’s Business & Entrepreneurial Group, whichis Fleet’s small business lending line of business. Hershoff is vice president in the Commercial Loan Syndication Group atCitizens Bank of Rhode Island and an adjunct lecturer in finance at Bryant College in Smithfield, Rhode Island.

IssuesIssues inin

Lending...Lending...

Logistically, a centralized function also allows forquick, consistent updates of changes to the model.Technological advances, fortunately, have made it pos-sible for most banks to disseminate updates quickly andeasily via an Intranet site, a network version of themodel, or the less desirable methodology of physicallydistributing replacement diskettes. Citizens FinancialGroup concluded that, notwithstanding the loss of con-sistency and the need for lenders and approvers tounderstand the model, which is a good thing, a distrib-uted approach yields more preferable results.

How Big Should the Model Be? What CustomerFacilities Should It Include?

Any profitability model should be able to capture anumber of customer interactions, including deposits,loans, leases (if any), off-balance sheet facilities, suchas letters of credit, and fee-based services, such as cashmanagement and trust account relationships. However,the more complete the coverage, the bigger the modelsize becomes. Its size may limit the model’s ability tobe saved on a single diskette, and it may affect thespeed with which it runs on a PC. After reflection,Citizens Financial Group determined that the vastmajority of its accounts could be covered by a five-loanfacility data structure. Larger relationships are handledby combining smaller loans into a dummy facility (forexample, adding three $50,000 term loans with variousmaturities into a single $150,000 loan with an averagedmaturity).

Clearly, deposit balances are important. The biggestimpact of deposits comes from the lower, or zero, inter-est rate paid to the depositor. The model calculates theinterest expense incurred by the bank using the lender’sinput of the interest rate received by the borrower,thereby giving the model the flexibility to capture bothinterest-bearing and non-interest-bearing deposits. Afterthe appropriate reserve balance is withheld, the amountof funds purchased from treasury is adjusted so that thebalance sheet is in equilibrium. Instead of allocating thedeposit benefit to each facility, it is calculated only atthe relationship level. This calculation allows the lenderand management to view the incremental value of thedeposits with regard to the overall relationship prof-itability. With regard to servicing expenses, CitizensFinancial Group chose to apply average account main-tenance costs with an override. If the cost of maintain-ing the account exceeded the funds credit on balances,

the override provided that no detriment to overall prof-itability would occur. An account activity fee would beassessed and collected.

In the case of leases, the multiplicity of deprecia-tion, residual realization, and taxation issues ledCitizens Financial Group to decide that building thesecomputations into the profitability model would renderit far too complex. Others likely will reach the sameconclusion. Also, there are models in the market thatanalyze the profitability of leases far better thanCitizens Financial Group’s loan model. The bank solvedthe riddle by building an input screen that injects thenet tax-adjusted profitability from a stand-alone leasingmodel if related leasing facilities exist.

Loan History or Bond Market as an Indicator ofEDF?

Everyone in this industry has heard a cocky lendersay, “We’ve never had a loss on these deals and I can’timagine the circumstances under which we would.”Moreover, many have not captured historical data toprovide a reliable basis over multiple business cycles toestimate these items. Therefore, since most banks havelittle else to use, employing bond market default ratesprovides a consistent indicator of expected default fre-quency (EDF) to recognize both loan rating and tenor ifwe can establish two things:

1. That there is a strong correlation between the riskimplied in a bank’s ratings and the analogous riskin the bond ratings to which the loans are mapped.

2. That a bank’s portfolio generally performs as pub-licly rated debt when default occurs.

The former premise is common for larger banksthat carry wholesale loans on their books, but becomestenuous when applied to smaller institutions that areprimarily community lenders.

To some extent, any bank can validate both correla-tion and portfolio performance empirically. It does soby analyzing historical annual loan defaults by risk rat-ing and comparing the result with what was observed inthe bond universe during the same time period. Oncethis analysis has been done, it’s possible to stress-testthe portfolio by applying historical public bond ratingtransition matrices during times of high defaults to ana-lyze how closely they conform to the default rates andlosses observed during the years being tested.

49

I s s u e s i n L e n d i n g

The cumulative default rates for the 28-year historyending in 1997, as reported by Moody’s InvestorsService, are included in Figure 1. Some smoothing isgenerally desirable when using these data due to occa-sional inversions (as seen in the one-year Aa and Aaverage default rates). Also, there is a significant jumpin default rates when moving into non-investment gradelending.

Do Collateral and Tenor Matter?Any model must provide for the higher probability

of default over time and lower loss given default (LGD)when the bank obtains more valuable collateral for itsloans. While Citizens Financial Group has not figuredout how to empirically modify pricing for guarantees orother loss-mitigating structures, the bank again supportsthe use of bond data to estimate the incremental proba-bility of defaults in later years. With regard to collater-al, a bank can empirically analyze its workout history toensure that the appropriate LGD is assigned for variouscollateral types. For example, Citizens Financial Grouphas estimated a range from 5% for marketable securitiesto 70% for unsecured loans. (Note that these rates areaverages.) A question, however, that always remainswith regard to LGD is how much the current economicenvironment affects recoveries on defaulted loans. Mostresearch is inconclusive, however, and until enoughgood data can be analyzed, collateral LGD rates shouldbe viewed as directional, not as absolutes.

The Old Saw—Average Cost or Marginal Cost?No pricing model would be complete without offset-

ting some of the income from loans by the estimated origi-nation and servicing costs of the loans. But these issuesraise a plethora of knotty questions, such as:

• What is the true cost that should be allocated toeach loan and relationship?

• Should the bank average its total costs over the portfo-lio by loan (if the bank has the accounting and loanadministration data to support that) or should the bankpresume that the marginal cost is zero?

One senior manager suggested that one more loanwould not cost much to service because lenders’salaries would have to be paid anyway, thus making themarginal cost zero. This approach seems too aggressive,but Citizens Financial Group believes that average cost

overstates the proper cost allocation to a new loan orig-ination and that something less is an appropriate com-promise.

Any cost matrix would have to address the fact thatlarger loans are more expensive to originate and servicethan smaller loans, everything else being equal.Additionally, the matrix would have to address the factthat with everything else equal, more creditworthy bor-rowers will cost less to service. Finally, it also is neces-sary to differentiate the marginal servicing and originationcosts within a loan relationship. Because most of the timeand expense is incurred analyzing the borrower and thefirst facility, the cost of adding more facilities is signifi-cantly reduced. Although the accounting data to supportthese exact numbers may be difficult to obtain, one mustat least establish the correct directional relationships sothat there is not a bias introduced that inadvertentlyencourages lenders to behave in an unintended manner.

Cost of Funds—Another Old SawA perennial issue in these matters is the question of

whether average cost of funds over the bank portfolioor marginal cost of funds is appropriate to determinethe relative spread earned. Average cost would workfine if summed over all facilities in the bank. But it willenrich unfairly or penalize the next transaction (depend-ing on the yield curve and relative funding levels),which is what the whole model is designed to prevent.Therefore, the only logical choice is a marginal fundsrate for floating debt that approximates the alternativeinvestment cost the bank faces. Any lower cost depositaccounts that the relationship carries with it and theexplicit rate on the deposits should be included to deter-mine the weighted funding cost for the relationship.

The case for fixed-rate debt gets even tougherbecause the match-fund cost presumes no prepayment.Yet, because of competition, the bank frequently offersan embedded prepayment option, which results in thebank collecting less than a full-yield maintenancepenalty if the loan is prepaid. Some banks now explicit-ly calculate the value of a prepayment penalty and thencompare it with the value of the put option to the bor-rower. They include the difference in the profitabilitycalculation. Citizens Financial Group found it useful toinclude a yield-curve estimator. It calculates a weight-ed-average cost of funds by interpolating between bulletand fully amortizing rates for those loans that haveunequal amortization and term.



What Is an Adequate Return and How Should WeMeasure It?

Substantial discussions have occurred in this indus-try regarding whether return on assets (ROA) or returnon equity (ROE) is the proper way to value the margin-al relationship. No thunderbolt has come from the skyto settle the matter. The establishment of hurdlesrequires a bank to determine which primary approachwill be used by the institution and how facilities or rela-tionships that fail to meet these hurdles will be treated.With capital no longer constrained in this industry, theability to add assets is presumed. It is, therefore, moreimportant than ever for a bank to be able to weigh theexpected return of a loan against the risk it carries. Eachnew loan also must be viewed in light of the entire port-folio and how the risk/return trade-off of the loanaffects the remaining portfolio. Consequently, a loanwhose return on assets is sub-par may nonetheless be anacceptable part of the portfolio. For this to happen, thebank’s capitalization must provide an equity allocationthat is small enough for the bank to use financial lever-age to generate a satisfactory return on that allocatedequity.

Of course, the allocation of equity, itself, is anissue on which many bankers are divided. The Baselstandards require a minimum of 8% capital to risk-based assets, and the regulators have suggested that atleast 10% is desirable if a bank is to be considered wellcapitalized. However, we do not believe, nor do the reg-ulators, that these requirements mean that every loanasset requires 8% or 10% capital to be allocated againstit. In fact, if capital is viewed as an economic quantitythat provides a cushion for a creditor against possibleloss on assets, then the first step in calculating therequired amount of capital is to theorize the possibledefault distribution for a portfolio of similar risk assets.This amount is then modified by the loss anticipated inthe event of default, which should be a function of col-lateral type. The expected loss is then added to theunexpected loss, a quantity that reflects the variance oflosses over time, as observed historically and modifiedfor other information the bank possesses. Appropriatepricing will support the annual provision expense tomeet the expected loss on a facility and leave enoughleft over after origination, servicing, and taxes to pro-vide an acceptable return on equity. If there is notenough pricing spread, amortized fees or value provided

by balances and other non-fee support, we must short-change either the reserve provision or the return on cap-ital—neither of which are acceptable alternatives.

Because bankers recognize that different loss pro-files should require different equity allocations, they aredissatisfied with pure ROE. The dissatisfaction has ledto risk-adjusted return on capital (RAROC) analysis. InRAROC, the return on the facility is risk-adjusted bycharging a loss provision that reflects the normalizedlong-term loss level. The capital allocations are adjustedby observing the distribution of possible losses andapplying enough capital to cover some very high pro-portion of possible losses. While RAROC provides anelegant analysis, it should not be used alone. Instead, itshould be used as a modifier of ROE and ROA hurdles.RAROC also can be used in conjunction with a broadlevel management of the risk/return dynamics of theentire commercial loan portfolio.

Perhaps an example will help define these issues.Many lenders make loans secured by accounts held bythe borrowers at the bank—sometimes at spreads overthe deposit yields paid and sometimes at rates deter-mined by market rates. The former presumes that ifbanks do not make the loan, the deposit goes away,while the latter presumes the deposit is irrelevant. Ineither case, it is difficult to imagine a loss likelihood(absent fraud or malfeasance), though default mayoccur. The loss mitigation provided by the collateralshould reduce the capital required to support this loan,though it is clearly not zero.

What About All Those Assumptions?By design, the operation of a pricing model

assumes that certain attributes, such as loan rating, cur-rent pricing, and present collateral, will all remain overthe life of the facility. We know this is unreasonable,given the dynamics of risk-rating changes, the preva-lence of performance-based pricing grids, and thechanging relationship between a bank’s cost of fundsand market indicators. To the extent that ratings migra-tion is incorporated in the provision charge and eco-nomic equity allocation, at least the credit risk is cap-tured. Most banks that attempt to incorporate additionalrating migration dynamics and pricing changes willonly further complicate what is already a very complexprocedure.

Another related question is whether it is reasonableto prognosticate the renewal or extension of short-term

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facilities, such as demand loans or credit lines, to the finalmaturity of the longest-term loans the bank has on thebooks. It is inappropriate to build into the model anyassumptions that are not contractual. Citizens FinancialGroup has dealt with this issue by making the model flex-ible enough so that a lender can quickly quantify theimpact of a facility’s term. For example, one can view theprofitability of a relationship that includes a one-year lineof credit that is analyzed as a one-year line and analyzedfrom an ex-post perspective where the line may be contin-ually renewed for as long as the relationship exists. Thisanalysis gives the lender the flexibility to view “what-if”scenarios based on the lender’s best judgment.

Output ExampleAfter considering all of the above, one may wonder

how all of the information is synthesized and ultimatelypresented. Obviously, Citizens Financial Group cannotshare the details of how the model calculates, but thebank can provide what the output looks like. This out-put is provided in Figure 2 for a simple two-loan rela-tionship, with the expectation of additional balances andcash management revenue after the second facility clos-es.

Are We Done Yet?There is no perfect pricing model available (if it

were, Citizens Financial Group and your bank wouldhave bought it from some rich vendor by now), nor isthere likely to be one in the near future. Each institutionmust use a model that is flexible with the types of loansit typically pursues. Also, it should be updated regularlyto include the most recent default, loss, and cost data.Citizens Financial Group is working on the fourth revi-sion of its model in a year and it is not perfect yet. Theinvolvement of lenders and administrators to test andpush the envelope on applying any model are a keydeterminant of its continuing value to the institution.Finally, it should be clear that with so many assump-tions, the results of the analysis are relative (rather thanabsolute) measures of the contribution of the relation-ship to the bank’s bottom line. p

Fadil can be contacted by e-mail [email protected] . Hershoff can be reachedat [email protected].



------------------------------------------ Issues in Lending ----------------------------------------------

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There is a window of opportunity for banks to lay the groundwork for more effective cross-selling and retention by emphasizing investment of capital and human resources at the beginning of a customer relationship rather than primarily on the mature customer base or eleventh-hour retention efforts. At best-practice banks, a significant portion of retention and cross-selling efforts is focused on the onset of new customer relationships based on simple products that fit customer needs and on a disciplined alignment of staff incentives and training with sales and retention goals.

This research brief grows out of The Quest for Deposits, a research project directed by BAI with participation from eight of the Top 20 U.S. banks and corporate sponsorship support from Xerox Global Services. The project derives its explanatory power from:

• A management practices report based on 150 interviews with executives at 50 large U.S. banks,

• Deposit performance metrics provided by the sponsoring banks, and

• A segmentation model based on a national survey of 4,200 consumers of financial products and services.

Summary

Across the nation, banks seeking to create deeper relationships with their customers are focused on the mature account base rather than on their newest customers. According to key benchmarking and best practices profiles generated through BAI’s Quest for Deposits project, refocusing resources toward cementing bonds with the newest customers is a more reliable path to the durable, profitable relationships that banks seek. The research reveals that a significant portion of bank investments in CRM, lead management, cross-selling and retention aimed at the mature customer base might be misdirected. Why? One of the most striking findings in the performance metrics is that most cross-selling opportunities occur during the first few months of a customer relationship. And in a refrain heard repeatedly through dozens of executive interviews, senior bankers at many financial services companies said that customer attrition rates are significantly higher at the beginning of a relationship than when a relationship is six months old or older—sometimes as much as 100% higher.

The study argues that in addition to focusing cross-sell and retention efforts on mature customer relationships, banks need to refocus

The Ninety-Day Window of Opportunity

Research Brief


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energies on the beginning of customer relationships and may need to reconfigure product packaging, sales efforts, lead management, service quality and incentive programs to do so.

The research data show that banks that touch their customers early and often in the relationship boast improved cross-selling results and lower attrition rates. In fact, the bank that displayed the best practices in developing a comprehensive new customer orientation program reported a product cross-sell ratio among new checking households that was 8% higher than the benchmark norm and 15% higher than the lowest performing bank in the study. While this may seem like a relatively modest level of differentiation between the top-tier, the average and the lowest performing banks, this is actually a very substantial performance differential when one considers that most large banks open hundreds of thousands of new checking account relationships per year. But in addition to cross-selling, the performance improvements that new customer orientation programs can generate in customer retention are staggering. This same top-performing bank reported that its checking customer attrition rate decreased by 50% as a result of its new customer orientation program.

Successful new customer orientation programs are built around a series of opportunities to touch the customer during the first 90 days of the relationship and are founded on simple products with transparent features and fees.

The research also revealed that the generation of breakthrough results through a new customer orientation program will

only be achieved if the program is integrated with a handful of basic premises:

• Keep products—including rates and fees—simple so bank staff can explain them and customers can understand them.

• Sell customers products that fit their financial needs.

• Don’t underestimate how much realignment of corporate culture, incentives and training may be needed to reach retention and sales goals.

The Quest for Deposits

The deposit business is still one of the most profitable for banks, and the checking account is where retail relationships often begin. The crusade for new retail deposit relationships has heated up in recent years and is white hot in the most competitive markets in the nation. Witness the investments behind more than a thousand de novo branches slated to open during the next two to five years and the adoption of free checking by all but a handful of banks. The result of these initiatives is often higher customer acquisition costs and longer payback periods on the marketing and sales investments.

A key concern is that banks need customers who are profitable, and profitability depends on the bank’s ability to hang on to customers and cross-sell them into new products. The success of those efforts usually is determined within the first three to six months of the relationship. That’s when most of the cross-selling opportunities arise and when customers are establishing account-usage patterns and forming opinions about their new banking partner.

Multi-product relationships are critical to retaining customers, as they represent greater involvement with the bank.


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Customer data provided by the eight large banks that participated in BAI’s Quest for Deposits project revealed that nearly three-quarters of cross-sales from a retail checking account relationship occur within 90 days of account opening (Figure 1).

Unfortunately, bank investments in cross-selling and retention have traditionally focused on the established customer base. The research suggested that redirecting a portion of those efforts to the first 60–90 days of a customer relationship will yield better results, but respondents also cautioned that no bank should underestimate the complexity of the task. Doing it right involves aligning incentives to encourage needs-based selling complete with carefully crafted profiling conversations at the point of sale. It also includes tangibly encouraging staff to identify the right products for a customer, to carry out an effective new customer orientation process that may extend three to six months, and to ensure high-quality fulfillment. In short, the task may amount to a significant change

in corporate culture, with all that such an effort implies.

The data analyzed by BAI and MarkeTech Systems International also showed that attrition rates during the first three months of an account’s life span can be up to two times higher than attrition from accounts half a year old or older. Bankers reported that the leading cause of attrition is selling customers the wrong products. That can result from failure or lack of a needs-based sales process at account opening to uncover customer requirements. It can be caused by products that are too complex for the staff to explain fully or for customers to understand while they’re at the platform. It also can result from management’s failure to align staff sales incentives effectively with the bank’s desire to match customers and products.

The second leading cause of customer disaffection during the initial phase of a new depository relationship is a failure to execute on fulfillment, especially on items such as check orders, ATM and debit cards,

0 10 20 30 40 50 60

1 month

Length of relationship Percentage of total cross-sales

2–3

4–6

7–12

>12

60%

13

8

10

9

Multi-product relationships are critical in customer retention, and most cross-sell opportunities come in the first few months after checking accounts are opened.

FIGURE 1: Time is of the essence*

* Source: 2003 benchmarking study of eight large U.S. banks by BAI Research and MarkeTech Systems International


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PINs, online banking and bill payment. Fulfillment problems can arise from poor quality control or training on the front end at account opening or on the back end in a fulfillment process. A customer’s dissatisfaction may be related to the problem itself or, separately, to the bank’s inability to solve it quickly and fairly from the customer’s viewpoint.

The third major controllable cause of dissatisfied customers is after-purchase surprises about product functionality or features, especially prices. The surprises generally grow out of relationship-origination processes that fail to inform customers adequately about features, especially fees.

Some banks reported that they had implemented new customer orientation measures to address such issues, while others reported that they recognized the need but had not begun to respond systematically. The research data suggest that an effective bank response to the challenge of enhancing retention and capturing cross-sell opportunities during the onset of new customer relationships should be multi-dimensional and involve a process that aligns:

• Product packaging,

• Needs-based sales efforts,

• Post-sales follow-up,

• Front-line sales incentives.

A key element in getting the mix right is product management.

Product Management

Customer-driven product management creates an environment in which cross-selling and retention can flourish. The first role of product management is ensuring that customers fully understand the products they are considering. That effort begins with simplifying products. Many of the banks

that participated in the research admitted that their products were too complex and contained more features than the average customer can comprehend or ever use. In response, these banks have sought to dramatically simplify their product offerings. The retail staff at one responding bank cut the number of product features they addressed in depth from 17 to three or four.

In addition, many banks are examining fees in the context of their potential effect on profitable customer behavior. The strategy is to increase account balances and extend relationships by reducing nuisance and transaction fees. Several banks in the study reported that they had simplified fee structures and surrendered millions of dollars of customer-unfriendly fees, but more than offset the fee shortfall with higher balances and improved retention. The simplification effort often has the added benefit of making pricing transparent to customers and—almost as important—to staff who have to explain it. Long-term, the sales process is a success only if product packages engage prospective customers and are free of unpleasant future surprises.

The second product management role is focusing on product packaging that encourages multi-product ownership and account usage in the first place—resulting in a sticky relationship. To this end, the research uncovered a significant trend of banks’ creating product packages that are targeted to particular customer segments, life events or financial needs. Some of these packages offer interest rate, fee and minimum balance structures that are based on the total assets and liabilities that a customer brings to the relationship—thus, rewarding the overall value of the relationship. Wells Fargo’s Homeowners Option Checking is one of the most visible examples to date as it is aimed at young families and includes mortgage, checking,


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money market and credit card accounts. Other banks have designed packaged accounts that are targeted to certain financial needs, such as establishing a credit history, saving for children’s education, saving for retirement or maintaining one’s standard of living after retirement.

Orientation Programs That Work

Product fit, quality and communication emerge from the research as the three main pillars of successful customer relationships.

• Product fit starts with customer-centric design of products and packaging and includes careful needs-based selling and customer rewards based on the total value of the relationship.

• Quality means fast, effective problem resolution.

• Communication involves simplicity of products and transparency of fees but also includes high-touch follow-up. The most successful programs employ predictive modeling that enables bank staff to make just the right approach to the customer at just the right time.

While some banks reported informal approaches to new customer orientation, the banks that delivered best on cross-selling and retention had clearly defined and systematic approaches to new-customer account management that became part of corporate culture. Whatever the tangible form of such programs, they institutionalize four essential steps (Figure 2, next page):

• Setting expectations,

• Opening the account,

• Orienting the customer and following up,

• Ensuring a high-quality customer experience.

This integrated, four-step process is designed to reduce attrition, stimulate account usage, cross-sell appropriate products and make the customer feel valued. The banks that faithfully applied this four-step process achieved performance metrics that were consistently higher than the benchmark norm. A sampling of the performance metrics from these best practice banks reveals that a coordinated new customer orientation program has the potential to generate substantial competitive advantage (Table 1, next page).

Step 1: Setting expectations

Almost a pre-step, product management plays at least two vital roles in setting expectations and enrolling satisfied customers. The first role is in simplifying products so staff can explain them and customers can understand them. A second role is creating packages that are closely aligned with specific customer segments or financial needs. The point is to grow a single point of entry, such as the opening of a checking account, into a profitable, multi-faceted relationship. The research reveals that selling such packages at account opening not only enhances retention, but has a much greater financial payback than trying to cross-sell those individual products a year or two later.

Step 2: Opening the account

Nothing is more likely to lead to new-account attrition than selling a customer the wrong product. The sales process is more likely to lead to long-term satisfaction if the product is simple and the pricing transparent. But the best way banks have discovered to ensure that any individual customer gets the right product is through needs-based selling. Needs-based selling is the foundation on which good customer relationships are created because engaging


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customers in a dialogue that clarifies the bank’s and the customer’s expectations and needs lays the groundwork for a relationship that is based on trust.

The process begins with conversations at the platform or elsewhere designed to uncover customer needs by probing for behavioral, demographic and attitudinal information. The profiling conversation is also the bank’s best opportunity to explain a product so thoroughly that the customer is spared any unpleasant surprises about price or other features later in the relationship. But profiling data also may be used on the

spot to try to cross-sell the customer into a second or third appropriate product, or it may be entered into a lead-management system that enables branch or call-center staff to engage the customer in a mutually helpful cross-selling dialogue later in the account onset period. At its most effective, profiling and needs-based selling may be linked to product packages that are specifically designed for distinct customer segments or financial needs.

While banks need to focus on the first 90 days after account activation, best-practice banks understand that the needs-based

Ena

ble

rsC

ham

pio

n

People—organizational alignment with retention /cross-sell goals and incentives

Pro

cess Open account Orient/follow up Assure qualitySet

expectations Follow-up timeline 1st week 2nd week/month

Process—structured new-customer orientation program

Technology—customer contact management

Technology—predictive modeling

Branch• Needs-based sales/profiling• Right products for customers• Purchase receipts• Welcome gifts

Product management • Simplify products• Clarify pricing• Train sales/ platform reps• Develop customer- focused products

Branch/call center• Thank-you letter• Follow-up calls• Additional needs analysis

Branch/call-center• Quality check-up (checks, ATM card)• Problem resolution• Evaluate account activity• Additional needs fulfillment

FIGURE 2: New customer orientation process*

TABLE 1: Benchmark results**

Performance metric Benchmark norm Results at the top–tier performers

Single service checking account households as a percent of total deposit households

27% Results that were 34% better than the benchmark norm

Average amount of time to cross–sell the next product after the opening of a new checking account relationship

2.9 months Results that were 57% better than the benchmark norm

Percent of checking households opening a new account within 30 days of a newchecking account relationship

27% Results that were 86% better than the benchmark norm

* Source: BAI Research

** Source: BAI Research and MarkeTech Systems International


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approach should extend across the entire customer-account life cycle, with the broad objectives of:

• Placing customers in products that best fit their needs,

• Establishing the foundation for managing the relationship going forward,

• Developing a migration path for the relationship across life events,

• Winning as large a share of the customer’s wallet as possible.

Banks that participated in the research reported additional techniques that they use with needs-based selling to enhance cross-selling and retention during the onset period.

• Concluding the account opening session by engaging customers in a detailed conversation that reviews the features, functionality and fee structures of the products that have been purchased. This conversation can help to reinforce customer expectations and eliminate unpleasant surprises that may arise when customers receive their first statement.

• Providing new customers a welcome kit containing tips, navigation tools, and access to or knowledge about products or services acquired. Today, technology enables a bank to print each individual customer a welcome kit that contains descriptions and details about only those products that a customer has purchased or indicated an interest in. The kits also encourage activation of sticky features, such as direct deposit and online banking.

• Providing switching kits to ease the transition from other providers. A major reason consumers are reluctant to switch banks is the inconvenience of notifying companies that automatically debit or credit their accounts each month. In response, many banks provide online

forms to help switch automatic credits such as payroll direct deposit or Social Security and automatic debits such as utility payments to the new destination account. Once a new-customer profile and contact list exists in the database, a bank can produce a customized switching kit that includes detailed letters of instruction to all banks, agencies, utilities and others that may be involved; a close-out letter to the old bank; and a detailed summary that includes estimated switch dates. A third-party communications provider can enable a bank to notify a new customer by mobile phone, home phone, PDA, pager, e-mail, fax or postal mail as each automatic transaction is switched to the new account.

• Providing welcome gifts to thank customers for their business.

Step 3: Orienting and following up

Follow-up is an important element in improving prospects for cross-selling and retention after the initial sale. Several major U.S. financial institutions have established relationship orientation programs that begin with calls to new customers three times within the first two or three months of the relationship. The first call occurs a few days after account opening, when bank representatives thank new customers for their business and make sure that they are satisfied with arrangements.

After a couple of weeks, the bank calls to verify the receipt and accuracy of checks, debit or ATM cards, personal identification numbers, etc., a critical activity since errors are a major cause of attrition. The two-week follow-up also provides an opportunity to inquire whether the new customer has additional financial services needs and to gather any information missing from the customer profiling session at account opening.


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Finally, two or three months after account opening, the bank calls customers again to ensure that they are satisfied with their products and services. With the relationship more firmly anchored at this point, bank representatives have the opportunity to fine tune the package of products and services being used by the customer and also to identify and meet additional needs.

At the most successful banks, branch staff members make the first follow-up contacts. At others, follow-up is the responsibility of the call center, which can ensure consistency and provide monitoring. At still others, follow-up is handled through the mail. The choice of channel is often based on the bank’s perception of the customer’s value, but other considerations apply.

“Our bank has a system where the bank sets up orientation calls automatically with the branch representative who opened the account. If the branch rep does not make the call within a week, it automatically gets sent to a retention unit in the call center.”—Senior Retail Executive, Large Bank

“Our bank thought an orientation program should be high-touch and branch-based, but how the contact is really executed and the quality of it is difficult to track with a branch-based program. So what we’ve incorporated is a call center-centric program where the branches know what is happening, but the calls are actually generated out of the call center.”—Senior Retail Executive, Large Bank

At top-performing banks, high-touch calling efforts may be supported by integrated marketing. Such marketing may cross channels and extend throughout the whole first year of a new customer account. Orientation, servicing and appreciation,

education and needs-based selling may proceed along parallel lines. In the same week as account opening, the customer might receive a welcome kit and thank-you letter. The second week could bring check book and ATM/debit card fulfillment. During the third week, a customer might receive a follow-up call from the branch or call center to ensure the accuracy of materials received. At the end of the month, depending on the customer’s responses to profile questions at account opening, an IRA rollover reminder might be inserted with a statement, or a retirement or education brochure sent via direct mail. Three or four months or further out, a customer might receive a communication about credit or investments or invitations to a seminar. Each contact is carefully spaced throughout the period to maintain contact without overwhelming the customer.

“We were able to reduce our attrition rate last year by reaching out to new customers by mail. Our orientation program makes sure of two things: 1) if we continue to communicate with them in that three–, six–, or 12–month time frame, our customers will feel closer to the bank and won’t want to leave us, and 2) we must communicate our product benefits and try to get customers to upgrade or expand the relationship.”—Retail Executive, Large Bank

Other banks, however, limit their orientation programs to select customer segments, with the objective of maximizing ROI. Some banks have demonstrated success in supplementing follow-up calls to customers during the orientation period with purchase-propensity modeling. In interviews, bankers revealed no consensus about how often it was appropriate to contact customers for marketing purposes.


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They said that general leads on household contacts were supplied to branches or call centers only about every six to eight weeks, whether limited out of concern for the customer or staffing realities.

Step 4: Ensuring a high-quality customer experience

Inevitably, problems occur. Late check orders, missing ATM or debit cards or some other difficulty with a small percentage of new accounts will arise during the first 90 days. Some problems may stem from changed customer needs and not be the fault of the bank.

Banks that recognize the problem and respond effectively can turn a problem into a customer-service success, creating more trust and opportunities for cross-selling in the future. On the other hand, the inability to solve a problem quickly and fairly (from the customer’s viewpoint) is a leading cause of attrition and can cost a bank an account as surely as the original problem. To reduce the likelihood of this kind of customer loss, some banks give branch staff different levels of authority to solve certain problems on the spot. That authority, if properly tracked and managed, leads to higher levels of customer satisfaction and employee commitment, both cornerstones of customer retention and profitability.

Aligning Incentives With Bank Goals

No bank is going to reach its potential in cross-selling and retention unless incentives give front-line staff tangible reasons to actively and consistently support the bank’s goals. Most bankers in the study reported they were not satisfied with their banks’ alignment of incentives with needs-based selling activities.

As three-quarters of cross-selling opportunities occur during the first 90 days of an account relationship, the data suggest that a significant portion of incentives should direct staff attention to relationship-orientation activities. Incentives should encourage placing customers in the right products at account opening and during cross-selling, completing critical steps in account origination—especially profiling, aiming for zero defects in product fulfillment and solving customer problems quickly and fairly.

The most common tactic to encourage front-line staff to be thorough at account opening and responsive to service requests afterward is to lag a portion of the incentive payment. For example, 50% of the incentive could be paid after 60–90 days based on account balance and retention. Another tactic is to provide an additional incentive for cross-sales at account opening or during the first 90 days.

Top-performing banks are migrating to a book of business approach, where a certain portion of a branch’s customer base (usually the top 10% to 15%) is monitored by a dedicated relationship manager. The book of business approach is often implemented in connection with extra efforts to retain and expand customer relationships and pays up to 50% of incentives based on total balance or growth in total value of customer accounts in the book.

“Our retention rate for new customers is only 73%. If customers can be retained for the first 60 days, then retention rates jump significantly. Therefore, branch staff are incented half upon opening an account and half 60 days out for retaining the account.”—Senior Retail Executive, Large Bank


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“Our bank has a two-part incentive compensation program. The first partis at account opening and the second part is at 90 days, when balance growth is checked.”—Head of Sales, Large Bank

Conclusion

The battle to obtain new retail deposit relationships has intensified significantly over the past several years. Aggressive marketing and price competition are prevalent in many markets. Industry consolidation and increasing competition from non-traditional entrants will be constants. All of this points to steadily increasing acquisition costs to obtain a new deposit relationship and longer payback periods to obtain positive returns on the initial marketing and sales investments.

While the ability to acquire new customers will be a core competency that will separate the winners from the losers in the quest for deposits, the research suggests that high-performing banks will be those that also become skilled at managing and growing customer relationships through the first 90 days after account opening.

Research Methodology

This research brief was written by Paul McAdam and Ajay Nagarkatte of BAI, based on:

• In-depth performance benchmarking of customer data from the eight Quest for Deposits sponsor banks by BAI and MarkeTech Systems International.

• Findings of in-person and telephone interviews held in the second and third quarters of 2003 with nearly 150 retail banking executives from 50 large U.S. banking institutions. The interviews were conducted by senior researchers from BAI.

This focus on new customer orientation is one aspect of BAI’s Quest for Deposits series—an ongoing research program focused on benchmarking, best practices examination and consumer research in the core retail deposit franchise. Please contact us to learn more about this series.

About BAI

Bank Administration Institute (BAI)One North Franklin, Suite 1000Chicago, IL 60606Ph: (312) 553-4600Fax: (312) 683-2426www.bai.org

BAI is the financial services industry’s leading professional organization that delivers information and education to enhance the organizational performance of financial services companies and the individual performance of their employees. BAI offers conferences, seminars and graduate schools, as well as a full range of employee development tools including assessments, e-learning, in-house and text-book training. BAI also provides valuable insights on complex strategic issues through BAI KnowledgeBank, BAI Research and Banking Strategies magazine.

Contact:

Paul McAdam Managing Director, Research (312) 683-2403 [email protected]

Ajay Nagarkatte Director, Research (312) 683-2486 [email protected]

© 2003, Bank Administration InstituteChicago, IllinoisUSA

The RMA Journal February 200680

© 2006 by RMA. Robert Phillips, Ph.D., is co-founder of Nomis Solutions, a company specializing in price optimimization solutions for the financial services industry. Dr.Phillips is a lecturer at Stanford University and has previously served as CTO of Manugistics and founder and CEO of Talus Solutions. Frank Rohde is vice president of sales andmarketing at Nomis Solutions.

Loan Pricing

By Robert Phillips and Frank Rohde

Many lenders consider risk-based pricing to

be the ultimate in pricing sophistication. Thereis no question that identifying higher-risk cus-tomers and charging them higher rates to com-pensate for higher losses is a sensible (and prof-itable) idea. However, risk-based pricing doesnot incorporate one of the key elementsrequired to maximize financial return—cus-tomer price sensitivity.

Understanding and using customer pricesensitivity in setting prices is a highly devel-oped science in many industries. The key tomaximizing profitability through pricing in allindustries is to trade off the increased profit pertransaction at higher prices with the reduced

penetration at the higher prices. This trade-offneeds to be made for each combination of cus-tomer segment, product, and channel andupdated continually as market conditions andcost-of-funds change. This is the discipline ofprofit-based pricing.

Analytical approaches—for estimating cus-tomer price response for different products bydifferent micro-market segments and for usingthis information to optimize prices— have beenused successfully in such industries as retail,hotels, and telecommunications for many years.Hotels understand that late-booking cus-tomers who want to book a room only forTuesday night are likely to be business travel-

This article is based on a chapter of the book Pricing and

Revenue Optimization by Robert Phillips, who contends

that profit-based pricing is relatively new to the

financial services industry; after explaining its success in

other industries, he provides 10 key elements of a

successful profit-based loan-pricing model.

Pricing and Revenue Optimization

ers who are relatively price insen-sitive, while early-booking cus-tomers for weekend nights aremore likely to be leisure travelerswho are more price sensitive. Bysetting and adjusting rates usingthese insights, sophisticated hote-liers are able to extract significant-ly greater profit from the samefixed stock of rooms.Sophisticated retailers track cus-tomer demand and price-sensitivi-ty across their stores, adjustingdiscounts and promotions to targetmore price-sensitive groups ofcustomers only as needed to movemerchandise. Deep discounts arenot wasted on customers who aremore than willing to buy at higherprices but are targeted specificallyto the most price-sensitive buyersin the market.

Application to Financial Services

While profit-based pricinghas been immensely successfulacross many industries, lendersare only now starting to use profit-based pricing to set andupdate APRs offered to variouscustomers for different products.Successful lenders have recog-nized that there are many charac-teristics of consumer lending thatrequire specialized approachesand algorithms. Simply put, pric-ing consumer loans is not thesame as pricing capri pants, groceries, or hotel rooms. • The profitability of a con-

sumer loan is a complex func-tion of the term of loan, theAPR, the amount borrowed,and the propensity of a par-ticular customer to repayearly or to default.

• Adverse selection means thatincreasing the APR for a par-ticular credit offering will tendto reduce the average quality

of applicantsfor thatproduct.Adverseselection hasno analog inother industries, and ignoringadverse selection was a short-coming of some initialattempts to apply retail-basedpricing optimization approach-es to financial services.

• Banks are subject to both vol-untary and regulatory con-straints on rate levels, includ-ing fair lending laws, whichneed to be taken into account. Nonlinear profitability func-

tions, complex customer behavior,adverse selection, and regulatoryconstraints work together to makeoptimal consumer credit pricingmore complex than retail or air-line pricing.

However, banks have at leastone advantage over retailers whenit comes to pricing. Lenders typi-cally have extensive informationon failed sales—customers whowere approved for a credit productbut decided not to take it.Retailers would kill for informationabout the number and identity ofpotential customers who wereinterested enough in their productto go through the effort of fillingout an application but decidedeither not to purchase or went else-where. Incredibly, most banks aredoing little or nothing with thislost-customer information.

Getting There

Profit-based pricing starts byapplying statistical analysis to his-torical won/lost information toquantify which products are valuedby which customers and by howmuch relative to the competition.This explicit quantitative under-

standing of customer price-response is not only a critical inputto profitable pricing, it is a sourceof tremendous market insight.

One bank that has successfullyapplied pricing and revenue opti-mization in consumer credit is theHalifax Bank of Scotland (HBOS).HBOS is the largest mortgage andsavings provider in the U.K. as wellas a major player in the provisionof credit cards and consumer loans.It also is one of the world’s 20largest banks with over 22 millioncustomers and assets exceeding£440 billion (US $800 billion).HBOS faced a particularly chal-lenging pricing problem in theunsecured consumer lending mar-ket—over a two-year span, averagemarket APRs had dropped from11.2% to 8.1% while the averagecost of funds rose from 4.6% to5.1%. A price optimization programwas initiated to improve the prof-itability of this increasingly com-petitive business.

The first step in the programwas to adapt HBOS’s existingcredit risk and loan profit modelsto account for adverse selection. Ahistorical database of loan applica-tions and conversions was ana-lyzed to determine the price andnon-price drivers of demand foreach combination of product,brand, channel, and market seg-ment. Once this was complete,the incremental loan profitabilitywas balanced with price sensitivi-ty for each segment to determinethe prices that maximized expect-ed profitability, subject to all U.K.pricing regulations. Potential ben-efits of 34 basis points from better

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P r i c i n g a n d R e v e n u e O p t i m i z a t i o n

The key to maximizing profitability through

pricing in all industries is to trade off the increased

profit per transaction at higher prices with the reduced

penetration at the higher prices.

pricing were identified and imme-diate benefits of £7 million (US$13 million) per year are alreadybeing realized.

The concept of profit-basedpricing is applicable not only tocredit markets but to any line ofbusiness (such as treasurydeposits) that involves somedegree of personalized pricing. Inthese lines of business, the con-cept of understanding the pricesensitivity and profitability of dif-ferent customer/product/channelcombinations and calculating theprices that maximize expectedprofitability has proven to beextremely effective in increasingoverall profitability.

In short, it is time for banks topay some serious attention to pric-ing. Most banks and financial insti-tutions are missing importantopportunities to increase profitabil-ity, build business, and increasecustomer loyalty. Risk-based pric-ing is an important first step, but itstill falls short of corporate bestpractices in pricing. Forward-thinking banks are using statisticalanalysis to mine their data to betterunderstand customer behavior andprice sensitivity. By incorporatingthis understanding into pricing,banks and other lenders canincrease profitability, drive addi-tional business, and provide betterservice to their customers.

10 Key Points

Here are 10 important pointsto consider in developing andworking with pricing models.

#1: Adverse selection is critical. Contrary to traditionalprice optimization solutions devel-oped for airlines, hospitality, manu-facturers, or retailers, softwaredeployed in the lending world

needs to be able to take intoaccount adverse selection. Adverseselection occurs when a bankincreases its loan rates—the cus-tomers likely to accept loans athigher rates tend to have lowercredit quality. An increase of 0.25%in the interest rate of a home equi-ty loan therefore not only decreasesthe number of customers willing toaccept the loan, but it also resultsin a slight deterioration of the cred-it quality of the customers that doaccept the loan. Price optimizationsoftware deployed in bankingneeds to be able to explicitly meas-ure, manage, and limit adverseselection effects in setting prices.

#2: Lost quote data is valu-able! Banks and insurance compa-nies have large amounts of dataand information on those prospectswho didn’t accept a particular price.Contrary to other industries, themajority of financial services prod-ucts require an application andcredit check, which results in readi-ly accessible data on those peoplewho’ve applied and then decidednot to accept a certain product.Sophisticated statistical models cantake that “lost quote” data intoaccount when predicting an indi-vidual’s propensity to respond oraccept a certain price point.

#3: Regulatory oversightrequires consistency, constraints,transparency, and defensibility.More than almost any other indus-try, the financial services industry issubject to regulation that governshow prices can be set. Thisrequires that price optimizationsolutions be able to take intoaccount constraints on minimumand maximum prices, minimumand maximum volumes of productssold to different demographic seg-ments or in different regions, etc. It

also means that users need to beable to incorporate fair lendingpractices and guidelines, Basel IIcapital requirements, and DOI-mandated rate constraints into thedevelopment and optimization ofprice matrices. Last, any pricingstrategy needs to be defensible,which means that 1) users need theability to generate reason codes forspecific price actions, and 2) anyoptimization software cannot be ablack box.

#4: Market changes need tobe incorporated rapidly.Mortgage and home equity rateschange daily, and underlying refer-ence rates might change even moreoften. To accurately determineprofit-optimal lending rates for dif-ferent market segments, price opti-mization software needs to be ableto recalibrate itself frequently(daily or weekly) and take intoaccount changes in consumerbehavior, competitive actions, andeconomic conditions. For example,when your biggest competitorlaunches a prime-for-life balancetransfer offer on a credit card, yourcustomers’ propensity to accept a6.25% home equity line of creditwill drop.

#5: Utilization is important. Agrowing proportion of the con-sumer and small business creditvolume in North America isextended to customers in the formof revolving credit (lines or cards).In order to optimize rates for creditlines, it is critical that price opti-mization solutions take intoaccount not just the initial proba-bility of acceptance but also theongoing utilization of credit bythose customers. While a specificprice point might be the optimalprice to sign up a new customer fora credit line, that same price point

The RMA Journal February 200682

may not be the optimal price pointto entice longer-term utilization ofthe credit line. Price optimizationsolutions need to be able to opti-mize prices for both the short-termand long-term value of the cus-tomer relationship.

#6: Prepayment and refi-nance need to be explicitlyaddressed. Existing price opti-mization approaches tend to focuson single point-in-time price set-ting rather than a customer lifecy-cle view. For lending products inparticular, a consumer’s ability torefinance a mortgage or loan with alower-rate alternative needs to betaken into account when optimiz-ing prices at origination. This maymean offering a lower initial rate toreduce the probability of prepay-ment later on.

#7: Prices are negotiable. Intraditional price optimizationdeployments in retail or travelindustry settings, customers areoffered a fixed price and make atake-it-or-leave-it decision. Infinancial services, especially busi-ness lending but also consumerbanking, customers and bankemployees often negotiate particu-lar loan rates as part of a broaderdeal or relationship. In these cases,optimized price lists need to haveflexibility built into individualprice recommendations. For exam-ple, the optimal indicated rate fora home equity loan to an existingchecking account customer maybe 6.60%, but the branch banker,in the interest of maintaining andextending the banking relation-ship, may offer the customer a rateof 6.50% if she also agrees to opena credit card account. Price opti-mization solutions need to be ableto take into account the differ-ences between indicated optimalrates and negotiated rates in those

environments where customer-facing employees have authority tochange list rates.

#8: Understand global vs.local dynamics. As an increasingnumber of transactions and rela-tionships are managed online,competition for individual cus-tomer relationships takes place ona national and even internationalplaying field. While a local bankmay have slight advantages interms of perceived or actual serv-ice quality or brand reputation, amortgage offer from a bank acrossthe country can be just as competi-tive as one from the local bank.Price optimization solutions needto be able to balance minute dif-ferences in regional consumerdemand and risk characteristicswith the fact that loan productscan be “shipped” virtually every-where in a matter of seconds.

#9: Understand when to offerwhat price. The loan originationprocess for mortgages and otherconsumer loans can be drawn-outand complicated. In optimizingrates for lending products, it is crit-ical to understand when a firmprice offer is made during the cus-tomer acquisition process, whenthe customer decides to accept orreject an offer, and if and howquoted prices can be changed. Forexample, a bank may advertise ahome equity rate “as low as6.30%” on its Web site or throughprint advertising. Once a customercomes into a branch, she may learnthat her loan-to-value ratio wouldput her into a pricing cell with arate of 6.50%. If she then decidesto fill out an application, she mayfurther be qualified into a 6.60%rate cell based on her risk charac-teristics. The difference betweenthe headline rate of 6.30% and thefirm offer of 6.60% is significant.

The rate at which the customercommitted to accepting the offerwas probably 6.50%. Price opti-mization solutions need to be ableto take into account differentacquisition processes with differ-ent rate quotation mechanisms.Furthermore, a price optimizationsolution should be able to opti-mize all rate quotations, not justthe final rate.

#10: Take a relationship view.Banks and lending institutions willbe most successful when they canleverage individual transactionsinto long-lasting customer relation-ships across multiple product hold-ings. What this means for priceoptimization is that software solu-tions need to be able to take intoaccount not only single productprofitability but also cross-productand longer-term relationship prof-itability. For example, when deter-mining the profit-optimal homeequity line of credit rate, a priceoptimization solution needs totake into account the customer’spropensity to apply for a creditcard in addition to the HELOCand price the HELOC appropri-ately. Put another way, maximizingprofitability of each product trans-action may not be the profit-optimal strategy for the bank over-all. Price optimization solutionsneed to be able to accommodatethese cross-product constraints andgoals to fully enable dynamic rela-tionship pricing. ❐

Contact Robert Phillips by e-mail [email protected] Frank Rohde by e-mail [email protected] and Revenue Optimizationis published by Stanford BusinessPress, 2005.

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25

Powerful pricing processes: Howbanks can escape the profit crisisGeorg WuebkerPartner, Financial Services, Simon-Kucher & Partners

Many banks are in the midst of a profit crisis, brought about to

a large extent through lack of pricing strategies and poor judg-

ment about the reactions of competitors and customers. Even

those who fare quite well could do much better. The following

article reveals that price is the primary profit driver. Top man-

agers and decision makers must focus more on the profit

potential hidden on the price side. This does not mean simply

increasing prices. Rather, success depends on two factors,

innovative pricing strategies orientated towards the cus-

tomers’ needs and the subsequent complete reorganization of

pricing processes.

Price is the primary profit driverMany banks are suffering from a crisis into which they have

put themselves. A common solution is to cut costs drastical-

ly. Personnel cutbacks are almost daily occurrences.

American banks, for example, cut more than 100,000 jobs

between 2000 and 2004. These measures to reduce costs

are inevitable. However, after heavy cost cutting in the recent

years, companies have nearly exhausted the potential to

reduce costs any further. Is there a way to escape the crisis?

What else can be done to increase profits? Management must

concentrate more on revenue and price. In these two areas,

the potential to increase profits today are significantly high-

er than through cutting costs. Furthermore, many price

measures immediately transform into a profit increase, the

so-called quick wins. Our experience shows that for many

banks these quick wins can provide a profit potential of mil-

lions of dollars. The following calculations illustrate the prof-

it potential of pricing:

Example 1: An average lending rate increase of 10 basis points

based on the credit volume of a bank could lead to additional

profits of U.S.$1 million (based on a volume of credit of U.S.$1

billion), U.S.$10 million (based on a volume of credit of U.S.$10

billion), or U.S.$100 million (based on a volume of credit of

U.S.$100 billion).

Example 2: A U.S.$10 average increase in per customer profit

could lead to additional profits of U.S.$1 million (based on

100,000 customers), U.S.$5 million (based on 500,000 cus-

tomers), or U.S.$10 million (based on 1,000,000 customers).

These examples demonstrate the power of pricing, also known

as ‘power pricing’ [Dolan and Simon (1996)].

A bank sells its golden credit card for U.S.$100. Sales volume is

one million units. The variable costs per unit are U.S.$60, which

results in a contribution margin of U.S.$40 per unit. The bank’s

fixed costs are U.S.$30 million. In this situation, the bank earns

a profit of U.S.$10 million [(100-60) dollars/unit x 1 million units

— U.S.$30 million]. How does each of the four profit drivers —

price, variable costs, volume, and fixed costs — change profit

when improved by 10 percent? A 10 percent increase in price

($100 to U.S.$110) leads (ceteris paribus) to a profit increase of

100 percent, from U.S.$10 million to U.S.$20 million [(110-60)

dollars/unit x 1 million units — U.S.$30 million]. The effect of the

other profit drivers is much lower. A 10 percent improvement of

variable costs, volume, and fixed costs leads (ceteris paribus) to

a profit increase of 60, 40 and 30 percent respectively. Bearing

this in mind, management should concentrate more on intelli-

gent price increases than on other measures, such as cost cut-

ting. As a result, managers and decision makers must see the

price as the ‘primary profit driver’. This is especially true in sit-

uations with low unit margins.

Before a bank decides whether to increase or decrease prices

it should analyze the impact of price changes given different

cost-income ratios. The bank needs to ascertain how much vol-

ume has to be gained (price reduction)/can be lost (price

increase) in order to keep the cost-income ratio constant.

Managers should only change a price if the expected effect on

volume is higher/lower than the given percentages. For exam-

ple, at a cost-income ratio of 0.75, a price reduction of 10%

only increases profit, if a volume increase of 67% or more is

expected. A 10% increase in price only increases profit, if the

volume decrease is lower than 29%.

Increased margins stimulated by professional pricing immedi-

ately increase profit and do not require expensive upfront

JOURNAL13v06 16-02-2005 11:17 Pagina 25

investments or severance pays. Relative to cost cutting, price

management offers three opportunities, it gains time, avoids

additional upfront expenses, and increases profit more

strongly. Surprisingly, most managers either do not focus on

the price or they make the wrong decisions. The following

case reveals the power of pricing. An American bank has

earned revenues of U.S.$1 billion. The profit is around U.S.$50

million. A sophisticated analysis shows that price increases of

on average around 5% are possible without losses in volume.

Consequently, the profit would increase by 100% — from

U.S.$50 million to U.S.$100 million. The key question is: How

can such a measure be successfully implemented?

Pricing processes: The key to successSimple price increases, such as an increase of all prices by 5%,

would be very risky and do not work. Just increasing existing

prices or ordering sales persons to negotiate higher prices will

fail. Banks must apply innovative price strategies that focus on

the customers’ need, value pricing, and are supported by a

completely restructured pricing process. In our experience,

many banks and insurance companies today do not follow a

systematic pricing process. Such a process is comprised of a

system of organizational rules, structures, and measures

intended to determine and implement prices. Pricing process-

es are complex and cover the following aspects:

1. The five phases of the pricing process:

■ Strategic guidelines (objectives, positioning, competition) —

What do we want? Where do we want to get to?

■ Status-quo check (current situation and processes) — How

do we do it today?

■ Price decision (structure, level, customization, bundling) —

What is the optimal price/price structure?

■ Implementation (organization, responsibility, IT, incentives)

— How can the price be enforced into the market?

■ Controlling/monitoring — How did the prices develop?

2. Information, methods, models, rules, qualifications, compe-

tencies, and deadlines.

3. Subjective (e.g. estimations, experience) and objective (e.g.

market, competition data) components.

When companies offer such a large number of products as

many banks do, with retail price lists of banks very often cov-

ering more than 200 price components, or prices are negotiat-

ed for each transaction, pricing processes are crucial. Due to

the high number of necessary price decisions, the effort

involved in each decision has to be limited. Precisely defined

processes are required to determine and implement prices and

thereby foster acceptable yields. The issue of pricing processes

is rather new for several reasons. Traditionally, price decisions

have been mostly made based on the feelings and subjective

judgment of the person in charge. At present, the concept of

pricing processes has been implemented consistently only by a

few companies, mostly in the life science and automotive

industries. The second reason why the issue is so new is that

pricing processes have been a difficult topic for academic

researchers. On the one hand, these processes are very indus-

try-specific and quite often also company-specific, requiring

time and labor-intensive research to understand. On the other

hand, pricing processes are kept top secret. An automotive sup-

plier, for instance, is not interested in initiating a public discus-

sion about its pricing processes. According to our findings,

effective pricing processes usually increase the return on sales

by about 2 percentage points. In light of the dismal situation

which most companies are currently facing, this is revolution-

ary. Figure 1 examines the increase in profit using cases from

various sectors of the financial services industry.

The increase in the return on sales in the right column of

Figure 1 should be read as follows: In the case of a retail bank,

the margin improved by 1.6 percentage points. The cases pre-

sented in the figure prove that the starting points for process

improvements are very specific. An increase in the return on

sales cannot be achieved based on simple price increases.

Instead, more intelligent measures have to be applied, a cru-

cial insight for success. Moreover, top management must

commit to the new pricing process. After all, the reorientation

of the company’s competencies regarding pricing and the

resulting profit increase are at stake. The following cases from

the banking industry demonstrate the impact of a new pricing

process.

26 - The Journal of financial transformation

JOURNAL13v06 16-02-2005 11:17 Pagina 26

27

■ In the retail unit of a large bank, profits could be increased

through an improved differentiation of customer seg-

ments. One group of regular customers reacted strongly

to the price increases, other groups and new customers

did not show any reaction to the same measures.

Improved coordination between pricing, segmentation,

product customization, and communications significantly

increased marketing efficiency. The bundling of certain

products and prices to packages was crucial, especially for

cross-selling [Wuebker (2003)].

■ Another bank was able to increase its revenue by 10 per-

cent after a sophisticated analysis of the competitors’

prices, price elasticities, segmentation, and customized

products. A detailed analysis of several product categories

demonstrated that no systematic pricing process existed

in the company. Every business unit used a different

approach to determine prices. Pricing guidelines, a frame-

work for the price policy, were missing. The price elastici-

ties of analyzed products were unknown. Prices were

determined based only on costs or competitors’ prices.

The project served as a pilot for the future pricing organi-

zation.

■ A pragmatic analysis of price sensitivities was identified as

a profit driver for the private banking division of a bank.

Based on this analysis and some updated price structures,

quick wins were generated. The additional revenue was

several tens of millions dollars.

■ The sales force of another bank was identified as being

overly generous with discounts. They made price the cen-

tral issue in negotiations with their customers. This prob-

lem was solved using argumentation guidelines and a new

incentive system.

These cases support the assertion, that generating profits

through pricing is not an issue of simply increasing or decreas-

ing prices. The parameters for improvement are more com-

plex: information, knowledge, competence, responsibilities,

incentives, price structures such as multidimensional or non-

linear prices, price bundling, multi-person pricing, and cus-

tomization are some of the most important ones. Ultimately, a

successful pricing process is about dramatically increasing

pricing intelligence.

Optimization of pricing processes: A case study Strategic guidelines (Phase 1)

During the first phase of the pricing process, the price strate-

gy and desired price positioning must be defined. In general,

banks do not have guidelines for pricing their products and

services. These guidelines have to be consistent with the

future strategy and the positioning of the bank. One bank

established the following guideline in a workshop: ‘We are a

premium bank. For the high value we deliver we set the appro-

priate prices. Our price position is in the upper quartile.’

In the next step, the strategic pricing objectives have to be

defined and prioritized. In our experience, complex and unin-

telligible target systems are relatively widespread. The follow-

ing example illustrates this. The conflict between profit and

volume targets is well known. Most bank managers strive for

higher prices without losing volume or market share. In many

banks, only explicit volume targets have been defined (number

of credit cards, number of new contracts, transactions, assets

under management, etc.). Consequently, profit is not the only

target that must be considered. A combination of profit and

volume targets is common in business practice. Managers

have to find a balance between volume and profit. This trade-

off must be resolved and made explicit.

Industry Revenue Main starting point for Increase in

category improved process return on

sales (%)

Private U.S.$500 Pricing process

banking million Pricing audit5

Retail U.S.$1-5 Extensive extraction of brand value

banking billion Increased pricing competence of 1.6

relationship managers

FundsU.S.$600 Price implementation on indirect channels

million Intelligent price segmentation5

InsuranceU.S.$100- Restructuring and optimization of branches

500 million Optimization of sales strategy 7

Figure 1: Efficient pricing processes lead to major profit increase

JOURNAL13v06 16-02-2005 11:17 Pagina 27

Status-quo check and price optimization (Phases 2 and 3)

The profitability of individual customer relationships is

unknown to many banks. In light of this, a structured and sub-

stantiated data analysis is required. In general, banks store a

great amount of customer information and data. However, this

information is frequently not properly structured. An in-depth

data analysis clarifies which customer relationships are prof-

itable for the bank under consideration. The case study

reveals that the contribution margin of many customer rela-

tionships is below zero and that there is no clear relation

between assets under management and contribution per cus-

tomer. This analysis is a crucial prerequisite for future price

decisions.

The analysis of the existing pricing process of the bank

showed that price decisions in general were focused on costs

or competitors. The impact of price variations on the sales vol-

ume was unknown to product managers. The lack of knowl-

edge about the relationship between price and volume and

price elasticities repeatedly caused poor decisions regarding

the optimal price. In the future, product managers will gather

sufficient information for price decisions. This information

involves crucial elements, such as value drivers and benefits

of the targeted customer segment, the willingness to pay, and

segment-specific price elasticities. Methods like expert judg-

ment or conjoint measurement have demonstrated their capa-

bility in the gathering of such information [(Wuebker and

Mahajan (1999)]. The result of these methods is a price-

response function, which serves as a base for the calculation

of optimal prices.

Implementation and monitoring (Phases 4 and 5)

A profit improvement potential of 2 percent (measured in

terms of return on sales) through the professional optimiza-

tion of prices and products is realistic for many banks. To turn

this potential into reality, the sales force must understand,

accept, and communicate to the customer the new prices and

their structures. In customer negotiations, the price, and not

value-to-customer, is frequently the focus, which results in

overly generous discounts. To avoid this, three instruments

have proven successful in enforcing higher prices and value on

the market, an incentive system for the sales people, indica-

tors for better evaluation and segmentation of customers

(regarding their price elasticities), and sales guidelines.

‘Incentive systems’ are crucial for the implementation of a

centrally planned price process. They are the only means of

achieving the intended price positioning. The purpose of an

incentive system is to link the bank’s objectives to those of the

sales person. Defining a sales person’s objectives through a

combination of volume (i.e. a number of successfully signed

contracts or volume of invested capital) and profit targets has

proven to make sense. In the long run, only profits, not volume

alone, secure the market presence of a bank.

Another way to enforce higher prices on the market is by

using an ‘indicator system’ to estimate the customer’s price

sensitivity. Relationship managers could be asked to classify a

representative sample of their customers in terms of these

indicators. By aggregating these judgments, an overall estima-

tion of the customers’ price sensitivity can be obtained. The

advantage of this method is its simple, fast, and pragmatic

operation. A quantification of the relationship between prices

and volumes is not possible off-hand.

When negotiating, relationship managers should never argue

relying only on price. The customers’ willingness to pay always

reflects the perceived value of the products and services.

Consequently, value, not price, should be the focus of the

negotiation. In business practice, we often notice the opposite

as the following case shows. A wealthy customer intends to

invest a huge amount of capital, more than U.S.$1 million, at a

bank of his choice. He is welcomed with the following words:

‘You are such a wonderful customer. Therefore we will grant

you our special price, which is 30% below our regular price.’ In

saying so, the customer relationship manager started an

unnecessary price discussion. As a result, the customer, sur-

prised by the generosity, demanded further discounts, ending

with a final price 50% below list. To avoid such a disaster, rela-

tionship managers should emphasize the value and services

28 - The Journal of financial transformation

JOURNAL13v06 16-02-2005 11:17 Pagina 28

29

generated by the bank. This requires a profound understand-

ing of the value drivers. This is the basis for developing ‘sales

and argumentation guidelines’. Supported by a value-based

argumentation, relationship managers are able to convince

the customer that the demanded price is right. Enforcing price

and value can be significantly bolstered this way.

Implications: Reaping the harvestMany banks are suffering from a profit crisis. Simple price

reductions in general reduce contribution margins dramatical-

ly, resulting in a profit collapse. Consequently, the cause of

many crises is price erosion, which is frequently started

because the reactions of competitors and customers are not

correctly estimated. Many bank managers do not sufficiently

understand the effects of price on volume. Yet price is the pri-

mary profit driver.

The bank’s executive managers must focus more strongly on

profits and prices. Companies need innovative pricing strate-

gies, which are in line with customers’ needs and value per-

ceptions and accompanied by an overall reorientation of pric-

ing processes. At successful banks like UBS, pricing is closely

linked to their organization. Other banks are just starting this

process.

The value-to-customer of products and services is not com-

pletely understood by many banks. Consequently, they do not

charge the appropriate price for the value delivered.

Increasing profits through more effective pricing processes is

a challenge for top management. Gains in the area of several

tens of millions of dollars can be achieved by implementing

professional pricing processes. The additional profit comes

from numerous measures.

At one company the following price and product measures

were implemented: Optimization of prices for core products

(U.S.$5.1 million additional profit), guidelines for systematic

discount strategy (U.S.$4.4 million additional profit), structur-

ing of special discounts (U.S.$3.2 million additional profit),

optimization of key account pricing (U.S.$3.1 million additional

profit), improved price customization (U.S.$2.8 million addi-

tional profit), and implementation of centralized controlling

(U.S.$1.0 million additional profit).

A systematic pricing process is comprised of five phases: strat-

egy, a status-quo check, the price decision, implementation,

and controlling/monitoring. Most companies do not follow a

systematic and standardized price decision process. The start-

ing point of professional pricing is substantial information.

Price elasticities, the willingness to pay for different products,

etc. have to be known to optimize prices and products.

Reliable and valid methods, such as conjoint measurement, to

collect such information are necessary.

The art of pricing lies in using intelligent and innovative means

of price customization to exploit the customers’ willingness to

pay [Schmidt-Gallas (2004)]. Some of these means are non-

linear pricing, multi-person pricing [Dolan and Simon (1996)]

and price bundling [Simon and Wuebker (1999)]. Companies

like Dell or Microsoft have successfully adopted these meth-

ods. They are a benchmark for value pricing.

References• Baumgarten, J. and G. Wuebker, 2004, “Strategies against price wars in the financial

service industry,” February 10, offshoretoday.com.

• Dolan, R. J. and H. Simon. Power pricing — How managing price transforms the bot-

tom line. The Free Press, New York (1996).

• Hardock, P. and G. Wuebker, 2003, “Bundling in the banking sector — a promising

strategy to create value,” March 12, offshoretoday.com.

• Lauszus, D., Added value private equity: Professional price management to increase

profitability. SKP White Paper (2004).

• Schmidt-Gallas, D., Profitable growth for insurance companies: Manage your pricing

or lose money, SKP White Paper (2004).

• Simon, H., and G. Wuebker. Bundling — A powerful method to better exploit profit

potential, in: Herrmann, A., R. Fürderer and G. Wuebker. Optimal Bundling. Springer,

New York (1999).

• Wuebker, G., 2002, “Bundles’ effectiveness is often undermined,” March 18,

Marketing News, p. 12.

• Wuebker, G. and V. Mahajan. A conjoint analysis based procedure to measure reser-

vation price and to optimally price product bundles. Herrmann, A., R. Fürderer, R.

and G. Wuebker. Optimal Bundling. Springer, New York (1999).

JOURNAL13v06 16-02-2005 11:17 Pagina 29

78 www.usfst.com

FST. Why does pricing represent an area of op-

portunity for banks?

FR. The pricing of deposits and loans is at the

core of managing the performance of a bank.

Yet in our work with a number of the large

money-center banks, we have found that the

pricing process is fundamentally broken. While

executives understand that they have some

pricing power in their respective markets, they

lack the tools to translate business strategy

and corporate goals into the tactical pricing of

products.

The lack of focus on pricing is surprising.

Most banks still manage their pricing strategy

with Excel spreadsheets, and the ratio of risk

analysts to pricing analysts in the typical bank is

probably five-to-one or higher. Similarly, banks

have invested significantly in risk-management

technology but have completely neglected pric-

ing technology.

FST. You’re saying the pricing process is fun-

damentally broken – that’s a strong statement.

What do you mean?

FR. Let’s take a look at the typical pricing process

in a large US bank. First, the Executive Pricing

Committee comes up with the pricing strategy.

However, there is no clear understanding of the

profit and volume tradeoffs when defining ob-

jectives for product and segment performance.

Next, the Pricing and Profitability team

manually translates that pricing strategy into

pricing tactics by using a combination of a

risk- and market-based approach to pricing, to

come up with rates for each product, channel,

market and customer segment. Despite their

best efforts, 80 percent of the rates are too

high or too low. One of the key reasons for this

problem area is that customer response to pric-

ing is poorly understood and often judgmental.

Most pricing managers do not have the tools or

the insight to understand how many more deals

are generated or how much profit is lost by de-

creasing a rate by 25 basis points in a specific

segment of the market. And, those that do have

the luxury of having access to price response

models have no infrastructure in place to opti-

mize thousands of rates simultaneously across

products, markets and customer segments.

Then because the Pricing Operations team

manually types those rates into the pricing ex-

ecution system, three to five percent of these

rates are miscoded. Now the rates are avail-

able to the Credit and Funding Operations.

This group works directly with customers to

negotiate the best rate for each individual

transaction. However, often times the front-

line negotiation rules are overly simplistic. For

example, the front-line staff is empowered to

give customers with a checking account a 50

basis point discount on loans and an additional

25 basis points of pricing discretion on all CDs,

regardless of the customer’s value to the bank.

Up to 20 percent of profits are lost during this

poorly managed negotiation process.

Last, but certainly not least, without a

rigorous actual performance tracking process,

the Pricing and Profitability team have a difficult

time determining whether or not performance

targets where met. And, if they were not met,

the pricing team is often unable to identify the

reasons why performance varied from plans,

which could help them make better pricing deci-

sions in the future.

These shortcomings in the pricing process

can result in profit and volume losses of as

much as 10-20 percent. However, there is an

even bigger issue that I believe was a root cause

of the credit crisis we have seen over the last

three quarters: banks and finance companies

have not managed to connect pricing strategy

to a balanced understanding of profitability and

market demand.

FST. So you believe that pricing is a root cause

of the credit crisis?

FR. Yes. What we saw from 2003 through the

summer of 2007 was a very aggressive expan-

sion of consumer credit – specifically mortgag-

es – without adequate risk premiums to cover

Frank Rohde is Chief Marketing

Officer and Vice President of

Product Management at Nomis

Solutions. He has 15 years of

experience in financial services,

working with a range of clients on

product development, marketing

and pricing problems.

Why banks must fix their pricing processThe last nine months have been difficult for US banks and finance companies, with market conditions causing executives to significantly lower future performance expectations. FST spoke with Frank Rohde of Nomis Solutions about what banks can do to weather this crisis.

In a recent survey of pricing managers

across the top 30 banks and finance

companies in the US and Canada, 90

percent admitted that their pricing

process was in dire need of improvement.

Executives in the top 10 banks in the US

admit privately that their ability to use

pricing to drive business results is limited.

FR.

EXECUTIVE INTERVIEW

79www.usfst.com

expected and unexpected losses. Because

banks didn’t have a comprehensive pricing op-

timization platform in place, they were unable

to adequately assess the cost of the adverse

selection that was invariably occurring in the

near- and subprime markets.

In addition, most banks were basing their

pricing strategy on what the competition was

doing, and the current pricing models that

banks had in place were not accounting for the

changing customer behavior down the line.

No one was running simulations or optimiza-

tions to determine how a portfolio of 620-FICO

customers with 90 percent LTV loans would

perform under these changing conditions.

Since October 2007, the pendulum has

swung the other way. Rather than adequately

price loans for near- and subprime customers,

the market has shut down completely. This

is an overreaction, out of fear that every new

mortgage to a 620-FICO customer will default.

During the good times, loans were signifi-

cantly underpriced compared to their level of

risk, and now because banks don’t know how

to price them, these loans are simply not of-

fered. Of course there is an optimal price for the

620-FICO 90 percent LTV customer, but banks

do not have the systems in place to determine

that price, so they miss out on the opportunity.

FST. Shouldn’t risk-based pricing have pre-

vented the excesses you’re describing?

FR. Sure. The problem is that pricing strategy is

often the result of a negotiation between vari-

ous stakeholders in the bank without the benefit

of a common information layer. While the times

were good, the marketing and sales instinct of

the bank took over and loans were priced the

same as everyone else in the market, in order to

grow volume and gain market share. Now fear

has taken over and banks are overreacting in

the other direction.

What is missing in this process is a pricing

and profitability management platform that

provides a common depth of pricing insight

to all stakeholders in the organization. Such a

platform would translate strategic goals and

constraints into the thousands of price points

a bank has in the market across deposit and

credit products. It should also accurately bal-

ance risk and profitability forecasts with an un-

derstanding of demand and competitive prices,

and allow for rapid recalibration of a strategy as

the market and consumers change.

FST. So how can banks fix their pricing process

and platform?

FR. Pricing optimization enables executives

to leverage pricing as a core strategic driver

of performance. Pricing should not be treated

as a support function. Instead it should be a

core competency, because it is the quickest

and highest leverage strategy that a bank can

deploy to impact results this year.

During the third quarter of 2007, net inter-

est margins for US banks were the lowest since

1991. Competition for deposit funds is heating

up and we’re starting to see some irrational pric-

ing, and credit charge-offs continue to increase.

In this environment, pricing optimization is one

of the few ways in which executives can improve

net interest margins and keep volume propped

up. Pricing optimization starts to show results

within months rather than years, and as such is

one of the few tools that executives have at their

disposal to weather the next 12-24 months.

Forward-looking organizations have real-

ized this potential and made pricing optimiza-

tion a strategic initiative, with high levels of

executive visibility. In addition to executive

sponsorship, choosing the right technology

partner is critical, as is ensuring the right

level of change management and communica-

tion internally.

But most importantly, I believe that if banks

and finance companies implement a compre-

hensive pricing and profitability management

platform, this will prevent a repeat of the irra-

tional pricing and excesses we have seen in the

last three years. n

Visit www.nomissolutions.com or contact us at [email protected] or 650-588-9800.

The root cause of the credit crisis we have

seen over the last three quarters is that

banks and finance companies have not

managed to connect pricing strategy to a

balanced understanding of profitability and

market demand.

“I believe that if banks and finance companies implement a comprehensive pricing and profitability management platform, this will prevent a repeat of the irrational pricing and excesses we have seen in the last three years”

Current Pricing Practices & Processes are Flawed

RESEARCH

Executive Research Report APRIL 2012

BAI Research Study:

The New Dynamics of Consumer Banking Relationships

S E G M E N T- D R I V E N P E R S P E C T I V E S

Inside:• Consumer Segments: Key Differentiators

• Service and Channel Usage

• Views on Financial Institutions

• Satisfaction with Primary Bank

• Considerations and Take-Aways

• Analytically Driven Segmentation: SAS Case Study

S P O N S O R E D B Y

TA B L E O F C O N T E N T S

E X E C U T I V E S U M M A R Y . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 3

F I V E C O R E C O N S U M E R S E G M E N T S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 4

S E G M E N T P R O F I L E — AT A G L A N C E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 5

I N S I D E T H E M I N D S O F C O N S U M E R S : V I E W S O N F I N A N C I A L I N S T I T U T I O N S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 6

C O N S U M E R S A N D T H E I R P R I M A R Y F I N A N C I A L I N S T I T U T I O N S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 7

F O C U S O N : S E R V I C E A N D C H A N N E L U S A G E B Y S E G M E N T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 8

S E G M E N TAT I O N P R I S M : C O M PA R I S O N S O F K E Y D I F F E R E N T I AT O R S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 9

F O C U S O N : C O R E P R O D U C T AT T I T U D E S B Y S E G M E N T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 0

C O N S U M E R I N S I G H T S : C O N S I D E R AT I O N S O N S T U D Y F I N D I N G S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1

S A S P E R S P E C T I V E : A N A LY T I C A L LY D R I V E N S E G M E N TAT I O N . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2

S A S C A S E S T U D Y: U N C O V E R I N G H I D D E N O P P O R T U N I T I E S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 3

T R E N D S A N D TA K E - A W AY S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 4

S T U D Y M E T H O D O L O G Y . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 4

BAI is pleased to present findings and analysis on an in-depth consumer study, sponsored by SAS, which was conducted in November 2011. Given the twin pressures of recent regulatory changes coupled with a lower rate environment, the research sought to answer the central question: How can financial institutions grow profitable customer relationships? The New Dynamics of Consumer Banking Relationships study addresses this key issue.

The findings and supplemental commentary presented here will provide bank executives with insights into how to better expand core deposit relationships, including:

• Consumer needs of bank products and services• Perspectives on consumer segments and strategies to address them• How consumers interact and engage with their banks

The study was conducted on a nationally representative sample of 3,200 U.S. consumer households, reflecting the U.S. Census demographics across age, gender and region. More information on the methodology is presented at the end of this report.

RESEARCH

PAGE 3

The New Dynamics of Consumer Banking Relationships Segment-Driven Perspectives

A C T I O N TA K E - AWAY

THE OPPORTUNITY FOR REVENUE GROWTH LIES IN TUNING CHANNEL AND SALES

CONFIGURATION ACCORDING TO SEGMENT MIX AND POSITIONING OF YOUR BANK.

A combination of a sluggish economic recovery and increased regulation has slowed the pace of revenue growth for banks in 2012 and beyond. As a result, the top priority of financial institutions has shifted from acquisition and origination to share of wallet capture. The focus is on delivering a perfect customer experience in every interaction across all channels. Doing so, requires a deep understanding of what customers need, want and expect.

The New Dynamics of Consumer Banking Relationships study defined five consumer segments that provide opportunities for banks to develop deeper relationships and gain greater share of wallet. The segments — Marginalized Middles, Disengaged Skeptics, Satisfied Traditionalists, Struggling Techies, and Sophisticated Opportunists — have their own characteristics and attitudes concerning banking overall, their primary bank and other factors.

Generally, satisfaction with and likelihood to recommend one’s primary bank goes hand-in-hand with other measures of customer satisfaction. Meanwhile, there is an opening for banks to expand relationships with customers. In fact, findings show consumers are eager for their banks to approach them with a cross-sell opportunity to strengthen their ability to manage their finances appropriately.

E X E C U T I V E S U M M A R Y

• Five consumer segments — ranging from Marginalized Middles to Sophisticated Opportunists — were profiled in the study

• Consumers are generally satisfied with their primary bank, but these relationships can be expanded

• Customers are eager for banks to approach them with additional products and services to address their needs

• Tuning channel and sales configuration according to segment mix and bank positioning are critical for revenue growth

• Vital differentiators in consumer segments go far beyond assets, income and other demographic indicators

• Customer segments created as recently as one or two years ago will need to be replaced based on the new market realities

Preview of Key Findings

• Marginalized Middles – By far, the largest segment in size, these consumers tend to be below average age* with above average income**. They also make up almost 40% of the large national bank population. However, this same segment is the least satisfied with their primary financial institution and the most confused about bank fees. These consumers visit branches least often of all the segments, and are the most likely to pay someone else to handle their finances.

• Disengaged Skeptics – The second oldest group of consumers, this segment has below average income** and is overall disengaged with the financial services industry. They are less likely than most groups to use any available services, particularly mobile. These consumers have the lowest monthly usage of most channels and also tend to have a high concentration of accounts with other financial institutions, including brokerage firms and other non-traditional channels.

• Satisfied Traditionalists – The oldest group of consumers with approximately average income**, this segment is generally satisfied with their primary financial institution. However, they have the lowest share of wallet at their primary financial institution and are not likely to consolidate their products at one financial institution. Additionally, this segment is the least likely to utilize online, mobile or debit services. Also noteworthy, these consumers have the second highest total deposit revenue per household potential, and they expect a wide variety of product offerings. The second most highly concentrated group at community banks, these consumers have the second lowest concentration at large national banks.

• Struggling Techies – This segment is home to the youngest group with the lowest income. Active in their finances and comfortable making tough financial decisions, these consumers are very receptive to financial institutions proactively pursuing their business with tempting offers. They are also the most likely to use online, mobile and debit services — and to use them frequently. While this group has low deposit balances, they have the highest share of wallet at their primary financial institution. These consumers are at the point in their lives where there is very low total deposit revenue per household potential.

• Sophisticated Opportunists – Of average age* and with the highest income, these consumers report the highest satisfaction with their primary financial institution. Much like the Struggling Techies, they are very receptive to financial institutions proactively pursuing their business with tempting offers. These consumers are knowledgeable about the banking world and comfortable making decisions regarding their finances. Their use of mobile and debit reward services is higher than most of the other segments. These consumers have the highest total deposit revenue per household potential.

PAGE 4

Five Core Consumer Segments Enable More Targeted Approaches The study identified five segments representing the current consumer landscape. By better understanding the differences in consumer preferences and attitudes, financial institutions can more effectively tailor products, services, pricing, sales and communication to customer needs. This more targeted approach allows banks to maximize share of wallet and develop deeper customer relationships based on segmentation. Banks can focus on the segments that they are well positioned to serve and that may offer the best opportunity for growth. The five segments are briefly defined as follows:

*AVERAGE AGE = 45.5 **AVERAGE ANNUAL INCOME = $62,100


The five segments identified in the study can provide direction to help banks more precisely target value propositions. While many financial institutions tend to market to the “average” customer, hidden within the broad customer base are often distinct segments with extremely different preferences. By understanding the differences across segments, banks can more closely address individual customer needs. The result is improved customer interaction across channels leading to deeper relationships and greater share of wallet.

Changing Consumer Trends: A Look BackOne need only look at prior research to see how consumer views and attitudes change over time. The BAI Research Study: The Quest for Deposits conducted in 2003 identified six consumer segments — Minimalists, Skeptics, Self-Servers, Sophisticates, Loyalists and Traditionalists. The dispersion of the segments was fairly even in the 2003 study, compared to the current research findings. Consumer attitudes and perceptions have changed significantly on certain aspects since that time. While Struggling Techies are a new segment, for example, they are the second largest population of the respondent consumer base. With their tech savvy and use of social media, these customers can have a significant impact on a bank’s reputation should they become dissatisfied. These characteristics could go unrecognized if using segmentation profiles based on income, age and other basic factors. It is also crucial to look at segments on an ongoing basis to be aware of any attitudinal changes.

Segment Profile — At a Glance


Marginalized Middles

36%

Disengaged Skeptics

18%

Satisfied Traditionalists

18%

Struggling Techies

21%

Sophisticated Opportunists

7%

Below average age with above average income

Second oldest group with below average income

Oldest group with roughly average income

Youngest group with lowest income

Average age with highest income

Largest segment, they make up about 40% of the large national bank population

Least satisfied with their primary financial institution while most confused about bank fees

They visit the branches least often of all the groups

Most likely group to pay someone else to handle their finances

This segment is the least satisfied group with all aspects of customer service at their primary financial institution

They are less likely than most groups to use any available services, especially mobile

Lowest monthly usage of most channels

High concentration of accounts at other institutions, including brokerage firms and other non-traditional channels

While this segment is satisfied with their primary financial institution, they have the lowest share of wallet there and are not likely to consolidate their products at one institution

This segment is also the least likely to utilize online, mobile and debit services

However, they do have the second highest total deposit revenue per household potential and expect a wide variety of product offerings

They are the second most highly concentrated group at community banks and have the second lowest concentration at large national banks

Active in their finances and comfortable making tough financial decisions, this segment is very receptive to financial institutions proactively pursuing their business with tempting offers

Most likely to use online, mobile and debit services and to use them frequently

While this group has low deposit balances, they have the highest share of wallet at their primary financial institution. At this point in their lives, however, there is very low total deposit revenue per household potential

This group is the most satisfied with their primary financial institution and, like the Struggling Techies, are very receptive to financial institutions proactively pursuing their business with tempting offers

They are very knowledgeable about the banking world and comfortable making decisions regarding their finances

Their use of mobile and debit reward services is higher within this segment than most other groups

This group has the highest total deposit revenue per household potential

This research was conducted, in part, to obtain responses that would allow us to segment in such a way that more targeted marketing efforts could be undertaken with this information. The segments in this research were formed using respondents’ attitudes towards banking in general.

NOTE: PERCENTAGES REPRESENT PERCENT OF TOTAL STUDY PARTICIPANT UNIVERSE. AVERAGE AGE = 45.5 AVERAGE ANNUAL INCOME = $62,100

Inside the Minds of Consumers: Views on Financial InstitutionsWhen asked about their attitudes and knowledge of financial institutions overall, consumer responses reveal some fairly pronounced differences between the segments. These variances provide insights into how products and services can be tailored based on these attitudinal dispositions. For example, in the chart below, 15% of the Marginalized Middles, which is by far the largest group, ranked “confusion about fees” as a top concern. For this segment in particular, a strong onboarding program associated with clarity and

transparency around fees and fee structure, rates and other matters could help alleviate these concerns.

The Struggling Techies and Sophisticated Opportunists segments, meanwhile, provide strong responses to specific questions. More than 80% in both groups agreed they would be willing to consolidate all accounts with one institution for a financial reward. For these customers, a rewards program is quite important in how they make certain decisions. Not surprisingly, consumers who tend to be extremely savvy with finances understand the mechanics and benefits of rewards programs and utilize them.


Simply looking at assets, income and other basic demographic indicators does not show the sets of differentiations on key attributes of the different consumer segments. These insights are vital in optimizing everything from product packages to marketing campaigns.


Consumers’ Attitudes on Financial Institutions Percentage Who Strongly and Completely Agree

Will go with one FI for a financial reward

Why product selection is very important

Confused about fees my FI charges

MARGINALIZED MIDDLES

8%

11%

9%

DISENGAGED SKEPTICS

33%

1%

13%

SATISF IED TRADIT IONALISTS

51%

STRUGGLING TECHIES

10%

76%

SOPHISTICATED OPPORTUNISTS

Perhaps not surprisingly, the amount of active involvement in day-to-day finances varies by a wide range across segments, from a high of 99% to a low of 14%. Consumers, though, are generally in agreement that they are not comfortable investing in the current market, with rankings varying by only 11 points, from 33% to 22%. This supports a key finding from the study that consumers are open, and actually looking for, financial advice — another opportunity for financial institutions to fulfill an unmet customer need and expand the relationship. Likewise, financial institutions can make sure that those who prefer online and self-serve channels have easy-to-use tools, and assistance when needed, at their disposal.

Drill Down: Consumers and Their Personal Finance PreferencesPercentage Who Strongly and Completely Agree

57%

36%

15%

83% 82%

0%

Actively involved in my day-to-day finances

Not comfortable investing in current market

Rather pay someone to manage my finances 11%

44%

28%


14%

22%

11%

DISENGAGED SKEPTICS

25%

4%


83%

33%

4%

STRUGGLING TECHIES

26%

5%


92% 99%

SATISFACTION with Primary Bank Views on CUSTOMER SERVICE

Consumers and Their Primary Financial InstitutionsGood news! While some broad consumer polls have shown low approval ratings for the banking industry in general, this recent study shows that the attitudes of consumers towards their primary bank and its staff are overall positive. Consumers’ satisfaction with their primary institution comes in at a strong 62%, generally better than had been anticipated at the study’s onset.

While the likelihood to recommend their primary institution decreases slightly to 58%, compared to overall primary satisfaction, these are still good signs. Other results show potential opportunities to grow share of wallet. As shown by the chart below, a strong majority of consumers agree that their primary bank executes transactions accurately and quickly, and has a warm and friendly staff. However, fewer respondents agree that their primary bank proactively suggests financial products.

LIKELY NEITHER LIKELY NOR UNLIKELYUNLIKELY

SATISFIED

NEITHER SATISFIED NOR DISSATISFIED

DISSATISFIED

CUSTOMER SERVICE ATTRIBUTE STATEMENT

PERCENTAGE OF THOSE WHO AGREE WITH STATEMENT

LIKELIHOOD to RECOMMEND Primary Bank

34%

4%

62%

7%

35% 58%

Consumers, generally, do not find their bank’s push for new products to be very proactive — an area of potential growth.


Consumer attitudes about their primary bank reveal some key attributes behind what drives satisfaction and the likelihood to recommend. The study also analyzed these findings across all five segments. This segmentation allows financial institutions to better identify and target customers most receptive to specific new product offerings and retail marketing campaigns.

Executes my transactions without any mistakes

Executes my transactions/ requests quickly

Has staff that are warm and friendly

Offers me excellent in-person service

Has staff that are knowledgeable, well trained and efficient

All of my product questions or requests can be handled by one phone call

The first person I talk to can handle all of my requests

Provides access to specialists to discuss my financial needs

Proactively suggests financial products to me

69%

67%

67%

63%

61%

55%

52%

51%

39%

Overall, consumers are satisfied and likely to recommend their primary financial institution.

C L O S E R L O O K


NOTE: The figures in the top left chart represent the scores from a 7 point scale where 1 was Extremely Dissatisfied, 2 – Dissatisfied, 3, 4 and 5 – Neutral, 6 – Satisfied and 7 – Extremely Satisfied. The satisfied rating in the pie chart represents the respondents who chose 6 and 7, the neutral rating represents those who chose 3, 4 and 5, and the dissatisfied rating represents those who chose 1 and 2. A similar rating scale is also used for the other two charts on this page (Extremely Likely, Likely, etc. and Strongly Agree, Agree, etc.)

Focus On: Service and Channel Usage by Segment As executive bankers review these consumer findings, it is important to look at this analysis in context of segmentation. If particular results are simply considered in terms of age and income, they present one profile. Whereas when viewed through the prism of rigorous segmentation, variations of the profiles begin to appear that can inform an institution’s distribution strategy.

The chart below shows the channels and services most frequently used across all five consumer segments. The more mature channels and services, such as online banking and debit card, generally pull in some of the highest usage percentages. Perhaps, not surprisingly, direct deposit is also climbing up due to some of the free checking requirements to avoid fees. Keep in mind, these are primary checking accounts — not ones at other institutions. Mobile banking, on the other hand, generally shows lower usage rankings. This is most likely driven by the mature alternatives available in the U.S. Mobile use is far more widespread, for instance, in other countries that do not have the infrastructure of the U.S. markets. But given access to tellers, ATMs and other channels, these scores remain relatively low. As needs and comfort with mobile, contactless and other alternatives grow, these numbers are anticipated to tick up substantially.


Snapshot: Top Banking Channels and Services

As shown above and in the charts on the opposite page, Struggling Techies are more likely to use online and mobile options at their primary financial institution than any other segment. This same group is also more likely to use the debit card as well as overdraft protection and early cash access services. Conversely, Satisfied Traditionalists are less likely to be online, use mobile financial capabilities, or use any kind of debit card.

While the Struggling Techies may embrace the technology channels and emerging components, they generally currently lack the financial wherewithal to be amongst the most valuable customers of an institution. This segmentation perspective can be used to determine if these types of consumers should be viewed as potential customers.

On the other hand, Satisfied Traditionalists score low in mobile banking usage. These consumers are typically ambivalent to these types of alternatives as they tend to rely heavily on in-person channels. Here, too, these deeper segment perspectives can help financial institutions determine if this market aligns with strategic plans.

Online Banking

Debit Card

Direct Deposit

Online Bill Pay

Overdraft Protection

Mobile Banking

81%

84%


87%

79%

78%

DISENGAGED SKEPTICS

73%

79%


85%

STRUGGLING TECHIES

79%

81%


91% 89%91%

88%73%

79%

69% 67% 65% 74%72%

63% 62% 61% 66%69%

33% 24% 21% 40%45%


Customer segments created as recently as one to two years ago will need to be replaced with new and expanded versions given the new market realities. Assess your institution’s capabilities compared to these segments to determine the points of intersection. Thoroughly re-examine your customer engagement strategy, making sure you are targeting the right segments with the right products, services and channels.

Additional Banking Services — Usage at Primary Financial Institution shown as % more or less likely to use as compared to the average

2 10

-2-3

4 36 5

2

-3 -2 -2 -1

-9

-1

-6

1

20%

15%

10%

5%

0%

-5%

-10%

-15%

-20%

DEBIT CARD DIRECT DEPOSITOVERDRAFT PROTECTION

REWARDS DEBIT CARD

EARLY CASH PAYMENT


Banking and Payment Channels — Usage at Primary Financial Institution shown as % more or less likely to use as compared to the average

20

1

-1 -1

0

58

6 7

2 3

13

7

11

-2 -2

-8-6 -6

-4 -4

-11

-1

-8

20%

15%

10%

5%

0%

-5%

-10%

-15%

-20%

MORE THAN AVERAGE

MORE THAN AVERAGE

ONLINE BANKING ONLINE BILL PAY MOBILE BANKING P2P PAYMENTS MOBILE BILL PAY

TOTALSAMPLE

AVERAGE

TOTALSAMPLE

AVERAGE

LESS THAN AVERAGE

LESS THAN AVERAGE

MARGINALIZED MIDDLES DISENGAGED SKEPTICS

STRUGGLING TECHIES SOPHISTICATED OPPORTUNISTS

SATISFIED TRADITIONALISTS

S E G M E N TAT I O N P R I S M : C O M PA R I S O N S O F K E Y D I F F E R E N T I AT O R S

-1 -1

25

-2-3

1

TOTAL MARGINALIZED MIDDLES

DISENGAGED SKEPTICS

SATISFIED TRADITIONALISTS

STRUGGLING TECHIES


Satisfaction with account

67% 59% 60% 79% 70% 82%

Likelihood to recommend

60% 52% 52% 70% 64% 76%

Years of ownership

11.6 11.2 12.6 14.0 9.6 10.7


68% 61% 60% 80% 71% 83%


62% 56% 53% 75% 66% 79%

Years of ownership

11.1 10.7 12.3 13.5 9.2 10.3


64% 53% 55% 76% 76% 80%


62% 52% 54% 69% 76% 77%

Years of ownership

9.4 8.4 10.1 11.7 8.6 7.6


66% 57% 55% 77% 73% 82%


66% 55% 55% 75% 76% 79%

Years of ownership

8.0 7.1 8.8 8.6 7.6 9.2

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EC

KIN

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ING

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PAGE 10

Focus On: Core Product Attitudes by SegmentSegmenting consumer attitudinal data by individual product is crucial to effective marketing efforts. By targeting the best customers for a specific product, a bank can improve conversion rates and campaign profitability.


Given the current economic environment, resources should be prioritized on those segments with the highest opportunity for revenue and profit growth. If the drive is to expand deposit relationships, look at segmentation to help determine which customers to focus on and what will attract those chosen segments. Likewise, analyzing consumer attitudinal data on loan and investment products can identify receptive customers to target with cross-sell campaigns.

The study asked consumers about their attitudes regarding three core products — deposit, loan and investment — at their primary bank. As the chart below shows, segmenting customer attitudes on their deposit accounts by satisfaction, likelihood to recommend and years of ownership allows a bank to better identify cross-sell opportunities and target campaign messaging and dollars. Similar attitudinal findings by segment were also revealed for loan and investment products.


Deposit Relationships at Primary Financial Institutions

Consumer Insights: Considerations on Study FindingsWhile there is a consistent cycle to banking products and services, the time is right to consider more developed forms of segmentation. Today’s segmentation efforts are rudimentary, and usually involve overlays and some age, income or asset segmentation. These can be very effective for their purpose, but with the advent of social media and other channels of communication, segmentation platforms must move to the next level.

Given all the macroeconomic considerations and shifts in unemployment, the economic outlook remains a concern for most U.S. consumers. As such, their need for guidance and services from financial institutions to help manage their money is likely to continue growing. However, this guidance and these services do not always have to be performed in person or offered at a branch. There are low-cost mechanisms for meeting those customer needs. The top online brokerage firms do a tremendous job of managing customer relationships through good toolkits and call centers. There isn’t a silver bullet for all, and for certain segments such online alternatives apply more favorably. The Marginalized Middles, for example, visit branches the least often, and self-service channels could be a low cost alternative to expand these relationships.


Key Recommendations

MARGINALIZED

MIDDLES

This is the largest segment and the group with the second highest revenue per household potential for checking accounts

While these consumers are the least satisfied with their primary financial institution, the size of this segment may make it impractical to provide more personal assistance. Frequent, easy-to-understand marketing messages and other communications, particularly around fees and rates, could help improve customer satisfaction

Additionally, this group visits branches the least often — rather than in-person interactions, offering them more education on the use of self-service channels could be a low-cost way to further solidify the relationship

DISENGAGED

SKEPTICS

This segment is very dissatisfied with all aspects of customer service at their primary financial institution

Their current concentration of accounts in other financial institutions (i.e. brokerage firms) and lack of channel and service usage leaves the door open for these other institutions to capture greater share of wallet with them through similarly priced products and the added bonus of enhanced customer service

As this is the second oldest segment, competitive products could also be marketed as a less risky transition product as they draw nearer to retirement

SATISF IED

TRADIT IONALISTS

This segment is a hard group to pin down as they have low receptivity to product offerings and technological advances made by other institutions in addition to a low deposit share of wallet

However, they are a tempting group as they tout a high deposit revenue per household potential and the highest investment balances, so building a wide product base within an institution focused on satisfying this group could potentially drive share of wallet and revenue

Products and services that manage cash flow with low risk could catch the attention of this group as they are the oldest segment

SOPHISTICATED

OPPORTUNISTS

High-potential group, needs to be treated well — and provided with the right tools (such as online financial planning and investment management) as well as other innovative products that allow them to manage their own finances

They are very knowledgeable, so clarity around fees as well as product features and benefits is important

This segment is the most receptive to consolidating with one financial institution, so product packaging is important (i.e. offering rewards)

STRUGGLING

TECHIES

Currently, a low deposit revenue potential group who are averse to fees, but have an immense liking of all things technological. Their receptivity combined with their balances across all products makes them a segment worth targeting

If it is possible, involve them in your technological innovation and social media initiative processes. Other than this interaction, their banking style allows for a relatively hands-off approach

As the youngest group, involving them in aspects of banking they are drawn to may get them more vested in your institution early on and keep them as customers as they grow into a more profitable segment

With a better understanding of differences in consumer preferences and attitudes, financial institutions can more effectively tailor products, services, pricing, sales and communication to customer needs. Here are some insights to help financial institutions focus on the segments they are well positioned to serve and that may offer the best opportunity for growth.

Analytically Driven SegmentationAs financial institutions pursue revenue growth, customer retention and profitability, building an analytical framework can help deliver superior results for marketing strategies. Analytics enhance the decisions made to execute strategies and plans to be more effective and achieve better results.

• Analytically driven, granular segmentation enables identification of different customer segments that are most likely to respond to specific campaigns or marketing actions.

• Predictive modeling capabilities enable specific target populations to be identified that are likely to respond positively to a specific campaign or other marketing activity. These capabilities can also be used to better understand and more precisely predict the behavior of targeted groups.

• Optimization capabilities help maximize economic outcomes by making the most of each individual customer communication while considering the financial institution’s resource and budget constraints, contact policies, the likelihood that customers will respond and other factors.

P E R S P E C T I V E

C U S T O M E R

S E G M E N TAT I O N

Drives I N I T I AT I V E S

EnablesC U S T O M E R

I N S I G H T

C A PA B I L I T I E S

Who are our targeted customer

groups?

Customer Strategy

Who are our most valuable customer

segments?

What are their key characteristics &

value proposition?

Which treatments/ offers to present to

each segment?

Key Outputs

• Differentiate customers based on segments• Segment treatment strategies• Marketing optimization (based on resources)

The foundation for this analytical framework is access to comprehensive, clean customer data that can be analyzed to create unique customer insight and effective segmentation. This data source should be continually updated based on interactions with customers and prospects, ranging from purchase transaction data to online data from the bank’s website users and direct marketing response data.

Driving Results through Segmentation


C A S E S T U D Y

U N C O V E R I N G H I D D E N O P P O RT U N I T I E S I N E X I S T I N G C U S T O M E R R E L AT I O N S H I P S

With a strategy to gain wallet share, a premier North American financial institution sought to more effectively market to its existing client base. Among the challenges were making sure the right customer got the right product or service offer at the right time, over the right channel.

Sounds easy, right? Now add in that the bank has about 20 million customer accounts spread out across its different business lines.

In the past, the institution ran one-off customer campaigns for a total of five or six campaigns a year. Now it turns to predictive modeling and optimization methodologies to provide campaign execution and decision support. As a result of these steps, the bank has exponentially increased the number of campaigns it runs per year, helping to generate more sales.

S I X M I L L I O N L E A D S … A N D G R O W I N G

The bank currently runs between 30 and 60 campaigns per year, which go out to half a million customers every month, helping to generate about six million leads over the course of a year. Finding those customers would have been a major hurdle under the old methodology where every campaign was its own little island.

With SAS® Marketing Optimization, the analytics team is able to mine through the bank’s seven million customers — and up to 18 months of data — to derive insights for more targeted customer campaigns. This solution maximizes campaign outcomes by helping refine individual customer communications while increasing marketing return on investment by determining the best offers for individual customers. This is all in addition to delivering analytic insight into the value of business constraints, such as channel capacity and contact policies.

TA R G E T E D C A M PA I G N S Y I E L D I N G S I G N I F I C A N T R E S U LT S

Driven by more targeted campaigns and improved customer service, annual growth is 80,000 to 100,000 incremental accounts more than what the bank would gain by simply waiting for customers to come through the door. The SAS solution allows this leading North American financial institution to make better use of its resources, speed up the time it takes to optimize a marketing concept and send leads. As a result, the bank is achieving an ROI in excess of 100% — a significant return for the cost of the solution.

Financial Services Marketing Best Practices S T R AT E G I C S E G M E N TAT I O N

• Analytical and Operational Profiling

• Predictive and Analytical Modeling

• Customer State Changes

• Event Triggering

• Real-Time Decisioning

C A M PA I G N E X E C U T I O N

• Collaborative Marketing

• Channel Coordination

• Coordinate Inbound and Outbound Marketing

• Decision Optimization

• Marketing Campaign Optimization


The forecast for retail banking in 2012 is stormy. The slow and uneven economic recovery, along with continued housing and mortgage challenges and the impact of new regulations, will make revenue and profit growth more difficult than ever. In fact, it is estimated that “the cost of recent regulations, combined with continued low interest rates, could reduce retail bank revenues by a third to one-half,” according to the December, 2011, BAI Banking Strategies Executive Report, A Look Ahead to U.S. Retail Banking 2012.

Given this reality, banks must go back to the drawing board and thoroughly re-examine all aspects of their customer engagement strategy — business as usual is no longer enough.

Re-examining the customer engagement strategy must start with a confirmation that financial institutions do indeed know their customers well enough to serve their needs in a manner that delivers excellence in customer experience every time, while maximizing the institution’s opportunity to grow revenue and profit from the relationship. The findings in this report clearly show that segments created even one or two years ago will not position an organization for success given the new market realities. Using this research to define new and an expanded number of customer segments will be the best path to greater share of wallet in a difficult market environment.

Phase II — National Consumer Survey

To achieve the research objectives, the New Dynamics in Consumer Banking Research Program utilized a two-phase approach. This report focuses on Phase II:

S T U D Y M E T H O D O L O G Y

• A comprehensive survey was conducted among a nationally representative sample of 3,200 consumer households to obtain detailed intelligence on a range of personal financial and bank consumer behaviors, attitudes, beliefs and preferences. The research insights include:

– Conjoint/discrete choice model to assess tradeoffs of pricing, convenience, and other drivers of choice/selection and bank usage.

– Segmentation to uncover unique bank consumer segments in terms of preferences and motivators of bank product and service selection and usage.

– Profiles of bank consumer product and wallet share characteristics by psychographic and demographic variables.

• In the quantitative portion of this study, responses were collected from consumers who met the following criteria:

– Sole or joint decision-maker for financial goals in household

– Any type of deposit, loan, or investment account with any type of financial institution

– Between the ages of 21 and 74

– Household income of at least $25,000

• The 3,200 respondents reflect the U.S. Census demographics across age, gender, and region. The regions are Northeast, Midwest, South, and West.

T R E N D S A N D TA K E - A W AY S


© 2012. CONFIDENTIAL. The insights and research methodologies described in this white paper are the intellectual property of BAI and shall not be reproduced or shared directly or indirectly with any other market research or consulting firm, without the express written permission of BAI.

SAS is the leader in business analytics software and services and the largest independent vendor in the business intelligence market. Drawing on 35 years of experience in financial services, SAS helps banks, credit unions, lenders, capital markets firms and other organizations address critical business needs. More than 3,200 financial institutions worldwide use SAS® solutions, including 97 percent of banks in the Fortune Global 500®.

SAS provides a suite of customer analytics solutions that expand the reach of the marketing function across the institution, giving banks the power to find the most profitable growth opportunities, take the best marketing actions and maximize cross-business impact.

• Focus on the customers, segments and offers that will generate additional revenue with the highest return on marketing investment (ROMI).

• Optimize every customer interaction across every channel in real time to grow customer lifetime value (CLV).

• Deliver a consistent customer experience that aligns products, channels, sales and service through a complete picture of customer relationships.

Learn more and discover our white papers and webinars: sas.com/banks

BAI is the financial services industry’s partner for breakthrough information and intelligence needed to innovate and stay relevant in an evolving market- place. For more than 80 years, we have focused on advancing the industry by offering unbiased education and research. Our offerings are as diverse as the industry, and include premier events such as BAI Retail Delivery Conference & Expo, ground-breaking research and performance metrics, professional learning and development programs, and in-depth editorial coverage through BAI Banking Strategies. Visit www.BAI.org for more information. BAI is Bank Administration Institute and BAI Center.

RESEARCH

BAI115 S. LaSalle St., Suite 3200Chicago, IL 60603USA

Phone: (312) 683-2469www.BAI.org

SAS Institute Inc. 100 SAS Campus DriveCary, NC 27513-2414 USA

Phone: (919) 677-8000 www.sas.com/banks


fs viewpointwww.pwc.com/fsi

The Price of Success: Aligning Pricing with the Customer Value Proposition

02 10 13 24 28

Point of view Competitive intelligence A framework for response How PwC can help AppendixMarch 2012

Point of view

3Point of view

Banks are facing strong headwinds in the current environment.

Changing consumer behavior and preferences have challenged banks’ abilities to compete effectively. Furthermore, mounting regulation and a difficult economic environment have made it increasingly more difficult to remain profitable.

• New online banks are changing consumer’s expectations about what a bank should offer, the perceived value of financial products and services, and the level of service a bank should offer.

• Consumers’ willingness to pay is continuously changing by market segment, product, service, and channel. Consumers are shopping around for the best financial products with no sense of loyalty, often turning to non-banks, such as retail stores and payday lenders, to meet their financial needs.

• Over the years, consumers have become accustomed to receiving free “basic” banking services and their views of what products are considered basic are expanding to include more costly services.

Bank offerings Consumer needs

Product

Channel

Price

Product

Channel

Price

Product

Channel

Price

Goodalignmentresults in

perceptionof value

Product

Channel

Price

Product

Channel

Price

Product

Channel

Price

From the rise of non-bank alternatives to Bank Transfer Day, consumer sentiment towards banks is changing. Banks are re-thinking their value propositions and how they should adapt products, delivery channels, and pricing to consumer needs.

4 FS Viewpoint

Traditional approaches to increase bottom line performance are running out of steam. More and more banks are discovering a critical driver for managing profits: pricing.

Pricing—the biggest missed opportunity in banking?

Based on our experience, pricing has significant leverage on profitability. Unlike other levers—such as growing market share or reducing operating costs—pricing changes fall directly to the bottom line. The reality is that price optimization has the potential to create more value than a bank can expect from overall reduction in variable costs, fixed costs, or increase in volume.

Moreover, our analysis shows that between one percent and five percent of value is lost because companies neither know enough about their customers’ willingness to pay nor have the ability to translate this knowledge into effective pricing strategies.

Leading firms take a strategic approach to pricing and continuously reevaluate the approach.

Banks should focus more carefully on the historical variation in their prices and understand how different customers value their products. Pricing should become a critical part of a bank’s strategy for developing its value proposition with customers and achieving long-term growth.

The power of pricing

1% Change inselling price

1% Change invariable cost

Incr

ease

in p

rofit

1% Change infixed cost

1%Change in

volume

8%

6%

4%

2%

Changing prices by 1% has a stronger impact on profit than changing anyother profit drivers by the same percentage.1

1 Based on PwC analysis.

5Point of view

Banks are beginning to acknowledge the potential value from pricing as a powerful profit lever. Furthermore, banks are realizing the need for more innovative approaches to respond to current and emerging pricing issues.

• Do we understand what customers value in our products? How do we prove our value proposition and present that to customers?

• How do we match the right price with the right customer? Why is there little or no relationship between the price set and the price that is finally accepted? Is pricing segmented to recognize the variations in perceived value among different customer segments?

• What market share will we achieve at different price points?

• Do we understand what drives cost to serve? Have we considered all the relevant costs into account to determine our floor prices?

• Are our pricing policies aligned with a customer’s contribution to the top-line and the bottom line?

• What is the value of our product compared to alternatives?

• Can we price based on our competitor’s vulnerabilities?

• What should we bundle as part of the base fee vs. charge for separately?

• How do we price our products or services for maximum profit?

• Can pricing help drive a multi-channel product offering?

• Should a price level similar to online competitors be implemented for products sold on the Internet? What are the price variations across regions, channels, customer segments?

• How much should be charged in each channel, and will the market allow any price differentiation between channels?

Product

Channel

Customer

6 FS Viewpoint

Leading banks are implementing “voice of the customer” (VOC) programs and behavioral economics techniques to influence customer perceptions, preferences, and behaviors.

Better insight into the mind and behaviors of the customer leads to better pricing.

In order to compete successfully in today’s environment, banks should understand how different customer segments value their products and services relative to the competition and the price that people are willing to pay.

The value consumers place on products and services is driven by more than just price—it is tied to a complex set of interrelated social, emotional, and psychological factors. “Behavioral economics” refers to the set of principles that helps explain and predict such

consumer behavior. VOC programs combined with behavioral economics help explain customer behaviors, preferences, and perceived product preferences relative to various price points.

Banks can leverage VOC data and behavioral economics design techniques to answer the following questions:

• What do customers really value about the bank and its products?

• How likely are customers to buy a product? At what price will they buy?

• What makes customers buy from one channel instead of another?

Enabling a shift from product-centric to customer-centric offerings.

These customer insights provide the requisite information to influence buying behavior—by tailoring the right products and bundled product solutions to the right customer segments at prices that offer the most compelling value proposition in the mind of customers. Using behavioral economics design combined with risk-based pricing techniques could also increase the long-term value of selective customer segments.

Product perception by customer segments (illustrative):Relative to its price, some customer segments will value a product more than others.

Per

ceiv

ed p

rice

Valuedisadvantaged

Value advantaged

Perceived benefits High

Downscaleretirees

Wealthyretirees

Fiscalrookies

Youngprofessionals

Powerprofessionals

Wealthyaccumulators

Hig

hLo

w

Low

Working classtraditionalists

Value disadvantaged customer segmentValue advantaged customer segment

Circles represent different customer segments. Size of circle represents approximate relative size (population) of the segment.

7Point of view

Why haven’t more banks adopted price optimization? Many are reluctant to adopt innovative pricing strategies due to commonly held beliefs—many of them untrue—about how price optimization works and the investment required to begin seeing returns.

Common objections we’ve heard What our experience tells us

“Quality data is in short supply.” • While data is important, it does not need to be perfect. Most banks find that they can leverage data from their origination, servicing, and financial systems to get started.

“Pricing takes a lot of judgment. How can data analysis replace the experience our professionals have?”

• Data-driven pricing analysis is a tool that is intended to complement, not replace, commercial judgment.

• In addition to pricing-, volume-, and characteristic-driven data analysis, several other variables (such as competitor landscape, non-price promotions, product lifecycles) impact sales. It is not always possible or practical to model these types of factors, and commercial know-how is needed to reconcile what the data is saying with real-world knowledge.

“It takes a long time to realize gains from pricing changes.”

• Pricing changes can usually be tested through limited pilots before being rolled out on a larger scale. Once a pricing strategy has been successfully tested and rolled out, benefits fall to the bottom line immediately.

• To make pricing changes stick, banks need to enforce standard processes and discipline across the organization.

“We have no control over pricing—the market sets it, and if we don’t fall in line, we’ll lose our customers.”

• While the market is competitive, different customer segments will vary in how they value a specific product or service. VOC data can help banks quickly hear and react to changing customer sentiments.

• The objective of data-driven pricing is to find 1) the customer segments that are willing to pay more for a given product (without significant loss of volume) and 2) those customers where modest price reductions can lead to substantial volume gains.

“Our product teams are already stretched thin and don’t have the capacity to get involved in a pricing project.”

• Most banks do not need to pull together large groups of people to start analyzing pricing opportunities and developing new strategies. A small team is all that is needed to get the project started and begin piloting initial proposals.

“We are already navigating many pricing-related regulatory requirements with the Credit Card Responsibility and Disclosure (CARD) Act and Dodd-Frank, and don’t want to add to the complexity.”

• Regulatory drivers of pricing will be better supported, managed, and compliant with increased focus on customer value and supporting analytics.

8 FS Viewpoint

As banks move from cost-plus price management to transaction-driven management, they are able to pinpoint margin and revenue leakages (such as in customers, products, and markets) and enable the organization to achieve the best price in every single transaction.

Many banks are realizing that traditional pricing approaches and capabilities are inadequate for achieving their strategic business goals. Leaders are embarking on a journey to pricing excellence that involves more pricing innovation and better discipline.

A bank that continues on to value-driven price management is able to understand how different customers value its products relative to the competition and estimate the price-elasticity of different customers for the demand of different products through different channels.

Pricing capability maturity model

Pri

cing

cap

abili

ty

Business value

Hig

hLo

w

Low High

Cost-plus andmarket pricemanagement

Transaction-driven pricemanagement

Value-driven pricemanagement

Monitor and continuousperformance improvementOrganizational alignment

Pricing operations, data management,and technology Pricing analytics

• Consumer behaviors drive targeted pricing decisions based on willingness to pay for one bank’s products relative to its competitors.

• Formal and standardized processes for price optimization.

• Price optimization system integrated with price management.

• Formal customer analytics and market intelligence function.

• Quantitatively measure andpredict pricing performance.

• Address common causes of pricing variation.

• Continuously refine prices based on customer behavior and market conditions.

• Historical information is used to manage pricing at a customer segment level.

• Formal and standardized processes for price setting and price management.

• Price management system has been implemented.

• Some proactive pricing analysis.

• Price exceptions are managed on an ad hoc basis.

• Analytics are limited to the expected cost to serve customers.

• No formal or standardized processes in place.

• Reliance on spreadsheets.

• Underutilization of available tools.

• Passive analysis; no detailed measures available.

• Minimal opportunities to analyze meaningful data.

• No centralized price setting and management organization.

• Centralized price setting and price management function.

9Point of view

In our view, banks that develop their capabilities in these six areas are better positioned to use pricing as a competitive advantage across market and customer segments as well as the entire portfolio of deposit, lending, and transaction products and services.

What is it? Expected benefits

Pricing strategy Provides a framework that supports overall business objectives.

• Aligns the organization to implement the bank-wide pricing strategy.

• Establishes competitive differentiations in the market.

• Links pricing strategy to multi-channel price management.

• Creates a value proposition that can be presented to customers.

Transaction and customer pricing analytics

Assessing current and historical transactional data can reveal revenue and margin leakages, and predict customers’ price sensitivity or willingness to pay.

• Identifies sources of revenue and margin leakages.

• Better understanding of customer preferences, profitability, and price sensitivity (“willingness to pay”).

• Ability to predict profitable pricing strategies.

Pricing operations

The processes and controls that enable banks to implement their pricing policies consistently and efficiently.

• Standardized processes lead to consistent practices when developing incentives, promotions, and contracts.

• Accounting controls provide more accurate and consistent measurement of pricing performance and customer profitability.

Data management and technology

The data and pricing technology tools that enable fact-based pricing decisions based on rigorous application of analytics.

• Leverage existing technology to scale pricing analysis to multiple business units, customer segments, and geographies.

• Provide more robust monitoring and reporting of pricing performance.

Organizational alignment

Clearly defined pricing roles and responsibilities that are supported by the right incentives. Includes roles for pricing governance, analytics, sales effectiveness, and execution.

• Business units and line personnel (branches, sales) that work toward the same pricing goals.

• Enhanced training and expertise in how pricing changes impact customer behavior and profitability.

Monitoring and continuous performance improvement

Standardized processes and metrics for monitoring compliance with pricing policy and continuously refining prices.

• Pricing policy is applied consistently, enabling an appropriate level of discipline while balancing the need for flexibility.

• Standardized pricing metrics can be used to compare different geographies, business units, and customer segments.

• VOC data can be monitored for leading and lagging indicators of changing consumer behavior and sentiment.

Our observations of industry practices.

Competitive intelligence

11Competitive intelligence

Pricing is often set directly by sales representatives, instead of being guided by practices that are grounded in analytic rigor and customer interaction.

Leading practice areas

What we observe in the industry

Bank A Bank B Bank C

Pricing strategy Pricing center sets core product rate bands for use by commercial banking sales officers. Officers have authority to negotiate rates without approval if within the band.

System controls prevent exceptions to approved deposit rates. The pricing center publishes premium rate offers that are available to branch officers, though incentives and guidelines to encourage premium offers are weak.

Commercial sales officers set product rates for each customer at their discretion. The pricing center publishes guidelines; however, because there are no system or other controls to ensure compliance, they are routinely disregarded.


Product price bands are set, based on the price elasticity of demand curves. The pricing curves are modeled based on historical sensitivity of balance flows to the bank’s rates relative to competitors.

Deposit rates are set based on a test and learn methodology in which customer rates are incrementally lowered and performance is tracked.

Product pricing is set based primarily on wholesale rate changes or competitor price reactions.

Pricing operations The process for handling exception pricing requests is informal, requiring ad hoc review by the pricing team. No formal process requirements, such as review criteria, escalations, or response windows, are in place.

Promotional rate plans are assigned rate plan numbers to which each participating account is linked on setup. Rate plans can be re-priced or terminated at the bank’s discretion.

There is no centralized process for handling or tracking exception activity. Approval processes are in place for local sales teams only.

Leading On Par Lagging

12 FS Viewpoint

Many banks are beginning to recognize pricing opportunities, but changes have been uneven. This has limited some banks’ abilities to fully realize profit and growth opportunities.

Leading practice areas

What we observe in the industry

Bank A Bank B Bank C


Elasticity tool is used to set product price bands. Competitive rates are provided weekly through an automated vendor data feed.

Pricing tool is under development. Deposit rates are captured weekly through an automated vendor feed.

Analytics for assessing product rates are ad hoc and spreadsheet-based. Data warehouse structure does not support efficient pricing analysis.


Spread revenue, based on funds transfer pricing (FTP), is attributed directly to deposit sales officers for incentive compensation purposes. Officers are observed to frequently negotiate customer rates to below pricing center guidelines.

Branch officers and treasury management sales officers are compensated on a balanced scorecard that includes FTP deposit revenue as well as balance levels and fees.

Relationship managers set product rates. Although FTP deposit revenue affects compensation, it is a small proportion relative to loan spread and deposit-balance based metrics; deposit pricing has modest impact on compensation.


Centralized pricing group models and monitors pricing performance and approves all policy exceptions.

Finance works with product managers to balance product profitability with adoption and to periodically review price performance.

Each product manager is responsible for setting prices and driving product adoption. Product managers are incentivized on sales volume without regard to profitability.

Leading On Par Lagging

A framework for response

Our recommended approach to the issue.

14 FS Viewpoint

The following six capabilities are fundamental to setting the stage for an effective pricing management program.

Pricingcapabilities

Transactionand customerpricing analytics

Pricingstrategy

Monitoringand continuousperformanceimprovement

Pricingoperations

Data managementand technology

Organizationalalignment

15A framework for response

Many companies lose revenue and margins due to having a poor understanding of their customers, the positioning of their products in the market place, not knowing what drives value to their customers, or what drives cost to serve.

Pricing is an integral part of a bank’s go-to-market strategy. The pricing approach a bank takes should be aligned with how it wants

to be positioned in the market. As financial institutions mature their pricing capabilities, they will be better able to respond to external forces while building upon their brand and value proposition.

Setting a pricing strategy is part of a recurring process and should be periodically re-assessed based on changes in internal and external strategic drivers.

Pricing strategy

Articulate what kind of bank you want to be—and how pricing will be used to get there. Brand

Market position

Cor

por

ate

Voice of the

Regulatory

Product value

customer

landscape

proposition

obje

ctiv

es

Internaland external

strategicdrivers

Pricingcapabilities


Pricing strategy



Pricing operations


16 FS Viewpoint

Price band analysis and price waterfall analysis tools have proven valuable in providing a foundation to capture opportunity at the transaction level, in allowing organizations to identify areas of price erosion, and in achieving the best net realized price for each customer or transaction. Margin leakages and unwarranted price concessions can be analyzed for a given product or business unit across geographies or customer segments.

Pricing transaction analytics

Examine transaction data using established analytical tools to identify sources of revenue and margin leakages.

Analytical tools Benefits

Price band analysis

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

2.0%

• Identifies distribution and variability between the invoice price and the actual transaction price (margin bands) among customers within and across different customer segments, products, geographies, and channels.

• Helps control the variation of prices by product, channel, and customer value for setting prices.

Price waterfall analysis100% 4%

96% 1% 95% 1% 94% 1% 2% 2%1% 88%

• Captures, quantifies, and visually displays each element (revenue leak) of the price structure, cascading down from list price to invoice price to pocket price which occurs after price is set with the customer.

• Flags outlier customers whose cost to serve in certain areas is disproportionately high or whose margin across transactions is consistently lower than average.

• Identifies which cost elements have the greatest impact on margins.

• Highlights which cost-to-serve elements can be reduced in order to keep a larger portion of the list price.

• Links cost to serve with pricing levels and customer segmentation.

• Used in conjunction with price band to target potential customer groups for price increases.

Pricingcapabilities


Pricing strategy



Pricing operations



Analytical tools such as voice of the customer, conjoint analysis, and price elasticity modeling help guide product price positioning and set target prices. In addition, banks can quantitatively measure how customers perceive product attributes and how its products compare against those factors. The analysis identifies tradeoffs between benefits and price (i.e., how much customers are willing to pay for superior product features or service benefits).

Customer pricing analytics

Employ price elasticity techniques to understand customer price sensitivity and predict their response to alternative price strategies and scenarios.

Analytical tools Benefits

Voice of customer (VOC) and conjoint analysis

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0.3 1.61.8

• Determines which features to include in bundled products or which features could be separate products.

• Provides insights into what customers value, how they buy the product, and opportunities to influence buying behavior through prices.

Price elasticity modeling

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• Provides a probabilistic view of customer buying behavior and an indication of elasticity changes, revealing how sales of a product and related substitutes respond to price changes.

• Predicts demand for one product when there is a change in the price in another product.

• Identifies customized product bundle variants at the right price to improve cross-selling.

• Predicts how price influences demand for products as a function of volume or channels.

• Uses this information to optimize pricing strategies to enable profit and volume improvement across various customer segments.

Pricingcapabilities


Pricing strategy



Pricing operations


18 FS Viewpoint

Pricing operations

Design standard processes and controls to effectively execute the pricing strategy.

Effective pricing operations require the entire organization to work closely together to facilitate effective execution. Successful banks will implement a governance model that balances centralized control and expertise with flexibility, as appropriate.

Standardized processes Established controls Agreed-upon metrics

• Standardize the process for developing and approving customer pricing deals and promotions.

• Design standard pricing policies for each product and sales channel.

• Understand why price exceptions are made and whether process or policy adjustments are needed.

• Establish a decision rights framework to define the pricing decisions that need to be made, and to identify the individuals responsible and authorized to make them.

• Develop controls to enforce consistent execution of pricing policies and procedures.

• Standardize accounting controls over the measurement and recording of customer incentives, promotions, and contracts.

• Establish metrics for evaluating the performance of the pricing strategy.

• Validate that the metrics used are aligned with the pricing strategy and goals of the institution.

• Agree on which pricing and margin points will be valued during negotiations and decision making.

Pricingcapabilities


Pricing strategy



Pricing operations




Leverage data management and technology to develop the right tools to identify profit improvement opportunities and set prices.

Areas Action Steps

Long-term customer-focused data strategy

• Make the necessary technological investments to improve the customer experience.

• Gather standardized data points consistently across all customer touch-points.

• Assign a universal customer identifier to track the activities of individual customers across all business units.

Pricing technologies and tools

• Develop the technological tools necessary to make monitoring pricing performance routine and to automate advanced elasticity analytics.

• Implement an agile technological infrastructure that allows for changes in the pricing strategy to be deployed quickly.

• Build good accounting controls into systems to enable the pricing strategy to be more effectively executed.

Data management and customer databases

• Standardize pricing systems, processes, and tools to facilitate collaboration across marketing, sales, accounting, IT, and other business units involved in pricing decisions.

• Build data warehousing capabilities to support customer-level data needed for ongoing pricing analysis.

Data quality controls • Data needs to be reliable, but not perfect, in order for the analytics and performance metrics to be effective.

• Automate the aggregation of data from multiple sources to close gaps between systems and to minimize manual input.

• Establish security controls to prevent data manipulation by unauthorized users.

Security concerns • Perform ongoing vulnerability assessments over servers and systems that secure customer transaction information.

• Evaluate threats to the environment and prioritize the resulting gaps to understand and address where the highest risks reside.

Banks collect a great deal of data, but we find they don’t consistently set up the technology infrastructure and processes to effectively analyze and leverage it. There are several steps that banks may want to consider to build the necessary data and technology foundations to support rigorous pricing analytics.

Pricingcapabilities


Pricing strategy



Pricing operations


20 FS Viewpoint

Effective pricing strategies bring marketing, sales, and operations together in order to facilitate more coordinated and effective execution. Senior management involvement also helps balance the level of input from various functional areas.

Organizational alignment deals with the people and culture factors that shape pricing behavior, including organizational structure, sales effectiveness, training, and talent management. Effective pricing management would include such issues as providing training on sales policies and procedures, developing profitable sales compensation structures, and creating reporting relationships that help the company develop and carry out pricing decisions.


Provide the right training and incentives to support defined pricing roles and responsibilities.

Key steps Activities

Define pricing roles and responsibilities

• Define cross-functional pricing roles and responsibilities across the organization (such as sales, marketing, operations, product management, branches).

• Establish consistent practices around how centralized functions (such as pricing strategy and analytics) should interact with business units and field personnel, and decide on who will have authority to make pricing decisions.

• Develop formal communication channels to provide a rapid dissemination of pricing information to customer-facing employees, and to collect feedback that is used to fine-tune pricing decisions.

Train and develop pricing expertise

• Ensure that salespeople have access to the right tools and are properly trained to execute the pricing strategy.

• Effectively manage the talent lifecycle, including workforce planning, recruitment, development, and performance management.

• Develop a process to inform employees of changes in the sales strategy.

Align incentives with pricing objectives

• Review incentive compensation plans, sales force performance, data sales tools, sales training, and territory and account information.

• Design incentive plan and performance reporting metrics that align compensation with pricing/profitability objectives.

Key considerations• What are the roles and responsibilities,

goals, and incentives for everyone who is involved in pricing, and are these functions aligned?

• How centralized or decentralized should the pricing process be?

• How do we expect salespeople to spend their time, and do they have the right skills and tools to manage prices effectively?

• Are compensation metrics aligned with both our strategies and our execution capabilities?

Pricingcapabilities


Pricing strategy



Pricing operations




Establish an ongoing process for measuring pricing performance and providing feedback that continuously refines the pricing approach.

Once a pricing strategy has been determined, it should be supported by an ongoing process of implementation and feedback. Monitoring processes may help ensure adherence to pricing policies and evaluate whether the pricing strategy is being achieved—through feedback from both internal (such as sales, finance, front-line personnel) and external (such as customers, market information) sources.

Banks that fail to continuously refine their pricing strategies are missing out on one of pricing’s greatest benefits—the fact that its impact can be quickly measured and the approach re-calibrated with relatively little operational effort.

Align pricing execution across the organization with standardized and agreed-upon practices.• Ensure compliance with agreed-upon

pricing policies.

• Evaluate exception requests based on analytics, market information, and customer relationship data housed at the center.

• Calibrate pricing limits.

• Monitor potential margin leakages and unplanned variations between geographies, business units, and customer segments.

• Communicate pricing authorities and policies to business unit personnel.

Monitor pricing performance.• Determine which data sets and tools

are needed to routinely evaluate pricing performance.

• Maintain pricing key performance indicators (KPIs), ensuring that definitions and thresholds are consistent across the bank.

• Integrate input from VOC programs with pricing strategy and refinement processes.

• Prepare and distribute interpretive pricing reports for executive management and business units.

• Define reporting outputs and requirements—rules for defining, capturing, storing, and archiving data.

• Align resources that are accountable for quality and the reporting of data inputs.

Pricingcapabilities


Pricing strategy



Pricing operations


22 FS Viewpoint

Moving to the future state

An innovative pricing approach can help identify near-term price improvement opportunities and develop a “world-class” pricing methodology, with the tools, data, skills, and processes to support it.

A two-phased approach can help financial institutions identify pricing opportunities that have the largest impact and invest in capabilities that are most aligned with long-term corporate objectives.

Phase 1: Perform analysis and identify opportunities

Pricing transaction analysis

Customer analysis Opportunity identification and prioritization

Activities • Conduct customer price band variation analysis.

• Conduct cross-product price variation analysis (price/value analysis).

• Conduct price waterfall analysis to identify the factors that contribute to the difference between the list and actual price.

• Develop potential strategies to address profitability opportunities.

• Conduct customer perceived value analysis (price vs. product quality and features).

• Conduct customer conjoint analysis and price elasticity analysis:

- Customer perceived value of product structure alternatives.

- Potential demand implications.

- Expected usage behaviors.

- How pricing alternatives influence client behavior.

• Analyze current processes, organization, controls, pricing systems/tools, analytics, governance, sales incentives, KPIs, and monitoring.

• Identify and develop opportunities for improvement (process, organization, technology, analytics).

• Develop an opportunities prioritization framework; prioritize identified opportunities and group them into:

- Quick wins (<1 year).

- Medium-term opportunities (1 to 2 years).

- Long-term opportunities (>3 years).

Deliverables • Price variation analysis.

• Price waterfall analysis.

• Customer perceived value and price elasticity analysis.

• Price policy improvement opportunities by different customer segments and major products.

• Estimate of size of profitability opportunity.

• Process improvement opportunities.


Moving to the future state

Beyond the realization of immediate benefits, sustainability is key. If the strategy, process, and supporting pricing systems are not fundamentally changed, the benefits are eroded as the firm returns to business-as-usual.

Phase 2: Develop pricing strategy and future state operating model

Future state pricing strategy

Future state operations, organization alignment, data management and technology


Activities • Develop new pricing strategy based on multiple inputs, including strategic bank objectives, pricing analytics, customer price elasticity, and competitive information.

• Develop new pricing guidelines and policies.

• Develop future-state pricing requirements:

- Establish a common pricing strategy across organizational units.

- Institute pricing process controls and metrics to safeguard published margin requirements and manage risk.

- Develop decision-support and scenario analysis tools to determine product offerings and pricing.

- Develop/select pricing technology tools.

• Develop high-level implementation plan:

- Define the 90-day roadmap for implementation, including pilot milestones to test pricing strategy in market.

- Align sales incentives with pricing objectives.

- Prepare pricing training materials and courses.

• Define the ongoing monitoring processes and supporting KPIs.

• Develop tracking tools to both monitor potential margin leakages and unplanned variations and ensure compliance with agreed-upon pricing policies.

• Evaluate exception requests.

• Design performance improvement process.

Deliverables • Future state pricing strategy. • Future state pricing processes, organization, controls, pricing systems/tools, analytics.

• Change management plan.

• Continuous performance improvement and management process.

Our capabilities and tailored approach.

How PwC can help

25

What makes PwC’s Financial Services practice distinctive.

How PwC can help

Integrated global network With 34,000 industry-dedicated professionals worldwide, PwC has a network that enables the assembly of both cross-border and regional teams. PwC’s large, integrated global network of industry-dedicated resources means that PwC deploys the right personnel with the right background on our clients’ behalf whenever and wherever they need it.

Extensive industry experience PwC serves multinational financial institutions across banking and capital markets, insurance, the asset management/hedge fund/ private equity industry, payments and financial technology. As a result, PwC has the extensive experience needed to advise on the portfolio of business issues that affect the financial industry, and we apply that knowledge to our clients’ individual circumstances.

Multidisciplinary problem solving The critical issues that financial services companies face today affect their entire business. Addressing these complexities requires both breadth and depth, and PwC service teams include specialists in strategy, risk management, finance, regulation, and technology. This allows us to provide support to corporate executives as well as key line and staff management. We help address business issues from client impact to product design, from go-to-market strategy to operating practice, across all dimensions of the organization. We feel equally comfortable helping the heads of business and the heads of risk, finance, operations, and technology, and have helped clients solve problems that cross all of these areas.

Practical insight into critical issues In addition to working directly with clients, our practice professionals and Financial Services Institute (FSI) regularly produce client surveys, white papers, and points of view on the critical issues that face the industry. These publications—as well as the events we stage—provide clients with new intelligence, perspective, and analysis on the trends that affect them.

Focus on relationships PwC US helps organizations and individuals create the value they are looking for. We are a member of the PwC network of firms with 169,000 people in more than 158 countries. We are committed to delivering quality in assurance, tax, and advisory services.

26 FS Viewpoint

PwC’s tailored approach focuses on all aspects of pricing management.

PwC’s tailored approach focuses on all aspects of pricing management.

Transaction�andcustomer

pricing analytics

Pricingoperations

Organizationalalignment

Pricingstrategy

Data management& technology

Pricingcapabilities

• Developing the pricing strategy, based on analysis of corporate objectives, customer transactional behavior, market landscape, and brand.

• Providing insights into how to set and manage prices at the product level.

• Helping to identify and implement the technological tools necessary to make monitoring pricing performance routine and to automate advanced elasticity analytics.

• Building business requirements for pricing systems implementation, and providing support throughout the vendor selection process.

• Analyzing profitability across customer segments, product segments, and channels.

• Assessing the importance of pricing in the buying decision, and developing price elasticities for key products.

• Establishing a pricing waterfall across customers, products, and channels, and analyzing each pricing waterfall element to identify unnecessary discounting costs to address, and variations between customers, products, and channels.

• Supporting management in designing the pricing function and definition of roles and responsibilities.

• Providing workshops and training to help implement new pricing policies and procedures.

• Developing formal, standardized processes and controls across the pricing and business functions.

• Developing key pricing performance metrics, such as target price and net operating income (NOI), and tracking for continual performance monitoring.

27

PwC Advisory

How PwC can help

Clientneeds

Manage riskand regulation

Innovate and grow profitably

Build effectiveorganizations

Reducecosts

Leverage talent

We look across the entire organization—focusing on strategy, structure, people, process, and technology—to help our clients improve business processes, transform organizations, and implement technologies needed to run the business.

Client needs Issues we help clients address

Innovate and grow profitably

• Reshaping the IT function into a source of innovation

• Transforming business information to drive insight and fact-based decision making

• Evaluating acquisition and divestiture strategies to position for the future

Manage risk and regulation

• Building a risk resilient organization

• Managing ERP investment and project execution risk

• Safeguarding the currency of business; keeping sensitive data out of the wrong hands

• Ensuring capital project governance and accountability

Build effective organizations • Establishing effective strategic sourcing and procurement

• Realizing competitive advantage through effective sales operations inventory planning

• Transforming the close and consolidation process to work for you rather than against you

Reduce costs • Driving efficiency through shared services

• Redesigning finance to realize efficiency and competitive advantage

• Taking control of cost through effective spend management and cash forecasting practices

Leverage talent • Defining and implementing an effective HR organization

• Rethinking pivotal talent

Select qualifications.

Appendix

29Appendix—Select qualifications

Portfolio product design and pricing—Large retail bank

Issues The bank wanted to increase product penetration for its small-to-medium sized business customer base. Traditionally, product penetration was driven by relationship managers in the branches, which had not been very successful. The small-to-medium sized business customer base often had products with both the small business division and the personal consumer division, making it difficult for the bank employees to have a single view of the customer’s portfolio. The bank was seeking a product bundle recommendation to drive product penetration and revenue for this customer segment.

Approach PwC helped analyze the bank’s small-to-medium-sized business customer base and identified four key customer segments based on industry, product portfolio, and service usage pattern. The analysis also assessed price sensitivity across segments, identifying customer segments that were insensitive to price increases, were highly sensitive (creating higher attrition rates), and were sensitive to certain types of price increases (such as rate vs. fee).

Using customer analytics to further profile each segment, PwC assisted in evaluating each segment’s behaviors and needs for various product elements and premium services. PwC helped the client develop a collection of product/service bundles targeted at each customer segment.

Benefits The client was able to better understand the behaviors and needs of its small-to-medium-sized business customer base and designed more relevant product that had greater appeal to its customers. The projected revenue impact was more than $100 million across three years, based on increased adoption and more targeted pricing.

30 FS Viewpoint

Pricing analytics benchmarking— Large US insurer

Issues One of the largest US insurers sought to assess its pricing analytics capabilities against future business needs and best practices across P&C insurance carriers to uncover potential areas for improvement, particularly in the data and technology environments.

• As the client’s customer base was expanding outward from its core focus, the client wanted to ensure that the right levels of investment in people, processes, and technologies were in place to retain the desired level of sophistication in its pricing strategy.

• Lack of coordination between the business unit and IT resulted in duplicative technology effort and sub-optimal integration solutions.

• Lack of automated integration resulted in manual effort by the business unit to support processes due to long lead times and IT’s high costs for transactions.

Approach Next, PwC assisted the client in evaluating the data and technology environments and developing a three-year roadmap to achieve the desired future state.

Benefits The successful conclusion of this engagement marked the beginning of a multi-year path toward transforming the technology environment to better support the overall pricing strategy, organization, and processes.


Multi-tiered pricing strategy design—Leading wholesale payments clearinghouse

Issues The client operated in a market where little product differentiation and high variable costs were adversely impacting margins and market share. At the same time, the client was experiencing the following issues:

• There was increased pressure to lower prices due to competitors’ pricing strategies and negotiated pricing discounts from owner banks.

• Unit cost declines that were not keeping pace with volume increases across each of the three fixed cost infrastructure payment platforms; low marginal cost of volume increases that were not being taken advantage of.

• Approximately 70% of volume driven by the top 10 players, who were collectively generating a surplus of capacity.

• Because of limited visibility into its clients’ needs and preferences, our client was unable to test new pricing models.

Approach PwC worked with the client’s CFO and CEO to design a multi-tiered pricing strategy across multiple product lines. The team established quantitative measures of price sensitivity through customer intelligence, behavioral economics, and pricing data analytics.

PwC helped the client identify volume growth potential through customer segmentation, price sensitivity, and market share analyses.

Benefits The client gained enhanced visibility into its competitors’ cost structure. In addition, detailed financial modeling tools enabled the client to respond more quickly and effectively to its competitors’ price changes. PwC’s pricing recommendations were estimated to potentially increase top line revenues by an average of 6% and net surplus by an average of approximately 25% across each of the product lines.

32 FS Viewpoint

Deposit price analysis— Big 5 Canadian bank*

Issues The client, a large Canadian bank, sought to implement improved deposit pricing practices in its commercial segment. Pricing decisions were highly decentralized, with relationship teams that were able to individually price customers within broad guidelines set by product management. The objective of the assessment was to test how effectively the relationship teams had priced deposit accounts relative to customer elasticity.

Approach PwC assisted the client by supporting several activities:

• Modeled price-elasticity curves based on account-level analysis of all business customers, segmented by multiple factors including company size, region, industry, product usage, and balance tier.

• Assessed rate positioning relative to theoretically optimal rate points on the elasticity curves.

• Tested field discipline in following pricing guidelines by analyzing account attributes, validating that account executives frequently priced outside of guidelines and failed to perform re-pricing reviews.

• Performed an FTP diagnostic to assess how effectively the framework matched typical deposit behavior in business segments.

• Based on the analysis, recommended pricing strategies for each product to move rate positioning closer to the optimal rate-balance point. The recommended pricing strategies ranged from downward re-pricing in certain segments and products to the introduction of premium-rate small business accounts.

• Recommended a new administered-rate product for large customers, which is expected to generate significant volumes through a rate enhancement while receiving more favorable FTP treatment.

• Recommended rate governance enhancements to centralize deposit pricing in product management.

Benefits Following PwC’s analysis, the product management team at the client validated our findings with the relationship teams and reached a cross-functional consensus within the bank: more than CAD $30 million improvement in margin was achievable through re-pricing of accounts and strengthened pricing controls.

* Led by a PwC team member at a previous firm.


Treasury management pricing—Large regional bank

Issues The client, the bank’s global transaction banking division, was concerned that its treasury management pricing was putting the bank at a competitive disadvantage:

• Excessive complexity due to the maintenance of more than 600 transaction pricing codes in the account analysis system.

• Feedback from treasury management sales officers who reported that standard price schedules were not competitive with the schedules of their peers.

• Pervasive discounting, with insufficient resources in product management to ensure that only appropriate pricing concessions were occurring.

Approach The PwC team began by helping the client perform a data analysis based on a time series of account analysis extract files. Each transaction code was mapped to standard AFP codes. The actual pricing of each code was then examined to understand the level of discounting relative to standard and whether natural breakpoints were visible in the pricing, i.e., volume points beyond which a lower agreed-upon price was the norm.

In addition, the PwC team helped perform a competitive analysis by comparing the mapped bank service codes to price points of peer banks obtained in similar engagements.

The team also supported the client by performing an elasticity analysis, comparing the level of discounting of each service code relative to a five-level assignment of price sensitivity to ascertain to the extent of discounting correlated with price sensitivity. The transaction code structure was examined for opportunities to collapse the existing set to a more manageable structure.

The transaction code structure was examined for opportunities to collapse the existing set to be more manageable.

Benefits The client was able to implement a number of pricing enhancements based on the study. By establishing volume tiering for key transaction codes, the bank was able to build more flexibility into the pricing structure and reduce discounting requirements. In addition, the team identified more than $25 million of annual savings by eliminating discounts on non-price sensitive and penalty transaction codes as well as standard price increases. Finally, the project served as a blueprint for restructuring and simplifying the transaction code structure.

34 FS Viewpoint

Developing a new card strategy using risk and behavioral price modeling—Top five global bank

Issues The client sought to redefine its existing pricing model with the objectives of improving existing lending and borrowing approaches. As a result of the new credit environment–markedly changed by the financial crisis and ensuing regulatory changes–the client was struggling to differentiate itself from the competition.

The client engaged PwC to understand how it could use new, more dynamic, verifiable, real-time data sources, such as bank and credit card information, to revolutionize its product development capabilities and develop a risk-based pricing model.

Approach PwC created a detailed 18-month roadmap, a supporting business case, and an innovative pricing strategy to offer better margins and innovative means for the client to win new customer segments.

PwC convened a multidisciplinary team of subject matter experts with applied backgrounds in statistics, actuarial sciences, and emerging modeling disciplines to develop an analytic model that used new sources of customer data to increase predictive value. The PwC team combined behavioral economics design techniques with risk-based pricing techniques to adjust customer risk profiles based on demonstrated good behaviors over time. The new model required the bank to not only extend credit, but also to embed methods to prevent the customer from becoming a bad credit user (such as triggers, stop gaps, value sweeteners, and additional fees).

Benefits PwC introduced behavioral economics techniques to all aspects of the lending and borrowing environment, creating a new way for both the issuer and cardholder to succeed. Behavioral profiles were developed for certain customer segments to identify market opportunity by shifting the focus from short-term share-of-wallet to longer-term value.

The new model provided the client with techniques to influence customer risk behaviors and increase customer lifetime value. As result, the client developed a new card business worth several million dollars.

“The Price of Success: Aligning Pricing with the Customer Value Proposition,” PwC FS Viewpoint, March 2012, www.pwc.com/fsi

© 2012 PricewaterhouseCoopers LLP, a Delaware limited liability partnership. All rights reserved. PwC refers to the US member firm, and may sometimes refer to the PwC network. Each member firm is a separate legal entity. Please see www.pwc.com/structure for further details. This content is for general information purposes only, and should not be used as a substitute for consultation with professional advisors.

LA-12-0174 Viewpoint Pricing

www.pwc.com /fsi

To have a deeper conversation, please contact:

John Garvey [email protected] +1 646 471 2422

Daniel Jackett [email protected] +1 415 498 7559

Nathaniel Fisher [email protected] +1 858 677 2539

Kathryn Wherry [email protected] +1 415 498 7359

Stephen Baird [email protected] +1 312 298 6027

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