equifax confidential and proprietary understanding credit scores customer tutorial

15
Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Upload: erick-biron

Post on 29-Mar-2015

231 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary

Understanding Credit ScoresUnderstanding Credit ScoresCustomer Tutorial

Page 2: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 2

Important Legal NoteImportant Legal Note

The information in this presentation is not to be relied upon, is not intended to be, nor should it be used or construed as, legal advice. Equifax assumes no liability for any errors or omissions in the information in this presentation. Compliance with the Fair Credit Reporting Act (FCRA), the Equal Credit Opportunity Act (ECOA) or their respective regulations is the responsibility of each entity to which such laws apply. All specific consumer, customer and other third-party information in this presentation is fictitious.

This presentation contains Equifax proprietary and confidential information. Do not distribute or copy.

Page 3: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 3

What is Credit Scoring?What is Credit Scoring?

The application of statistical methods to credit data with the intent of predicting the likelihood of some credit-related event taking place.

Makes use of credit history information

Developed using “analytically derived, demonstrably and statistically sound” statistical techniques

A credit score does not tell how an individual will act. Rather, it tells the probability or likelihood that the individual will act a certain way.

Page 4: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 4

Developing a Scoring ModelDeveloping a Scoring Model

Commonly used terms

An Attribute (aka “Characteristic” or “Variable”)is an aspect of an individual’s credit history. Some examples might be “Age of Oldest Trade” or “Utilization Rate on Open Bankcard Trades”.

A Bad Definition is what the model is developed to predict. A common bad definition for the Financial industry is “90+ Days Past Due”; common bad definitions for the Telecommunication industry are “No Pay”, “Involuntary Disconnect” or “60+ Days Past Due”.

Page 5: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 5

Developing a Scoring Model (continued)Developing a Scoring Model (continued)

Commonly used terms

A Performance Period is the time period for which the bad definition applies. Financial industry scorecards are designed to predict the likelihood of some event occurring over the next 12-24 months. Telecommunication industry scorecards have a performance window of 6-12 months.

The Observation Point is the point from which the model development data was taken. It is the starting point of the Performance Period.

A Bad Rate is the percentage of accounts that meet the “bad definition” within a certain score range. Typically, bad rates are quoted as “interval” or “cumulative” bad rates.

Page 6: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 6

Model DevelopmentModel Development

Utilizes historical information to predict futureevents and outcomes

PredictiveModel

ObservationPoint

90+ Days Past DueNo Pay

Prediction Time FramePerformance Window

Independent Variables Dependent Variable

Credit Attributes

HistoricalInformation

Page 7: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 7

Developing a Scoring ModelDeveloping a Scoring Model

General scoring model factors

Payment HistoryHas there been delinquency in the recent or historical past?

Amount OwedWhat are the aggregate balances? How high is the credit utilization (balances as a percent of available credit)?

Length of Credit HistoryThis is a proxy for stability – longer history equates to stability and often more credit information.

Page 8: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 8

Developing a Scoring Model (continued)Developing a Scoring Model (continued)

General scoring model factors

New CreditHas the consumer escalated their use of credit?

Types of Credit in UseDoes the consumer have a healthy mix of credit devices?

Public RecordsPublicly available information related to bankruptcies, judgments and liens.

Page 9: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 9

Developing a Scoring Model (continued)Developing a Scoring Model (continued)

Variable (aka “Characteristic” or “Attribute”) Value Range Points Constant 500 Revolving Utilization 0-30%

31-60% 61+

41 8

-21 Average Age of Credit File (in months) <6

7-12 13-20 21+

-18 0 12 30

Worst Credit Rating Current 30-59 60-89 90+

5 -10 -30 -57

Number of Open Accounts <2 2-4 5+

-18 9 19

Percent of Trades that are Satisfactory <80% 81+%

-31 9

Presence of a Public Record Item? Yes No

-31 3

Number of Inquiries 0-1 2 3+

12 3

-10 Bankcard Balance <$2,000

$2,000-$5,000 >$5,000

7 5

-12

An example scorecard (for illustrative purposes only)

Page 10: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 10

What Factors Affect a Score?What Factors Affect a Score?

Payment HistoryA record of late payments on current and past credit accounts may lower the score.

Public RecordsMatters of public record such as bankruptcies, judgments, and lien items may lower the score.

Amount OwedOwing too much may lower the score, especially if the accounts are approaching the total credit limit.

Page 11: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 11

What Factors Affect a Score? (continued)What Factors Affect a Score? (continued)

Length of Credit HistoryIn general, a credit history that dates back for a longer period of time is better.

New AccountsOpening multiple new accounts in a short period of time may lower the score.

Page 12: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 12

What Factors Affect a Score? (continued)What Factors Affect a Score? (continued)

InquiriesWhenever someone else, i.e. a lender, gets a credit report an inquiry is recorded on that credit report. A large number of recent inquiries may lower the score.

Open AccountsThe presence of too many open accounts can lower the score, regardless of whether the accounts are being used or not. However, closing accounts will likely cause the utilization rate to go up which may lower the score.

Page 13: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 13

Performance ChartsPerformance Charts

A gains chart is a tool used to obtain an overall view of how a particular score performs on a specific population. Generally speaking, the population is rank ordered from the lowest risk (top) to the highest risk accounts (bottom), and is then separated into equal-sized groups.

Gains charts can be used in a variety of ways and here is an example of information that a risk model gains chart can provide:

Isolating high-risk accounts in the low level score ranges. When using risk models, this information is useful to clients who are looking to reduce their overall portfolio delinquency rate. By referencing the “Decum % of bads” column, the client is able to determine which score ranges capture the most amount of bad accounts in their portfolio. (The higher the number, the higher percentage of bads that are isolated at or below a particular score range.) This information can then be used to drive their acquisition strategy by allowing the client to determine which customers they wish to add to their existing customer base.

0

10

20

30

40

50

60

70

80

90

100

260 300 348 400 450 500 550 600 650 700 750 799 850 899 992

cum

mula

tive p

op

ula

tio

n %

Score

Accounts Eliminated

Cumulative Population

Cut off score

Page 14: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 14

Gains Chart Explanation Gains Chart Explanation

Percent of Goods: A calculation that divides the summation of good accounts by the total good population. For example, 11.86% = 23,775 / 200,533.

Decum % of Bads: A calculation that divides the summation of bad accounts by the total bad population. For example, 43.58% = 21,239 / 48,741. Note: Calculations for this number starts from the bottom score range and filters to the top.

Interval Bad Rate: A calculation that divides the number of bads by the population within that interval. For example, in the upper most decile the interval bad rate of 1.16 = 280 / 24,055.

Cumulative Bad Rate: A calculation that divides the summation of bad accounts by the summation of total of accounts. For example, 2.36 = (280+847) / (24,055 + 23,746).

Min / Max Score: The minimum and maximum score ranges within that specific percentile.

Total Accounts: The number of accounts present in the portfolio.

Goods: The population of accounts the customer is targeting to keep (e.g., paid accounts).

Bads: The population of accounts the customer is targeting to eliminate (e.g., non-payers or 90+DPD).

Min Score

Max Score

Total # of Accts

% of Total

Number of Goods

Percent of

GoodsNumber of

BadsPercent of Bads

De-Cum # of Bads

De-Cum % of Bads

Interval Bad Rate

Cum Bad Rate

De-Cum Bad Rate

751 - 830 24,055 9.65% 23,775 11.86% 280 0.57% 48,741 100.00% 1.16% 1.16% 19.55%716 - 750 23,746 9.53% 22,899 11.42% 847 1.74% 48,461 99.43% 3.57% 2.36% 21.52%687 - 715 24,331 9.76% 22,325 11.13% 2,006 4.12% 47,614 97.69% 8.24% 4.34% 23.63%664 - 686 24,400 9.79% 21,296 10.62% 3,104 6.37% 45,608 93.57% 12.72% 6.46% 25.75%646 - 663 23,584 9.46% 19,802 9.87% 3,782 7.76% 42,504 87.20% 16.04% 8.34% 27.83%629 - 645 24,032 9.64% 19,120 9.53% 4,912 10.08% 38,722 79.44% 20.44% 10.36% 29.98%611 - 628 24,466 9.81% 18,629 9.29% 5,837 11.98% 33,810 69.37% 23.86% 12.32% 32.16%589 - 610 24,375 9.78% 17,641 8.80% 6,734 13.82% 27,973 57.39% 27.63% 14.25% 34.68%559 - 588 23,814 9.55% 15,855 7.91% 7,959 16.33% 21,239 43.58% 33.42% 16.36% 37.73%420 - 558 24,683 9.90% 13,269 6.62% 11,414 23.42% 13,280 27.25% 46.24% 19.41% 40.90%

7,788 3.12% 5,922 2.95% 1,866 3.83% 1,866 3.83% 23.96% 19.55% 23.96%249,274 100% 200,533 100% 48,741 100.00%

Missing or Default

Page 15: Equifax Confidential and Proprietary Understanding Credit Scores Customer Tutorial

Equifax Confidential and Proprietary 15

Dual Score Matrix- Risk StrategyDual Score Matrix- Risk Strategy

A dual score matrix offers further risk segmentation. Risk based product offers can be set within each one of the risk segments based on combinations of the General Risk Score and Bankruptcy Navigator Index 3.0 score’s value.

Default751 - 716 - 687 - 664 - 646 - 629 - 611 - 589 - 559 - 420 - Missing or830 750 715 686 663 645 628 610 588 558 Default Value1 2 3 4 5 6 7 8 9 10 10

Low 13,940 5,745 2,734 1,249 559 315 161 90 45 25 46 24,909 Risk 5.6% 2.3% 1.1% 0.5% 0.2% 0.1% 0.1% 0.0% 0.0% 0.0% 0.0% 10.0%

0.7% 1.3% 2.0% 2.9% 3.0% 3.8% 7.5% 4.4% 13.3% 0.0% 4.3% 1.2%

6,597 6,543 4,368 2,947 1,690 1,091 653 467 215 97 258 24,926 2.6% 2.6% 1.8% 1.2% 0.7% 0.4% 0.3% 0.2% 0.1% 0.0% 0.1% 10.0%1.2% 2.5% 3.3% 4.0% 4.2% 4.3% 5.8% 5.1% 7.4% 18.6% 5.0% 2.9%

2,501 5,281 4,754 3,723 2,518 2,035 1,445 876 571 291 610 24,605 1.0% 2.1% 1.9% 1.5% 1.0% 0.8% 0.6% 0.4% 0.2% 0.1% 0.2% 9.9%2.8% 3.8% 5.6% 6.8% 6.4% 8.5% 6.6% 6.6% 11.7% 10.7% 11.8% 5.9%

712 3,226 4,487 3,991 3,422 2,746 2,169 1,545 933 500 1,332 25,063 0.3% 1.3% 1.8% 1.6% 1.4% 1.1% 0.9% 0.6% 0.4% 0.2% 0.5% 10.1%2.5% 5.1% 8.6% 10.2% 11.2% 9.6% 10.7% 11.6% 14.4% 13.8% 15.8% 9.8%

203 1,681 3,572 4,047 3,738 3,225 2,720 2,122 1,624 843 1,091 24,866 0.1% 0.7% 1.4% 1.6% 1.5% 1.3% 1.1% 0.9% 0.7% 0.3% 0.4% 10.0%5.9% 6.7% 12.5% 12.5% 11.9% 14.3% 14.7% 15.2% 15.5% 23.0% 17.9% 13.4%

68 776 2,252 3,349 3,755 3,674 3,172 3,026 2,221 1,322 1,171 24,786 0.0% 0.3% 0.9% 1.3% 1.5% 1.5% 1.3% 1.2% 0.9% 0.5% 0.5% 9.9%

10.3% 9.5% 13.1% 15.1% 16.0% 18.2% 17.1% 17.7% 21.5% 21.8% 19.9% 17.1%

24 338 1,234 2,532 3,294 3,646 4,059 3,708 3,157 2,127 856 24,975 0.0% 0.1% 0.5% 1.0% 1.3% 1.5% 1.6% 1.5% 1.3% 0.9% 0.3% 10.0%4.2% 10.4% 17.1% 20.3% 20.4% 20.1% 23.0% 22.8% 24.5% 32.3% 23.2% 22.5%

6 128 656 1,669 2,480 3,309 3,893 4,162 4,435 3,380 863 24,981 0.0% 0.1% 0.3% 0.7% 1.0% 1.3% 1.6% 1.7% 1.8% 1.4% 0.3% 10.0%0.0% 12.5% 16.8% 25.5% 25.2% 28.2% 25.2% 26.8% 31.7% 33.5% 30.7% 28.1%

4 25 223 709 1,567 2,602 3,648 4,563 5,174 5,591 873 24,979 0.0% 0.0% 0.1% 0.3% 0.6% 1.0% 1.5% 1.8% 2.1% 2.2% 0.4% 10.0%0.0% 36.0% 32.7% 34.8% 36.3% 35.1% 34.0% 37.3% 35.5% 44.3% 35.1% 37.5%

- 3 51 184 561 1,389 2,546 3,816 5,439 10,507 688 25,184 High 0.0% 0.0% 0.0% 0.1% 0.2% 0.6% 1.0% 1.5% 2.2% 4.2% 0.3% 10.1%Risk 0.0% 0.0% 37.3% 52.2% 43.3% 50.9% 53.4% 51.0% 55.0% 62.0% 53.8% 56.6%

24,055 23,746 24,331 24,400 23,584 24,032 24,466 24,375 23,814 24,683 7,788 249,274 9.7% 9.5% 9.8% 9.8% 9.5% 9.6% 9.8% 9.8% 9.6% 9.9% 3.1% 100.0%1.2% 3.6% 8.2% 12.7% 16.0% 20.4% 23.9% 27.6% 33.4% 46.2% 23.96% 19.6%

Total

D

E

F

G

H

I

J

BN

I 3

.0

C

380-432

346-379

TotalRange

A

High Risk DECLINEDGeneral Risk Score

Meduim Risk

187-225

137-186

low-136

Low Risk

318-345

290-317

261-289

226-260

B

433+

High Risk

Medium Risk

Low Risk