In a credit-hungry economy, how much is too much?

Transcription

1 In a credit-hungry economy, how much is too much? Know how new debt affects risk with sharper measures of credit capacity Number 1 February 2008 US credit hunger seems insatiable. Consumer debt has reached an all-time high more than $2.5 trillion in Q according to the Federal Reserve. Certainly, there are many reasons for this growth among them, lower interest rates and growing competition among lenders to offer new and different types of credit products. But while the opportunity for lenders is great, so are the potential pitfalls and not just in increased losses and dissatisfied customers. Concerns over mortgage subprime have put the issue of consumer debt front-and-center, with the media, legislators and even consumers themselves asking: How much is too much? What s missing in today s lending strategies is the ability to determine, For consumers who look equally risky, who can safely manage additional credit? This presents a dichotomy for lenders, who find themselves needing to be risk-conscious and tightening credit standards, while still pursuing new opportunities. The good news is that a new breed of analytics can help lenders walk the fine line of growing the business without over-extending consumers. The analytics measure a consumer s capacity to take on additional credit, and as such, provide powerful new insight into managing consumer debt. Make every decision count TM

2 The limits of income The reason lenders need analytics to measure credit capacity is simple: today s risk measures are not enough. Traditionally, lenders use income and income-based measures (i.e., debt-to-income ratios), along with FICO scores, to gauge a consumer s ability to handle incremental debt. But income, while predictive, is by itself limited. This is primarily because income is often self-reported, difficult to verify and subject to manipulation. Even consumers who attempt to report income honestly and not all do often are unclear how to calculate their earnings accurately: Do I report my income as gross or net? Do I include stock income/bonuses? Do I account for spousal support? Even when income is accurate, it does not account for discretionary income relative to cost of living. Consider for example, the same income won t stretch as far if you live in Manhattan vs. Little Rock. While income-based measures augment lender strategies, stronger measures of capacity are needed for a more complete picture of consumer credit risk. Putting credit capacity to work Like income, a FICO score is a strong predictor and critical to risk management strategies. But bureau-based risk scores cannot consider information not yet represented on credit reports, such as incremental future debt. The fact is there are many reasons why different consumers could get the same FICO scores. For example, some with mild delinquency and low utilization may receive the same score as those with no delinquency but high utilization. These various credit profiles within the same score band represent different sensitivities to incremental debt, as shown in Figure 1. What s missing in today s lending strategies is the ability to determine, For consumers who look equally risky, which can more safely manage additional credit? in other words, more precise measures of credit capacity. Figure 1: Same Risk, Different Capacity (Theoretical Example) Larry, Mary and Harry Similar FICO Score, Different Capacity 50% ESTIMATED DEFAULT RATE 40% 30% 20% 10% Legend Capacity Level Larry Mary Mid Harry BALANCE CHANGE The theoretical consumers on this chart have similar risk scores with the same default probability, given no change to their indebtedness. But they have different capacities to handle additional debt, which affects their future risk. This makes credit capacity critical to lending strategies. page 2

3 The value of measuring credit capacity Increase control over loss exposure and reserves. Lenders can refine line assignments toward consumers best able to repay debt, and limit exposure for those posing the highest default risk. This would help reduce loss reserves and reallocate working capital to more profitable areas of business. Grow portfolio profits. Line assignments can more closely correspond with what a consumer can safely handle, minimizing losses. Demonstrate responsible lending practices. Proactive management of consumer debt loads would help address consumer group and legislative pressures to alleviate over-indebtedness. Improve customer satisfaction, retention and corporate image. Public promotion of responsible lending practices could help boost customer ties and corporate image, and attract and retain more good customers. Capacity measures would allow a lender to reallocate loss exposure and reserves toward consumers best able to repay debt, not to mention protect its customers long-term credit health and loyalty. And proactive management of consumer debt levels can go a long way in addressing today s legislative and consumer group pressures for greater consumer protections within lending practices (see sidebar). Research shows that a new analytic approach can effectively capture and leverage capacity. The FICO Credit Capacity Index generates a forwardlooking risk measure that predicts which consumers can more safely manage new or increased credit. Combined with FICO scores, Credit Capacity Index helps lenders better target and set initial credit amounts and product terms, and refine account management actions such as credit line assignment and authorizations. Credit Capacity Index is extremely effective within existing credit strategies. Across income groups and risk levels, there are segments with relatively high, moderate and low capacities to manage increased debt, as shown in Figure 2. This knowledge can be used to target or refine offers of new credit for each group. Figure 2: Opportunities to Target Action FICO by Income and Credit Capacity Index Results on pooled bankcard sample POPULATION % 60% 50% 40% 30% 20% Legend Capacity Level Moderate 10% 0% UNKNOWN < $30K $30K 54K $55K 79K $80K 114K $115K+ FICO TM CREDIT CAPACITY INDEX WITHIN INCOME GROUPS This chart shows the distribution of credit capacity levels within income groups for the mid-fico score range of Opportunities exist within each income level to safely offer new or grow existing credit lines, or to reduce exposure among those less likely to safely manage new debt. page 3

4 Managing capacity a practical approach So, how would a lender use these analytics in practice? Let s explore a sample strategy for new bankcard accounts. For prescreen acquisitions and originations underwriting, strategies often include FICO scores, income and other measures. Credit Capacity Index would be added to existing strategies, providing new information on credit capacity not otherwise captured. This would help determine target offers and initial line assignments, especially near existing cutoff zones, as illustrated in Figure 3. While this sample strategy is somewhat basic, it demonstrates the overall approach for using Credit Capacity Index: While FICO scores reflect consumer risk based on today s credit mix, FICO Credit Capacity Index measures a consumer s ability to take on future incremental debt, in both new and existing credit accounts. Consumers with very low FICO scores and low income, as well as those with high FICO scores and high income, would be treated the same as before, with a few exceptions. Consumers with FICO scores in the lender s operating range, missing income or other borderline areas would be assigned either higher or lower lines, depending on capacity. For example, in the FICO group, there would be opportunities to increase lines for high-capacity consumers, but reduce lines by the same amount when capacity is low. This would minimize future losses and retain consistent exposure levels. A similar approach to Figure 3 could also be used in account management. Credit Capacity Index would be included on top of existing measures, such as internal analytics, FICO score, current delinquency and relationship status. Figure 3: Using Capacity in Practice Simple New Account Acquisition Very Accept Maximum Line FICO Score + Income Moderate Decrease Line from Standard Standard Line Assignment Increase Line from Standard Very Decline / Accept Minimum Line Moderate FICO CREDIT CAPACITY INDEX TM When assigning credit limits for new accounts, Credit Capacity Index is layered on top of existing risk measures here, FICO score and an income measure. Using this strategy, a lender could fine-tune target offers and initial line assignments, particularly for borderline decisions. page 4

5 The critical take-away here is that Credit Capacity Index is a powerful tool for use within existing lending strategies not a replacement for other risk measures. It s still essential, for instance, to consider the consumer s projected risk to repay the debt. After all, you may not want to extend credit to high-capacity consumers that are also high-risk. That s why Credit Capacity Index and FICO scores go hand-in-hand. Just as the FICO score s rank-ordering of risk is used in strategies to determine whether to extend credit to consumers and doesn t provide a yes/no answer on its own Credit Capacity Index operates much in the same way. It serves as a key part of the strategies that answer How much new debt is too much? Adding techniques like strategy optimization can help determine the optimal combination of risk measures to make fully informed credit decisions. Modeling for the future Like the FICO score, Credit Capacity Index is built on credit bureau data and is designed to rankorder consumers according to risk for use within lending strategies. But FICO scores reflect consumer risk based on today s credit mix. By contrast, Credit Capacity Index measures consumer risk if he/she takes on future incremental debt. This new debt can be in the form of new credit accounts or increases in existing accounts. FICO Credit Capacity Index is based on Future Action Impact Modeling, which can isolate consumer sensitivity to new behaviors not currently present on the credit report and infer tolerance for incremental future debt. Figure 4: Strong Risk Separation as Balance Increases New Bankcards Mid- FICO Scores, FICO by FICO Credit Capacity Index Results on pooled bankcard sample 30% 25% Legend Capacity Level Mid Pop% 45% 20% BAD RATE 15% 10% 37% 18% 5% 0% NO INCREASE LOW MED LOW MED MED HIGH HIGH REVOLVING BALANCE CHANGE Credit Capacity Index successfully spots bankcard accounts most likely affected by incremental debt. The chart shows a greater increase in bad rate as balances rise for those identified as low-capacity than for high-capacity consumers. Similar results were seen across the consumer lifecycle and risk score ranges. page 5

6 Credit Capacity Index, now available at FICO, is based on patent-pending technology called Future Action Impact Modeling. Unlike traditional bureau-based risk modeling, Future Action Impact Modeling can isolate consumer sensitivity to new behaviors not currently present on the credit report and infer tolerance for incremental future debt. FICO research reinforces the added predictive value of Credit Capacity Index when used with FICO scores. Validation results for both new and existing revolving accounts show that Credit Capacity Index effectively rank-orders consumers most likely affected by incremental debt within each risk score range those that, without a change in debt, would have the same expected risk of default. We re also working with lenders on validations for installment products. Credit Capacity Index, like the FICO score, is an objective risk measure that meets the consumer and legislative fairness test. Based solely on credit repayment history, it would be applied equally across all consumer segments and is fully compliant with the Fair Credit Reporting Act (FCRA). Today s lending challenges call for a new approach to answering How much is too much? Tools like FICO Credit Capacity Index offer lenders a huge advantage by adding a new dimension to risk assessment for a more complete picture of consumer debt. To learn more about FICO s measure of credit capacity, contact us at or cbhelpline@fico.com. The Insights white paper series provides briefings on research findings and product development directions from FICO. To subscribe, go to For more information US toll-free International web (0) info@fico.com Fair Isaac, FICO, Credit Capacity Index and Make every decision count are trademarks or registered trademarks of Fair Isaac Corporation in the United States and in other countries. Other product and company names herein may be trademarks of their respective owners Fair Isaac Corporation. All rights reserved. 2452WP 05/09 PDF