moody’s analytics

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Moody’s Analytics:

Practical Stress-Testing Issues and Implementation

December 4, 2013

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Agenda

1. Introductions

2. Regulatory Background

3. Common Analytical Challenges

4. Common Infrastructure Challenges

5. Summary


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Moody’s Analytics Story Begins with Broad and DeepInsight from Well-Respected Names

Credit Research &

Risk

Measurement

Enterprise Risk

Management

Structured

Analytics &

Valuation

Economic &

Consumer Credit

Analysis

Training &

Certification


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Stress-Testing Complexities

» The stress-testing exercise is one of the biggest challenges undertaken

by the industry and regulatory community – Impacts numerous business processes and functional areas

– Achieving “best-practice” remains a work in progress

» The national policy objective – increase the loss absorbing capacity ofbanks for:

– Losses under severe stress Higher capital, and higher quality capital

– Ensure a resilient pool of unencumbered liquidity to reduce over-reliance onthe “lender of last resort”

» The objective of the banks: Satisfy the regulators, but also ensure thatany firm infrastructure and/or reporting investments improve businessprocesses and create firm-value


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In a word: SEVERE

Actions that can be taken for poor CCAR data, analytics, and processes:

1. Inability to pay dividends

2. Prohibition from buying back stock (treasury stock repurchase programs)

3. Leverage limitations

4. Capital and liquidity surcharges

5. Prohibition on growth – organic and M&A

6. Fines

7. Informal and formal actions (e.g., WA, MOU, C&D, Capital Directive)

Failure can originate from poor processes, governance weaknesses, analytical,

infrastructure and reporting shortcomings. Most common causes (to date) are data and

infrastructure.

Consequences of Failure“I was being asked to attest to this. It isworse that SOX 404. I hired [CRO] to havehim sign it. I’m not signing this thing.”

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Summary

• To develop a firm-wide stress-testing framework, sponsorship and budget must be

allocated from the top of the organization. Governance is as important as results.

• Best practice starts with an assessment of current state and a roadmap for buildingfuture state automation of the business process and analytics. Good design isimperative.

• Realize: Future state will require re-tooling of existing business processes, data

governance, model risk management, system integration(s), and comprehensiveregulatory and management reporting capabilities.

• Firms need a lot of data (internal and external) to properly model losses (defaults andrecoveries) from the “bottom-up”. Bottom-up modeling may not always be preferred.

• Challenger models are a requirement given today’s model risk managementexpectations

• Pre-provision net revenue modeling (PPNR) with credit considerations is complex,particularly new business volume, spreads/rates, credit quality of new origination, andforecasted capital (i.e., RWAs)

• Infrastructure build requires a thoughtful way to integrate existing analytics and growand adapt to constantly changing requirements.

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Regulatory Background

2

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Effective Stress Tests Contain Five EssentialComponents

Tailored Multiple

Approaches

Forward

Looking and

Flexible

Meaningful

Results

Governance and

Control

» Regulators are forcing banks to acquire enhancedcapabilities in stress testing, capital planning andliquidity planning

» These exercises must be tailored to a bank’s

exposures, activities, and risks

» The process is forward-looking, modular, and flexible

» Results are to be clear, actionable, repeatable, wellsupported, and inform decision-making

» An organization’s testing framework should include

strong governance and effective internal controls

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Generically, “Stress Testing” is very broad

» Credit

» Interest Rate

» Market

» Liquidity

» Operational

Can be applied tovarious risk types

» Counterparty / Borrower /Facility

» Portfolio / Region / ProductLine / Cohort

» Enterprise / Legal Entity /Jurisdiction

Can be applied at manylevels

» Static – working withcurrent position data.Stock measures

» Dynamic – a “flow” conceptwith a time/forecast

dimension

Can be static ordynamic

» Top down

» Bottom up

» Hybrid

» Arbitrage free /Fundamental/Stochastic

Methodologies Diverge

» Risk based (EL, EC, VaR,downside risk/semivariance…)

» Accounting based(ALLL, OTTI, FVO, NII, netincome, DTA, RegulatoryCapital Ratios)

Results can beexpressed differently



DFAST / CCAR Stress Testing is far more specific

Conceptually very simple:

» Forecast of entire income statement and balance sheet

» Forecast is conditioned on specific economic scenario(s)

» Forecast considers pro-forma regulatory capital

» Quarterly for at least 9 (perhaps 13) quarters

» Focus on regulatory capital adequacy

» Incorporated into the capital planning process

But the devil is in the details:

» Stress testing requires unprecedented coordination betweenheretofore “siloed” risk and financial planning processes:

- Budgeting and planning

- Asset-liability management

- Credit risk

- Management and regulatory reporting

» Cross-border challenges (e.g., new PRA rules and emerging EBArules)

» Linkage to R&RP as well as liquidity risk requirements

» The primary inputs into the stress-testing framework are“conditional” loss estimates, synchronized PPNR calculations, ALLL(Charge-off and provision), and net income

- There is a non-trivial “work-flow” coordination that must existbetween the treasury, finance, risk, credit, and regulatoryreporting groups to achieve

- All stress testing must be integrated with capital planning, themain focus of the Federal Reserve and related supervisory

agencies

» Estimates of losses, revenues and expenses must all be“synchronized” with the same economic and market conditions

» Data, data-management, and risk and finance integration are keyelements of success or failure



Anatomy of a Stress Test – Data, Modeling, Reporting

Profit & Loss Forecast

+ Net Interest Income

+ Trading Revenues

+ Non Interest Income

-Non Interest Expense

+ Pre-Provision Net Revenues

- Charge-Offs

+ Recovery

Expected Net Charge-Offs (NCO)

-ALLL forecast

+/ - Net Revenues for non-banking

activities (asset mgmt, insurance,

etc.)

Taxes

Dividend Payout

+/- Accounting Adjustments

(effect of changing acct standards)

= Available Capital

Year 1

Q+1 Q+2 Q+3 Q+4

Profit & Loss Forecast

+ Net Interest Income

+ Trading Revenues

+ Non Interest Income

-Non Interest Expense

+ Pre-Provision Net Revenues

- Charge-Offs

+ Recovery

Expected Net Charge-Offs (NCO)

-ALLL forecast

+/ - Net Revenues for non-banking

activities (asset mgmt, insurance,

etc.)

Taxes

Dividend Payout

+/- Accounting Adjustments

(effect of changing acct standards)

= Available Capital

Year 2 + 1Q

Q+5 Q+6 Q+7 Q+8 Q+9

M

a c r o / R e g i o n a l E c o n o m

i c S c e n a r i o s

B u s i n e s s P l a n ( B a s i c / A d v a n c e d ) Capital Plan Adequacy

Under Stress

» Total and Average Assets

» RWA

» Total and Average Liabilities

» Capital(Regulatory and TCE)

» Interest Income / Expense

» Non-Interest Income /

Expense

» Dividends

» Treasury Stock and “Other”

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CCAR Process – Themes from RegulatorsFrom Regulatory Roundtable Hosted by Moody’s Analytics (D.C. 5/14/13)

» Stress testing process is as important as the results

– Process should be repeatable and auditable and should be part of the process of managing thebank. Regulators want to be able to trust the results of the stress test. Attestation is still a “future

state” possibility, and there is precedent.

– CCAR capital ratios AND rigor of processes are binding constraints on business strategy(MRAs have been often based on qualitative factors)

» Banks have been going from one short term fix to another. A longer term vision forinfrastructure that enables effective stress testing, capital planning, and enhanced

workflows is needed (e.g., “single point of entry/command and control”)

» There could be unintended consequences to Stress Testing

– Credit flow impact from ST could be more impactful than FOMC target rate changes (Fed Funds).Consider scenario velocity and the “speed” at which a firm approaches capital thresholds.

» Banks are allowed to use ‘vended’ models, but they need to: 1) know how the modelswork, 2) calibrate the model to the bank’s data and 3) be in control of changes to the

model. The vendors must have extensive documentation.

» Data infrastructure and system integration is a fundamental problem at most banks

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1. Done correctly, stress-testing is merely a special case of sound practice for risk

management, financial planning, and portfolio management. There is a need toachieve a “normal course of business” standing.

2. There must be an acknowledgement by senior bank management, and often the Board,that existing systems and processes are ill-suited to handle current expectations.In April of 2010, former Comptroller Dugan made this point at the Richmond FRB. Thisfact wasn’t, nor is it currently, fully appreciated. Feedback to banks seems to stop shortof driving the proper points home on needed integration points focusing rather onidiosyncratic details.

3. Until firms invest in and achieve a “closed-system” structure, banks will continue

to see stress-tests as a chore and compliance exercise, not as a way to bettermanage their firm and create increased business intelligence and improved clientinteractions. If the goal of the FRB is to improve safety and soundness through data-driven analytical capabilities, changes to the current process must be considered,starting with more effective guidance focused on promoting and enhancing businesspractices, automation, and analytical rigor.

CCAR Process – Industry Stress-Testing Themes

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Stress Testing Lessons from Aftermath of the Crisis:Observations from the Basel Committee

“Events of 2008-present in global financial markets clearly indicate the need for a more robust,flexible and forward-looking stress testing framework for credit portfolios”

“Senior management’s involvement is critical in ensuring appropriate use of stress testing inbank’s risk governance and capital planning. Banks that fared well in the crisis had seniormanagement take an active interest in the development of stress tests and making strategic

plans based on the results”

“Stress testing can no longer be isolated mechanical exercises by different business lines that are hard to interpret, non-cohesive and strategically non-actionable”

“In most instances, stress testing frameworks were not flexible enough to respond quicklyas the crises evolved . Frequent (e.g. quarterly) updating of scenarios is c ritical forunderstanding changing risk profile”

Basel Committee

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FRB Principle 2 for Designing and Implementing aStress Testing Framework Expects Banks to UseMultiple Approaches to Stress Testing

An effective stress testing framework employs multiple conceptually sound stress testing

activities and approaches

All measures of risk, including stress tests, have an element of uncertainty due to assumptions,

limitations, and other factors associated with using past performance measures and forward-

looking estimates. Banking organizations should, therefore, use multiple stress testing activitiesand approaches …, and ensure that each is conceptually sound. Stress tests usually vary in

design and complexity, including the number of factors employed and the degree of stress applied.

A banking organization should ensure that the complexity of any given test does not undermine its

integrity, usefulness, or clarity. In some cases, relatively simple tests can be very useful and

informative.

Furthermore, almost all stress tests, including well-developed quantitative tests supported by high-quality data, employ a certain amount of expert or business judgment, and the role and impact of

such judgment should be clearly documented.Interagency Guidance on Stress Testing for Banking Organizations

with Total Consolidated Assets of More Than $10Bn

SR Letter 12-7, May 14, 2012

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Common Analytical Challenges

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Common Challenges

• Data management and linkage to front-office origination systems

• Data “chain of custody” is becoming more important. Major data remediation efforts attimes required, as well as use of proxy data where possible. Fed handling of missingor suspect data.

• Many firms buying or building custom internal data-marts for specific use for stress-testing and reporting. Distinguishing features include….

• Reconciliation to GL, FRY14 schedules, FRY9C, and FFIEC 031/041

• Analytical challenges across loss estimation and PPNR

• Many banks attempting to use ALM models for balance forecasts

• Conditioning margin for non-accruals and linking NPA forecasts to scenarios

• Credit and regulatory capital conditioned new business volumes

• Non-interest income and expense models

• Analytical approach to volume and spread estimates (change in mix, not just level)

• Reporting accuracy and comprehensiveness

• Desire to have ability to prepare regulatory reports from one environment

• Ability to “drill-through” reports non-aggregated (or less aggregated) position details

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Example: Linkage to Front-Office and FRY14 Reporting

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Central Credit Concept: Assess Shocks and How They DynamicallyTransmit Risk to Capital and Earnings Over Time

• Decline in GDP

• Rise in unemployment

• Shift in yield curve

• Slowdown in home sales

Commercial

Counterparties

CASH FLOW STMT

INCOME STMT

BALANCE SHEET

AssetsCashReceivablesInventoriesPP&EIntangibles

LiabilitiesWC LinesPayablesOther Debt

Equity

Deterioration in credit

quality evidenced on

financial statements

Consumer

Counterparties

Deterioration in credit

quality evidenced in

reduced ability to repay

Collateral

Deterioration in value

evidenced in

depressed prices

• Bureau score

• Net worth

• Sources/stability of

income

• DTI, LTV, etc.

• Fair value

• Ability to seize

• Ability to liquefy

SHOCKS

CASH FLOW STMT

INCOME STMT

BALANCE SHEET

AssetsCashInvestmentsLoans(ALLL)OREO

LiabilitiesDepositsInterbankOther Debt

Capital

Old EL Old ULNew EL New UL

Obligor Facility

BBB B 3 6

Transmitted

PD and LGDincrease

Losses flow

through

income

statement

to capital

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Macroeconomics Matter… Models Should ConsiderBroader Trends, Feedback Loops, etc.


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But Local Economics Usually Matter Even More… Idiosyncratic Scenarios Stress Geographic, Industry,Counterparty, and Product Concentrations

2014Q1 Severely Adverse


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The Most Common Concern is Credit Losses Under Stress

Prototypical Credit Loss Stress Testing

Economic

Conditions

» Real GDP Growth

» Employment» Interest Rates

» Home Prices

» (Others)

Capital and

Liquidity Metrics

» Portfolio loss levels

» Impact to earnings» Impact to cash

» Implied risk-basedcapital ratios

Credit Quality

Metrics

» Quarterly expectedloss rates by

portfolio segment

Econometric

Models

Balance Sheet &

Income StatementModels

Economic Forecast

Assumptions

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To Begin, One Needs to Identify the Assets to Test

Commercial Real Estate

Commercial & Industrial

Home Equity

Credit Portfolio

Residential Mortgage

Other Consumer

Oil & Gas

Manufacturing

Transportation

Mezzanine

Owner Occupied

Services

Warehouse

Single Family

Other

Fixed Rate

Adjustable Rate (ARM)

Interest Only

Other

Construction

Multi-Family

Office

Retail

Alt-A

CRA

Other Mortgage

Direct Auto

Direct Deposit

Unsecured Loan

Second Lien Line

Unsecured PCL

Direct Other

First Lien Loan

Second Lien Loan

First Lien Line

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Many Balance Sheet Items can be “Stress Susceptible”

Example Breakdown of Non-Credit Assets & Liabilities

Derivatives

Securities

Off Balance Sheet

Other

Stress Susceptible

Assets & Liabilities

Physical Assets

Servicing Rights

US Treasuries

Agency MBS

Private Label CMOOther ABS / CDO

Municipal Securities

Miscellaneous / Equities

Other Futures & Options

Swaps

Caps & Floors

Rate Locks / Forwards

FX Options

Land

Buildings

Equipment

OREO

Standby L/Cs

Commitments

Non-Consolidated Interests

Other Notable A/L Deferred Tax Assets

Loans Held for Sale

TDRs

Goodwill / Intangibles

Pension Obligations

FDIC Assessments

Special Assets

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Our stress testing framework links macroeconomicfactors to credit risk measures – and charge offs

Scenario

Δ inExpected

Loss Δ i n 1 0 - y r

T r e a s u r y Y i e l d

Δ

i n 1 - y e a r F e d

F u n d s T a r g e t

Δ

i n C o r e G o o d s

C P I

Δ

i n C o n s u m e r

C o n f i d e n c e

Δ

i n S p e c G r a d e

S p r e a d s

Δ

i n N o n - F a r m

B i z P r o d u c t i v i t y

O t h e r s …

S1 ?

S2 ?S3 ?

S4 ?

S5 ?

Scenario

Conditions

External

Impacts

Internal

Impacts

Financial

Impacts

Capital

Impacts

Δ inProbabilityof Default Δ

i n 1 0 - y r

T r e a s u r y Y i e l d

Δ

i n C o r p o r a t e

T a x R a t e

Δ

i n 1 - y e a r F e d

F u n d s T a r g e t

Δ

i n C o r e G o o d s

C P I

Δ

i n W a g e s a n d

S a l a r i e s

Δ

i n C o n s u m e r

C o n f i d e n c e

Δ

i n S p e c G r a d e

S p r e a d s

Δ

i n N o n - F a r m

B i z P r o d u c t i v i t y

O t h e r s …

--- … … … … … … … … …

• The macroeconomic variables are drawn from those specified bythe Federal Reserve in CCAR process. Moody’s and the client will

jointly determine the macro-variables to be considered

• In advance of modeling, segmentation is performed forappropriate granularity (e.g., geography, industry, etc.)

• The PD, LGD, and EAD models are used to calculate the EL –

and translate those to charge-offs at the segment level

• The output will also be used to calculate rating transitions andfuture portfolio balances

HISTORICAL DATA PREDICTIONS

(Via regression model)

Independent “explanatory” variables

(macroeconomic factors) Regression modeled

Predictions Values of macrofactors from

forecast scenarios

ii

i

i X Factor ε β α +∆×+=∆ ∑ ]%[%

Our goal is to translate the relationship between scenario conditions and their impact

Dependent variables(credit risk measures,

such as PD)

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FOR ILLUSTRATION


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We compute expected losses under stressed scenariosby putting the PD, LGD and EAD models together

Stage 1:

Inputs

» Obligor PDs

» RiskCalc v4.0

» RG PD Mapping

» Sectors (NAICS)

» Debt Type

» Public/Private Flag

Stage 4:

Back-Testing

» Validation tests

forrepresentativene

ss, level, and

model

robustness

Stage 2:

Risk Factors

» Estimate

changes in PD,LGD, and EAD

based on macro

variable

forecasts

» Prior period PDsserve as the

starting state for

current period

PDs

» Expected loss =

PD*LGD*EAD

» Expected lossesdistributed over

future quarters

with loss timing

Stage 5:

Support

» Model review and

support

Stage 3:

Expected Loss

Documentation and

ImplementationPD Stress ResponseInitial PDs

RiskCalc v4.0 & RG

Mapping to PD

2014 C&I Moody’s Model – Collection ofmodels used for stress testing obligor PDs &

LGDs given the economic scenario.


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Combined Framework: Time Series Expected LossProjection (dollar value)

$-

$1,000,000

$2,000,000

$3,000,000

$4,000,000

$5,000,000

$6,000,000

$7,000,000

$8,000,000

$9,000,000

$10,000,000

D e c - 0

5

A p r - 0

6

A u g - 0

6

D e c - 0

6

A p r - 0

7

A u g - 0

7

D e c - 0

7

A p r - 0

8

A u g - 0

8

D e c - 0

8

A p r - 0

9

A u g - 0

9

D e c - 0

9

A p r - 1

0

A u g - 1

0

D e c - 1

0

A p r - 1

1

A u g - 1

1

D e c - 1

1

A p r - 1

2

A u g - 1

2

D e c - 1

2

A p r - 1

3

A u g - 1

3

D e c - 1

3

A p r - 1

4

A u g - 1

4

D e c - 1

4

A p r - 1

5

A u g - 1

5

D e c - 1

5

Severely Adverse Adverse

Base


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DFAST/CCAR: Stressed Projected C&I Loss Rates

Aggregate: 7.0% (MA) vs. 6.8% (Fed)

0

2

4

6

8

10

12

A l l y F i n a n c i a l

A m e r i c a n E x p r e s s

B a n k o f A m

e r i c a

B B & T

B N Y M

e l l o n

C a p i t a l O n e

C i t i g r o u p

F i f t h

T h i r d

G o l d m a n

J P M o r g a n C

h a s e

K e y c o r p

M o r g a n S t

a n l e y

P N C F i n a n c i a l

R e g i o n s F i n a n c i a l

S t a t e S

t r e e t

S u n

T r u s t

U . S . B a n c o r p

Fed MA Fed Aggregate MA Aggregate

Source: Board of Governors of the Federal Reserve; Moody’s Analytics

Notes: Not displayed is the Fed’s estimate of 49.8% for The Goldman Sachs Group.


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Baseline

Scenario 1:

Quicker

Recovery

Scenario 2:

Mild Second

Recession

Scenario 3:

Deeper Second

Recession

Scenario 4:

Depression

Scenario

CCAR/DFAST:

Severely

Adverse

Moody’s Analytics Has Asset Models for All Asset Classes

» Commercial Mortgages

» Income Producing

» Construction

» Fixed & Floating Rate

Commercial Real

EstateCommercial &

Industrial

» Public Companies

» Private Companies

Treasury & Asset

Management

» Non-Agency & AgencyRMBS

» ABS (credit cards,autos, student loans,etc)

» All Structured

Retail Banking

» Residential Mortgages,HELOCs

» Auto Loans & Leases» Credit Cards

» Equipment Leasing

CCAR/DFAST:

Adverse

CCAR/DFAST:

Baseline

Probability of Default | Loss Given Default | Exposure at Default Charge Offs

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Moody’s Analytics Improves Your PPNR Modeling

* Note that Interest Income less Interest Expense = Net Interest Income (NII)

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Net Interest Income* Modeling

» Develop or enhance portfolio balance,new origination volume, usage, andinterest charged on new loan models formultiple portfolios

» Provide or assist you with data collectionand handling, empirical research, custom

model development, validation andtesting, and training and documentation

» Seamlessly link models and scenarioswith simulated estimates of credit losses,income, and non-interest income andexpense

Non-Interest Income and Expense

Modeling

» Use your data, or supplement your dataset with data from Moody’s AnalyticsCredit Research Database – the largestfinancial statement and default databasein the world

» Modeling customized to your ownbusiness and experiences

» Statistically-derived benchmark forcomparison against expert-judgmentdriven approaches

» Identify statistical relationships betweenPPNR worksheet line items and economicvariables

» Moody’s Analytics approach is based onthe Federal Reserve approach.


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Pre-Provision Net Revenue Pain Points

1. Need unbiased estimates of new business volume and usage under stress. Challengerapproach to subjective forecasts. Helps improve the FP&A process.

2. Need to consider the credit composition of new business volume. In a Basel I world,this need not be complicated. New FRB rules for Basel 3 incorporation into pro-formastress-tests will present new challenges

3. Estimate deposit volumes under stress. Consider the impact of disintermediation.

Different approaches emerging. MA works with clients on design and implementation.Can also use more traditional and simplified approaches.

4. Can provide proper stress-test inputs to the firm’s existing ALM platform, includingscenario and market data inputs

5. Often will supply transition matrices to include in existing platforms for a variety of use,

including estimation of impacts to non-accrual levels within scenarios

6. If lacking in NII calculations, MA has can produce a full base-runoff and new businessNII calculation using RiskConfidence, MA’s proprietary ALM model

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Other Issues to Consider

» Other Real Estate Owned

» ALLL process and modeling

» Mortgage Servicing Rights, Loss and Recovery emergence

» FRB approach is not GAAP

» OTTI Calculations and Stress-Testing Structured Products

» FVO Calculations

» Municipal Securities

» Model Validation(s) and Documentation

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Common Infrastructure Challenges

4

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Stress Testing Affects the Balance Sheet:Multiple Business Practices are Impacted. Requirement: Integrate Processes

Stress-Testing

» Regulatory driven

» Internal use

- Regulatory ReportingInternal – Capital Planning

- PPNR

- Budgeting/Planning

- Profitability

- ICAAP

Budgeting / Plan» Capital planning

» New business mgt

» Scenario mgt

» Distributed; Use-test

- Non-interest income/expense

- Scenario Planning andMaintenance

- Volume, Rate, and CreditPlanning (distributed)

- Scenario dependent baserunoff

ALM/Treasury» PPNR

» Integration

» IRR/ALCO

» Discretionary books

- Credit adjusted NII

- Dynamic balance sheet andincome statement

- Accurate pro-forma regulatoryand economic capital

- Interest rate risk

- Economic and market valuation

- Liquidity risk

- Net income

Performance

Management» RAROC/ROCAS

» Risk Appetite Framework

» FTP/Profitability

Industry concerns:

• Improved operationalcontrol(s) throughautomation

• Auditability &Transparency

• Persistence

• Return on Investment

• Linkage to ERM

• Leverage existing spend

- Push-down through planningand budgeting

- Returns on capital before andafter stress

- Reverse stress-testing

- Risk Appetite Framework

- Profitability analysis

- Economic capital (fullintegration)

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Workflow (Steps) for DFAST/CCAR Exercise» While presented as a sequential workflow, this is not realistic or practical. Such a workflow must be

instantiated to work in an asynchronous fashion. Must deal in a robust fashion with numerous hand-

offs, edits checks, task schedules, and interactions.

Data Pull as ofSept-30

Fill-in “Missing”Data with ProxyData (inc. Tags)

Populate RequiredFields for FRY-

14M/Q

DocumentWorkflow, Version,and Audit the Data

Receive ScenariosExpand and

“Regionalize”Scenarios

Ensure Market Datais Consistent with

the ScenarioTailor Scenarios

CalculateConditional ELs

Across All Assets

DetermineBusiness Strategyin Each Scenario

Create ProperAssumption Input

for IntegratedPPNR

Calculate ExpectedNII/NIM and

Balance Sheet forEach Scenario

CalculatedExpected NIR and

NIE in EachScenario

Determine Charge-

Off and ALLL inEach Scenario

Assess and Apply

Other Losses,Including Ops Risk

CalculateAppropriate Pro-

Forma RegulatoryCapital

Populate RequiredRegulatory

Reporting Forms

Reconcile Reportsto FRY-9C and

Other Reporting

Assess andValidate Results

Apply Measures toCapital Plan

Data

Scenario

Design

Analytics

Reporting


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Stress-Testing and Capital Planning

» August 19, 2013, the FRS issued a report entitled, “Capital Planning at Large Bank HoldingCompanies: Supervisory Expectations and Range of Current Practice.”

» While the requirements for smaller banks, those between $10 and $50 billion, are lessonerous (see FR Vol 78, No 150, 8/5/2013) for the initial submission (i.e., March 2014), theunderlying principles are important for all firms. FRB approaches appear to lead globalpractices, although recent BOE guidance has interesting nuances that may turn out to bean improvement.

» One key lesson learned is that firms:

“…failed to adequately identify the potential exposures and risks stemming from

their firm-wide activities” and that one of the key weaknesses was the inability of

firms to simulate risks exposures, across the enterprise, in a comprehensive and

integrated fashion.”

» If one looks at the specification of the stress-test and Capital Plan Rule with an objective

eye, it fits all the details of a “3-tier” platform design, something the FRB is ostensiblyworking toward internally. Implications?

» Conclusion: A significant amount of work on data, analytics, and integrated risk, finance,and management reporting is required in order to create a repeatable, sustainable, andtransparent stress-testing and capital planning process. What does that work-flow entail?


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MA’s Stress-Testing FrameworkModular, Flexible and Comprehensive (Idea: Straight Through Processes)

Spreading SystemRiskAnalyst / RiskOrigins

Core Systems(e.g. GL, Loan Accounting)

RiskFoundation Datamart (Risk/Finance/Regulatory Structures)

D A T A L A Y E R

R E C O N C I L I A T I O N

- RiskFoundation Datamart as an integrated risk andfinance data layer is the foundation for stress testing

- RiskFoundation can be integrated with various datasources, including enterprise data warehouses and corebanking systems

- This platform layer is used for Dodd-Frank-mandatedreporting (e.g. CCAR stress testing), Basel II and II I

- Our solution design accommodates comprehensive regulatory

reporting, internal risk and LOB reporting, plus dimension /hierarchy management:

- Executive and board-level reporting

- Instantiation of the organization’s Risk Appetite Framework(s)

- Existing and expected liquidity risk reporting

- Drill-through and scenario dependent PPNR, balance sheet, new businessvolume

- Comprehensive wholesale and retail credit portfolio reporting

ManagementReporting

R E P O R T I N G

RegulatoryReporting

- Part of Moody’s Solution

- Bank’s Internal / Third Party Systems

- Moody’s is able to work within existing analytical layer tocoordinate, enhance and improve risk transparency

- By linking results from point solutions to the reporting layer(RiskFoundation), Moody’s can empower the bank byproviding key linkage between input data and outputresults.Risk Management

and ALM Systems

Credit Models

(Wholesale, Retail,Investment)

Budgeting &Planning Systems A N

A L Y T I C A N D B P M L A Y E R

R I S K R E P O R T I N G

NCOs ALLL PPNR

ScenarioAnalyzer

RWA

RiskAuthority

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Capital Planning

Performance Assessment


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“Book-End” Strategy

Through numerous engagements, we observed a need to “bracket” the data layer and the

workflow control mechanism (i.e., command and control layer/SPE)

• Current spreadsheet-based environments, while flexible, may not provide forrequired long-term sustainability, transparency, and auditability

We recognize that pre-existing systems that are part of the stress-testing workflow need tobe mapped to a defined business process, although a critical re-think of overall system

design - from customer points of interaction to back office risk assessment - needsadjustment

Internal and third-party models are part of most engagements but the process of sharingrequired inputs, assumptions, and outputs can be difficult.

Thankfully, third-party vendor management requirements are increasing in importance asan integral part of the risk management discipline. This is important for mission critical

work such as stress-testing, capital and liquidity risk planning

RiskFoundation and ScenarioAnalyzer form the “bookends” upon which a bank canarchitect a fully-automated stress-testing platform that will be managed and controlled in acentralized fashion.

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RiskFoundationTM – Cornerstone of Moody’s AnalyticsStress Testing Solution for Banks

» Infrastructure for a world-class riskmanagement system

» Regulatory compliance

» Benefits:

– Integrated view of risk

– User workspaces

– Shared components, includinganalytics (e.g., RiskOrigins)

– Common, scalable infrastructure

– Implementation and system

maintenance efficiencies – Common user experience

– Data governance

– Data persistence and versioning(chain of custody concepts)

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ScenarioAnalyzer TM: A Tool for On-Going Balance SheetForecasting and Strategic Planning

• ScenarioAnalyzer TM provides an unique, single platform to managescenarios, control all required models, create proper workflow(s),allow for MRM, perform sensitivity analysis, aggregate and managerequired data, allow for back-testing and benchmarking.

What is it?

• Address regulatory requirements and produce frequent reportsoutlining changes in portfolios thus providing a holistic view of theinstitutions’ risks, incomes, expenses, efficiency, and financialmetrics. Integrated with front-office risk origination platform(s)

Balance Sheet IntegratedView

•Facilitate the development, integration, validation, standardization, andmaintenance of custom models and scenarios. Integrate with FP&A and ALM at the cash-flow level allowing for the management and orchestration ofnumerous hierarchies. Permit on-demand aggregations and reconcilement.

Highly CustomizableSoftware

• Allows institutions to address stress testing requirements using adedicated, centralized platform across asset classes and portfolios.

Fully consistent with Basel-3 liquidity risk rules: LCR and NSFR

Liquidity Stress Testing

Capabilities

• Designed with an open architecture so institutions can add third-party software, use it with other bank systems and evolve theenterprise risk platform over time as the institutions’ grow

Scalable & OpenArchitecture

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ScenarioAnalyzer TM Combines Customized ScenariosWith the Institution’s Balance SheetActs as the Controller for Models and Data, and Provides Workflow and Required FRY14/Y9C Reporting

•Gap Analysis• Interviewing Process

•Strategic Roadmap•Expert Guidance•Findings &Recommendations

1: Qualitative Assessment

•Custom Scenario Definition•Methodologies•Balance Sheet Analysis•Sensitivity Analysis•Financial MetricsPerformance

•Behavioral Models

2: Quantitative Analysis •ScenarioAnalyzer TM

•Training & Workshops

•Reporting•Data Consolidation

3: Platform &Infrastructure

Translation engines apply the scenarios and business strategy to the

balance sheet to analyze the funding model

Formula engines can formulate any desired funding model and/orgrowth strategy

Stress testing capabilities are used to reflect future macroeconomicconditions that should be consider when defining the institutions’ riskappetite and perform sensitivity analysis

Drill down capabilities allow to allocate funding and liquidity costs bybusiness units, geographies, and products

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Moody’s Analytics Economic and Consumer CreditAnalytics (ECCA)

About ECCA» 70+ economists, more than 40% of which

have PhD’s

» 20+ data specialists

» Located around the globe in London,

Prague, Sydney and West Chester

» Leadership:

– Mark Zandi, Chief Economist

– Petr Zemcik, European Chief Economist

– Juan Licari, Sr. Director Consumer Credit Analytics

Stress Testing Services» Adapt Fed stress testing scenarios to your

markets through use of our extensive database ofeconomic, financial and demographic data –more than 260 million time series covering 200+countries and 600+ cities

» Forecast alternative macroeconomicscenarios globally for stress testing and riskmanagement

» Forecast and stress test consumer creditportfolios with customized models

» Provide the highest frequency and most up-to-

date outlook with monthly updated forecasts ofnational and regional economies

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44


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Stronger Near-Term ReboundS1

S2 Mild Second Recession

S3 Deeper Second Recession

Protracted SlumpS4

Baseline / Most LikelyBL

Standard

Below Trend Long Term GrowthS5

Oil Price ShockS6

Fed BaselineFB

Fed Adverse ScenarioFA

EBA BaselineEB

EBA Adverse ScenarioES

Regulatory Driven

FSA AnchorFSA

Fed Severely AdverseFS

Moody’s Analytics – Macroeconomic Scenarios

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RiskOriginsTM: Modular Workflow-Driven Platform forLinking Front-Office to the Risk and Finance Users forImproved Data Capture and Reporting

» Standardize processes with straight-through processing

– Reduce redundancies and mistakes

– Achieve regulatory compliance

– Improve profitability

– Win more deals that reflect risk tolerance

– Improve customer satisfaction

» RiskAnalyst is “consumed” by RO

– Spreading & scoring

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RiskAuthorityTM is an End-to-End Modular Solution toManage Basel I, Basel II, and Basel III Pillars WhileAccounting for 55 Jurisdictional Differences in Capital

and Liquidity Requirements

M o d u l a r •Liquidity Compliance

•Liquidity Monitoring• ALM•Credit Risk•Market Risk•Concentration Risk•Operational Risk•Grid Computing•Scenario Analyzer•Regulatory Reporting

C o m p r

e h e n s i v e a n d G l o b a l

•Standardized, IRBFoundation and

Advanced• All products and assetclasses supported

•Liquidity Coverage Ratio•Net Stable FundingRatio

•Liquidity gap•Maturity mismatch•Concentration of

Funding•Market Risk•Operational Risk•EL Provisioning Tool(IFRS 9 Impairments)

C o n f i g u r a b l e b

y S u p e r v i s o r o r R i s k •Supports over 55

supervisors•More than 2,000 build-inregulatory reports

•Basel I, II or III•Credit (standard,foundation andadvanced)

•Market (standard)•Operational (standard)•Liquidity Risk

F u l l y A u d i t a b l e •Dashboard reporting to

visualize results• Interface to quicklyanalyze results

•Maintains results historyfor trend analysis

• Audit regulatory reports• Audit calculation resultsand rules applied

RiskFoundation TM

RiskAuthorityTM

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Summary

• To develop a firm-wide stress-testing framework, sponsorship and budget must be

allocated from the top of the organization• Best practice starts with an assessment of current state and a roadmap for building

future state automation of the business process. Good design is imperative.

• Realize: Future state will require re-tooling of existing business processes, datagovernance, model risk management, system integration(s), and comprehensiveregulatory and management reporting capabilities.

• Firms need a lot of data (internal and external) to properly model losses (defaults andrecoveries) from the “bottom-up”. Bottom-up modeling may not always be preferred.

• Challenger models are a requirement given today’s model risk managementexpectations

• Pre-provision net revenue modeling (PPNR) with credit considerations is complex,particularly new business volume, spreads/rates, credit quality of new origination, andforecasted capital (i.e., RWAs)

• Infrastructure build requires a thoughtful way to integrate existing analytics and growand adapt to constantly changing requirements.

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Find out more about our award-winning solutions

www.moodysanalytics.com

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http://www.moodysanalytics.com/http://www.moodysanalytics.com/


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www.moodysanalytics.comUnited States7 World Trade Center250 Greenwich StreetNew York, NY 10007+1.646.283.8261

121 North Walnut StreetSuite 500

West Chester PA 19380+1.610.235.5299

AustraliaLevel 101 O'Connell StreetSydney, NSW, 2000

Australia+61.2.9270.8111

United KingdomOne Canada SquareCanary WharfLondon E14 5FA+44.20.7772.5454

PragueWashingtonova 17

110 00 Prague 1Czech Republic+420.22.422.2929

49

Thomas Day

Senior Director, [email protected]

mailto:[email protected]:[email protected]


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moodysanalytics.com

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