© 2014 Fair Isaac Corporation. Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent. Alternative Credit Data and FICO ® Score Fundamentals Ankush Tewari Director Credit Risk Decisioning LexisNexis David Shellenberger Senior Director Scoring and Advanced Analytics FICO

Agenda © 2014 Fair Isaac Corporation. Confidential. ► Alternative Credit Data ► Assessing Data Partners ► Combined Score Strategy Fundamentals 2

© 2014 Fair Isaac Corporation. Confidential. Using Alternative Data What should I consider when assessing the value of alternative credit data? 3

© 2014 Fair Isaac Corporation. Confidential. Alternative Credit Data 4

© 2014 Fair Isaac Corporation. Confidential. ► Addressing unscoreable population ► Young adults ► New immigrants ► Underbanked ► Augmenting available credit data ► Reduce manual underwriting burden Why Use Alternative Credit Data? 5 …And book more loans at an appropriate price!

© 2014 Fair Isaac Corporation. Confidential. Conceptual Thinking About Leveraging New Data Sources Value of Alternative Data Traditional Credit Data No hitThin fileThick file 6

© 2014 Fair Isaac Corporation. Confidential. ► Regulatory compliance: The data source must comply with all regulations governing consumer credit evaluation ► Depth of information: Data sources that are deeper and contain greater detail are often of greater value ► Scope of coverage: A database covering a broad percentage of consumers can be favorable ► Accuracy: How reliable is the data? How is it reported? Is it self-reported? Are there verification processes in place? ► Predictiveness: The data should predict future consumer repayment behavior ► Orthogonality: Useful data sources should be supplemental or complementary to what's captured by other data sources Alternative Data Considerations 7

© 2014 Fair Isaac Corporation. Confidential. A Word About Orthogonality FICO ® Score Stand Alone Information Value Business Credit Data Property Data Marginal Contribution Value FICO ® Score Business Credit FICO ® Score Property Data 8

© 2014 Fair Isaac Corporation. Confidential. ► Large discrepancy between data sources with respect to coverage, predictive power and orthogonality to traditional credit bureau ► The contribution of alternative data can vary on the type of unscoreable or thin file ► Presence of derogatory information ► Stale files ► New to credit ► Attention should be paid to the type of adverse action reasons that may be returned ► While a data source may be FCRA compliant, thought should also be put into the granularity of the data, for example household vs. individual level aggregation Alternative Credit Data Observations 9

© 2014 Fair Isaac Corporation. Confidential. Assessing Alternative Credit Data Partners 10

© 2014 Fair Isaac Corporation. Confidential. ► Where is your data sourced? ► What is your coverage? ► Who uses it? ► What are some of the attributes deemed most beneficial? ► Are you FCRA compliant? ► Do you have case studies? Questions for a Data Provider 11

© 2014 Fair Isaac Corporation. Confidential. Live Interview 12

The data behind RiskView provides insight into creditworthiness not found on traditional credit reports WILLINGNESS TO REPAYABILITY TO REPAYSTABILITY Address Changes Home Ownership Economic Stability Property Value Occupational Licenses Education History Criminal Records Bankruptcies, Liens, Judgments Evictions and Foreclosures 13

Four examples of RiskView data highly correlated to default risk Source: LexisNexis analysis of credit bureau extract Address Changes Evictions Stable Addresses: 5X Less Risky Presence of Eviction: 3X more risky Value of Residence High Value: 7X Less Risky Occupational License Presence of License: 2X Less Risky 14

RiskView Case Study: Augmenting Bureau Scores in Auto Lending

RiskView Performance in the Auto Industry LexisNexis periodically tests RiskView’s ability to augment bureau-based scores In 2013, we conducted research on a combined portfolio of auto loans from multiple lenders The portfolio contained a bureau-based score for each loan as well as the performance of the loan; bad defined as 90 DPD within 24 months of origination RiskView added lift to the lending decisions in all segments ranging from superprime to deep subprime and also the bureau unscorables 16

Baseline Bureau-only Score Performance Total Sample Size: 108,044 Total Bads: 5,035 17

RiskView Performance on High Risk Segment: Bureau Score between 500 and 550 Segment Bad Rate = 13.3% % of Segment28.1%21.1%19.8%18.2%17.2%14.6%10.6%9.4% 18

RiskView Performance on High Risk Segment: Bureau Score between 550 and 600 Segment Bad Rate = 10.8% % of Segment1.4%1.9%3.3%5.2%8.0%12.2%17.7%18.6%14.9%9.0%7.2% 19

RiskView Performance on Moderate Risk Segment: Bureau Score between 600 and 650 Segment Bad Rate = 6.8% % of Segment1.4%1.7%3.1%7.2%15.2%20.0%20.8%16.0%8.3%6.0% 20

© 2014 Fair Isaac Corporation. Confidential. Combined Score Strategy Fundamentals 21

© 2014 Fair Isaac Corporation. Confidential. ► Two pieces of information are required: ► Volume distribution: how the applicant population will distribute on the new score ► Performance: how the new accounts are expected to perform on the new score ► Volume and performance distributions can be acquired by doing score validations on your portfolio Cut-off Score Selection 22

© 2014 Fair Isaac Corporation. Confidential. FICO Validation Odds Chart An Approach to Setting Cutoffs ►This chart provides both required items: ►Distribution of applicants from the development ►Related performance from the development ►Lenders can use the odds chart to determine initial cutoffs

© 2014 Fair Isaac Corporation. Confidential. Dual-Score Strategy FICO ® Score Alternative Credit Data Score Low High Strengthen your decision Change your decision Alternative Credit Data offers opportunities for a lender to grant credit to increase revenue/profit or reject an application to minimize risk 24

© 2014 Fair Isaac Corporation. Confidential. Alternative Data Scoring The Concept of “Joint Odds” High Risk 5:1 Marginal Risk 10:1 LowRisk 20:1 Alternative Data Score Low ScoreHigh Score 25

© 2014 Fair Isaac Corporation. Confidential. The Concept of “Joint Odds” Credit Bureau Scoring Low Risk 30:1 Marginal Risk 15:1 High Risk 5:1 Low score High score Credit Bureau Score 26

© 2014 Fair Isaac Corporation. Confidential. High score 30:1 15:1 60:130:1 15:1 5:1 15:1 5:1 1:1 Alternative Data Score The Concept of “Joint Odds” Joint Odds Low score High score Credit Bureau Score 27 Low score

© 2014 Fair Isaac Corporation. Confidential. Case Study: Installment Loan Setting Approve/Decline Strategies 28 Low High FICO ® Score Alternative Data Score Strategy: Maintain Acceptance Rate/Decrease Bad Rate— Numbers in Cells Are Bad Rates Cutoff HistoricalStrategy Acceptance Rate60% Bad Rate2.0%1.7% High

© 2014 Fair Isaac Corporation. Confidential. Setting Approve/Decline Strategies Case Study: Installment Loan 29 Low High FICO ® Score Alternative Data Score Strategy: Maintain Bad Rate/Increase Acceptance Rate — Numbers in Cells Are Bad Rates Cutoff 5.8% HistoricalStrategy Acceptance Rate60%66% Bad Rate2.0% High

© 2014 Fair Isaac Corporation. Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent. Thank You! Ankush Tewari David Shellenberger

© 2014 Fair Isaac Corporation. Confidential. Learn More at FICO World Related Sessions ► The FICO ® Score: 25 Years of Democratizing Access to Credit ► Separating Fact from Fiction in the Marketing of Credit Scores Products in Solution Center ► FICO ® Score 9 Experts at FICO World ► Dave Shellenberger ► Brian Cooper ► Freddie Huynh White Papers Online ► Insights #40: To Score or Not to Score Blogs ► 31

© 2014 Fair Isaac Corporation. Confidential. Please rate this session Online 32 Ankush Tewari David Shellenberger