Maximizing the Credit Universe

Similar documents
Universe Expansion: Is the Way You Score Customers State of the Art or State of Denial?

Universe Expansion: Is the Way You Score Customers State of the Art or State of Denial?

Implementing a New Credit Score in Lender Strategies

Inaugural VantageScore 4.0 Trended Data Model Validation

Scoring Credit Invisibles

2008 VantageScore Revalidation

Trended Credit Data Attributes in VantageScore 4.0

A credit score that means more. To lenders, borrowers and the nation.

A Decade of Validation Demonstrates Superior Performance

Dollars of Lines Originated (Billions) Dollars of Lines Originated Billions)

Diving deep on credit establishment

SEGMENTATION FOR CREDIT-BASED DELINQUENCY MODELS. May 2006

VANTAGESCORE SOLUTIONS INTRODUCES VANTAGESCORE 3.0 MODEL

FICO s analysis indicates:

Universe expansion. Growth strategies in the evolving consumer market

Federal Reserve Bank of Philadelphia

Executing Effective Validations

CFPB Data Point: Becoming Credit Visible

How much can increased predictive power impact profits?

How Are Credit Line Decreases Impacting Consumer Credit Risk?

Enhanced Public Record Standards July 2017

Boost Collections and Recovery Results With Analytics

Maximizing predictive performance at origination and beyond!

Testing Methodologies for Credit Score Models to Identify Statistical Bias toward Protected Classes

Quarterly U.S. Consumer Credit Trends DATA AS OF DECEMBER 2017

GET SOCIAL WITH US. #vision2016. Tweet, follow, share throughout the session.

Understanding TransUnion s Credit-based Insurance Scores

Emerging Opportunities in Home Equity Lending. Joe Mellman Senior Vice President, Mortgage Business Lead

Credit Score Basics, Part 1: What s Behind Credit Scores? October 2011

GET SOCIAL WITH US. #vision2016. Tweet, follow, share throughout the session.

ECONOMIC COMMENTARY. Americans Cut Their Debt Yuliya Demyanyk and Matthew Koepke

A new highly predictive FICO Score for an uncertain world

Credit Market Consequences of Credit Flag Removals *

FICO Score Open Access Consumer Credit Education US Version. Frequently Asked Questions about FICO Scores

Credit Score Basics, Part 3: Achieving the Same Risk Interpretation from Different Models with Different Ranges

Identifying High Spend Consumers with Equifax Dimensions

Count Balance $0.00 $0.00 $0.00 Current Delinquent Other 0 0 0

A Credit Smart Start. Michael Trecek Sr. Risk Analyst Commerce Bank - Retail Lending

Turning the tide. Managing troubled portfolios

The Benefits of Credit Reporting How CBA Reporter Can Positively Impact Your Lending Organization

American Reporting Company. American Reporting Company

CRIF Lending Solutions WHITE PAPER

Credit Market Consequences of Credit Flag Removals *

65 E. Wacker Place Suite 1405, Chicago, IL Ph: Fax: Credit 101

The Bubble, the Burst and Now What Happened to the Consumer? Joe Mellman Vice President, Financial Services TransUnion

THE PREDICTIVE VALUE OF CREDIT-BASED INSURANCE SCORES

Understanding Your FICO Score. Understanding FICO Scores

Multi-Bureau Data: Maximising Predictive Accuracy and Customer Understanding

2/10/2015 CREDIT FOR SUCCESS TODAY S NEW RISK FACTORS MOBILE BANKING. The new Consumer Financial Protection Act, the ATR Rule (Ability to Repay Rule)

Get educated A study in the student lending marketplace

Millennials, Generation Z and credit

Your Money, Your Goals Spotlight Series. Understanding credit reports and scores: An in-depth look

How Students Use Credit and What You Need to Know. Deb Gossman College Ave Student Loans

Understanding. What you need to know about the most widely used credit scores

White Paper. Who s Getting Paid During the Subprime Crisis?

Score migration strategies for turbulent times

Summary. The importance of accessing formal credit markets

2017 VANTAGESCORE MARKET STUDY REPORT. AUTHOR Peter Carroll, Partner

Exploring specialty finance data

FICO Score Open Access Consumer Credit Education US Version. Frequently Asked Questions about the FICO Score

Introduction. In short- credit is an essential part of our personal and national economic stability.

Credit score ratings chart 2017

How to be Successful With Higher-Risk Auto Lending

Financial Well-being. Debt and Credit

The Benefits of Credit Reporting How CBA Reporter Can Positively Impact Your Lending Organization

Credit Reports 101. Bill Bufkins, November 3, 2011

Desktop Underwriter/Desktop Originator Release Notes

2018 VANTAGESCORE MARKET STUDY REPORT. AUTHORS Peter Carroll, Partner Cosimo Schiavone, Principal

From Main Street to LendStreet a lending platform success story

CREDIT REPORTS & CREDIT SCORES

TIP: Make sure this information is correct. A wrong address or phone number could be a mistake or a sign of identity theft.

UNDERSTANDING BUSINESS CREDIT

For competitive advantage, refresh more frequently. FICO s analysis indicates:

LendIt Michele Raneri April 2016

TABLE OF CONTENTS. Healthier Black Elders Center

Harnessing Traditional and Alternative Credit Data: Credit Optics 5.0

2015 BOK Financial Corporation and BOKF, NA DFAST Public Disclosure

FAQ. What is trended credit data? Why is this change coming?

Credit Score: What it Means to your Business

12 Steps to Improved Credit Steven K. Shapiro

A Checkup On Your Financial Health. Paul Ellinger Bruce Sherrick

Trends Report Alternative Financial Services Lending Trends Insights into the Industry and Its Consumers

A Balanced View of Storefront Payday Borrowing Patterns Results From a Longitudinal Random Sample Over 4.5 Years

February 2018 QUARTERLY CONSUMER CREDIT TRENDS. Public Records

Improving Your Credit Score

ALTERNATIVE DATA AND THE UNBANKED

Socio-Demographic Projections for Autauga, Elmore, and Montgomery Counties:

Attract and retain more high-quality customers while reducing your risks.

Ohio Bureau of Workers Compensation Actuarial Committee

JOB SITUATION INCOME. 3 rd Quarter 2015 PITTSBURGH

Building a U.S. credit score

Credit and Credit Cards

Measuring Retirement Plan Effectiveness

Credit Cards and Financial Health Member-Exclusive Report from CFSI s Consumer Financial Health Study

UPDATED CREDIT SCORING AND THE MORTGAGE MARKET. December 2017

CREDIT SCORE USER GUIDE

How to Stay Relevant in a Disruptive Lending Environment

Does providing FICO Scores influence financial behavior?

LexisNexis RiskView Report

Asset Lending. Hard Money ASSET LENDING OR HARD MONEY

Transcription:

SM JUNE 2015 Maximizing the Credit Universe Contents It s not just the value of the score that defines the credit accessible universe 1 From the credit eligible universe to the credit accessible universe 2 The Credit Eligible Universe 2 Case Study 4 Universe and Risk Optimization 5 Conclusion 5

Maximizing the Credit Universe INTRODUCTION One result of more conservative lending practices following the Great Recession has been the incorporation of judgmental criteria in lending strategies which give greater scrutiny of any previous bankruptcy and that require consumers to have a thick file. 1 The implicit assumption of the criteria is that more information on the consumer credit file enables a better assessment of the consumer s risk level. This paper will show that qualitative criteria of this nature may not only fail to reduce origination risk, but can also substantially reduce the accessible lending universe for reasons unrelated to consumer risk assessment. This paper contains two sections. First, a review of the data and analytic processing elements, such as the composition of the credit file, consistency of file composition across the primary three national reporting companies (CRCs) and credit score model design. Each element will be discussed and its impact on the accessible universe evaluated. The review will show that for certain judgmental criteria lending strategies, they can reduce the lending universe by as many as 60 million consumers. Second, a case study analyzes the impact of these elements on a sample mortgage originations strategy. The case study demonstrates how the strategy can be enhanced to expand the universe by 19 million consumers and simultaneously lower the overall risk of the originated loan portfolio. 1 A consumer with less than three credit accounts or trades in his or her credit file is defined as having a thin file whereas a consumer with three or more accounts/trades is defined as having a thick file. IT S NOT JUST THE VALUE OF THE SCORE THAT DEFINES THE CREDIT ACCESSIBLE UNIVERSE The size of the credit accessible universe, i.e., the number of consumers who satisfy a lender s risk criteria within a specific strategy, is not simply a function of whether their credit scores reflect sufficiently low likelihood of default. The size of the universe is also conditioned upon the following (Figure 1): Does the consumer have a consumer credit file at one or more of the CRCs? What is the composition of their file? How many accounts are on the file? How old are the accounts? How often are these accounts updated? Is the composition of their credit file the same at all CRCs? Given the minimum data processing criteria of the lender s scoring model, does the consumer s credit file contain sufficient data to be scored? Can the consumer be scored at all three CRCs if they have different file composition at each CRC? And finally, does the consumer s score exceed the lender s cut-off threshold? Depending on the lender strategy, the number of CRCs that the lender works with and the credit scoring model design, each of these three hurdles may substantially reduce the universe of consumers that the lender can access to offer credit. 1 - VantageScore: Maximizing the Credit Universe

Figure 1: Credit-accesible universe conditions FROM THE CREDIT ELIGIBLE UNIVERSE TO THE CREDIT ACCESSIBLE UNIVERSE The Credit Eligible Universe As of the 2010 U.S. Census, 308 million people live in the United States; of which, 237 million (77 percent) are 18 years or older and may be eligible to receive credit. Using a 2010-2012 sample of consumers who were randomly selected from the three CRCs, roughly 220-230 million of the potentially eligible population have a credit file with at least one of the CRCs. This is the credit eligible universe the universe of consumers who can be considered for lending. A lender s credit accessible universe is the universe of consumers who are ultimately considered for credit after filtering the eligible universe through the hurdles referenced in Figure 1. Credit File Composition The credit eligible universe of approximately 227 million individuals can be assigned the following file composition profiles (Figure 2). Mainstream Typical credit users 160 million consumers with at least three credit accounts that are frequently updated on their credit file (at least every 6 months) Upsiders? Often consumers such as thin file consumers, infrequent users of credit, and new credit users that have the potential to be highly credit-worthy 20 million consumers who have one or two accounts, i.e., a thin file that is frequently updated (at least every 6 months) 13 million consumers with any number of accounts but who use credit less frequently, such that their credit file is updated within a 6 to 24 month window 1 million consumers who may use credit frequently, but whose accounts are less than 6 months old Minimalists Those that use credit only rarely but could be good loan candidates 13 million consumers who rarely use credit, with updates to their credit file that are at least 24 months old 13 million consumers with only derogatory information on their credit file Figure 2: Credit file composition Number of Accounts High (=>3) Frequency of Updates High (within 6 months) Profile Volumes (millions) Mainstream 160 1 or 2 High Upsiders? 20 Any Moderate (6-24 months) Upsiders? 13 <6 months old Any Upsiders? 1 Any Only collections or public records Inquiry only deceased Low (>24 months) Minimalists 13 Any Minimalists 13 Ineligible 7 IMPACT: Strategies that require a mainstream file composition immediately exclude 60 million consumers VantageScore: Maximizing the Credit Universe - 2

Figure 3: Model design criteria affect the eligible universe Profile Volumes (millions) Scored by Conventional Scoring Models Scored by VantagScore 1.0 & 2.0 Scored by VantagScore 3.0 Mainstream 160 Upsiders? 20 Upsiders? 13 Upsiders? 1 Minimalists 13 Minimalists 13 Ineligible 7 IMPACT: Lenders that use a conventional credit score model could exclude as many as 40 million consumers Figure 4: Credit file composition across CRCs 100% 50% 0% 6% 16% 78% 20% 22% 24% 55% 36% 42% Mainstream Upsiders? Minimalist At 1 of 3 At 2 of 3 At 3 of 3 IMPACT: A strategy that requires the presence of a Mainstream file composition could lose as many as 36 million consumers if the consumers are sourced through just one CRC Figure 5: Consumer credit use contributes to the eligible universe Gain 5.1 million consumers Open accounts More intense usage Upsiders? 4.8 million Minimalist 0.3 million Mainstream File Composition Annualized Consumer Migration Lose 5.5 million consumers Account closures More sparse use of credit Upsiders? 4.2 million Minimalist 1.3 million Ineligible Consumers with inquiry-only information or who are deceased (7 million consumers) Credit scoring model design As credit scoring technology has improved over the last decade, more recently developed models have taken advantage of these improvements and are consequently able to score a larger percentage of the credit eligible universe. VantageScore 3.0 scores 220 million consumers (Figure 3). See www.vantagescore.com/universeexpansion for a comprehensive discussion of VantageScore 3.0 scoring approach and the predictive performance results for these newly-scored consumers. File composition across CRCs The composition of a consumer s credit file can vary at each CRC for many reasons. Lenders may report the consumer s credit information to the CRCs at different times, and though less frequently occurring, some lenders may not report to all major CRCs. As a result, a consumer s credit file composition and consequently their score can be different at each CRC (Figure 4). For example, a review of file composition for one million consumers across the three CRCs showed that only 78 percent of consumers had a mainstream composition at all three CRCs simultaneously. Sixteen percent of consumers, approximately 26 million, had a mainstream composition at two CRCs simultaneously and 6 percent, approximately 10 million, had a mainstream composition at just one CRC. File migration Although it s a phenomenon with considerably smaller volume, consumers credit use behaviors impact the composition of their credit file and, therefore, possible consideration for lending (Figure 5). Annually, an average of 5.1 million consumers expand their credit usage by opening accounts and using credit more intensely, and as a result, move from the Upsiders and Minimalist tiers to the Mainstream file composition tier. Conversely, an average 5.5 million consumers reduce their need and use of credit to drop out of the Mainstream tier. As a result, these consumers appear and disappear from the accessible universe. Clearly there are a number of significant hurdles that must be passed in order to be considered credit-worthy. Figure 6 shows the potential cumulative impact of these hurdles. Under a worst-case scenario, the accessible universe may be reduced by as much as 43 percent based on these elements. And this is prior to any empirical analysis of consumer risk IMPACT: The accessible universe for a strategy requiring mainstream file composition can vary by +/- 5 million consumers as consumers migrate into and out of consideration given their changing credit usage pattern 3 - VantageScore: Maximizing the Credit Universe

Figure 6: Credit accesible universe based on their behaviors, i.e., the credit score value, has been applied. Case Study The following analysis of a mortgage originations strategy shows the impact of requiring qualitative file composition criteria, given the data and analytic processing environment. The analysis also demonstrates how to enhance the strategy to expand the universe of eligible consumers while reducing the risk profile of the originated portfolio. The strategy below reflects a typical design for mortgage originations. For a consumer to be considered for credit: Their credit file (from at least one of the CRCs) must be Mainstream, i.e., have at least three trades with updates during the last 6 months. A credit score is obtained for every instance of a Mainstream credit file at the CRC. If three credit scores are obtained, the median value score is selected as the consumer s score If two scores are obtained, the lower score is selected If just one score is obtained, this is used as the consumer s score Finally, a consumer is eligible if the score value is greater than 620. How effective is the current strategy? 173 million consumers have at least one instance of a mainstream file composition at the CRCs. However, 54 million consumers are excluded from consideration given they do not have a Mainstream file composition at any of the CRCs (Figure 7). Of the 173 million consumers, 128 million exceed the score threshold criteria of 620. Figure 7: Mainstream file composition Mainstream Percent of population Accessible Universe (Millions) All 3 bureaus 59.1% 135 2 bureaus 12.1% 28 1 bureau 4.7% 10 Total accessible universe 173 Ineligible 54 Figure 8: Default rate profiles by score assignment method A review of the default rate profiles (Figure 8) for these consumers shows that consumers with two or more credit scores have lower actual default rates across the credit score spectrum. These results suggest that the consistency of information, in this case, file composition, is representative of higher credit quality information. Conversely, consumers with a mainstream file at just one CRC, and, therefore, a single credit score, demonstrate higher risk levels across the credit score range. At the threshold score cut-off value of 620, the default rate is as high as 13 percent. Under this current strategy, the organization is willing to accept a default rate as high as 13 percent in its originations business. Any expansion to the accessible universe must be achieved at or below this default rate. VantageScore: Maximizing the Credit Universe - 4

Figure 9: Universe expansion by removing file composition criteria Universe and Risk Optimization Removing the Mainstream composition criteria so that any consumer with a valid credit score is eligible will naturally expand the universe. Using VantageScore 3.0, the universe can be expanded by 27 percent or 47 million consumers (Figure 9). Exist at Incumbent Opportunity Change in information coverage 3 CRCs 135 183 36% 2 CRCs 28 30 9% 1 CRC 11 7-35% Not eligible 55 7-89% Total (millions) 227 Figure 10: Impact of the score selection criteria Figure 11: Final accessible universe for revised strategy Figure 12: Default rate profile for revised strategy The next logical question is whether this expanded universe contains consumers of sufficiently high credit quality. Applying the score selection criteria, results in a revised score for 21 million consumers. An increased number of scores are now available for these consumers. Applying the score assignment method of selecting the median if three scores are present or the lower if two scores are present, results in a lower selected final score and a more conservative risk assessment. 48 million consumers, who were previously ineligible given their credit file did not satisfy the mainstream file composition criteria, become new opportunities (Figure 10). Finally, applying the score cut-off criteria that consumers must have a score greater than 620, results in a final accessible universe of 146 million consumers a 14 percent expansion over the accessible universe identified under the incumbent strategy (Figure 11). Significantly, 19 million New Opportunity consumers score at or above 620. Note also that the Alters Existing population is slightly reduced by 300,000 consumers, given their revised score is now lower than the cut-off. The final requirement of the revised strategy is that these consumers, with revised and new scores, perform at or below the default rate profile of the incumbent strategy. Figure 12 demonstrates that the default rate profiles for the revised (Alters Existing) and newly (New Opportunity) scored consumers are clearly at or below the incumbent performance, most significantly in the higher risk portion of the credit score range. CONCLUSION Strategy design elements such as file composition criteria clearly impact the accessible universe and do not necessarily reduce the risk exposure. Furthermore, scoring models that require sufficient file composition in order to score the consumer may further reduce the accessible universe, without reducing risk exposure. Conversely, leveraging the mathematical innovation in VantageScore 3.0 not only maximizes the lending universe, but it also does so without increasing risk exposure. 5 - VantageScore: Maximizing the Credit Universe

The VantageScore credit score models are sold and marketed only through individual licensing arrangements with the three major credit reporting companies (CRCs): Equifax, Experian and TransUnion. Lenders and other commercial entities interested in learning more about the VantageScore credit score models, including the VantageScore 3.0 credit score model, may contact one of the following CRCs listed for additional assistance: Call 1-888-202-4025 www.equifax.com/vantagescore Call 1-888-414-4025 www.experian.com/consumer-information/ vantagescorelenders.html Call 1-866-922-2100 www.transunion.com/corporatebusiness/solutions/ financialservices/bank_acq_vantage-score.page VantageScore June 2015 Copyright VantageScore www.vantagescore.com