EFL Case Study: Using the EFL Score to Enhance Credit Bureau Data Equifax Peru Executive Summary: Equifax () set out to determine if EFL could add value to its MSME scoring in one of their biggest markets in Latin America: Peru. A 12 month, 800 borrower pilot was designed with a leading Peruvian financial institution. EFL s results enabled significantly increased predictive power in the MSME segment (see Exhibit A below) EFL and have since partnered regionally to offer the expanded credit scoring solution marketwide. This joint study proved that the EFL application, when used in combination with the Equifax score, enables financial institutions to increase lending by 14 while maintaining target default rates, or to reduce default rates by 5 while maintaining target acceptance rates. Using EFL to Increase Lending Using EFL to Reduce Default 6 5 48% 6 5 4 4 3 3 8% 8% 8% 4% Exhibit A: Equifax and EFL joint project results
Partners Overview Equifax: A Global Leader in Credit Scoring Equifax is one of the world s largest credit scoring firms, with operations in 15 countries and registered data on over 600 million individuals and 80 million businesses i. Equifax has a particularly strong footing in Latin America, where it works with financial institutions in Brazil, Argentina, Chile, Costa Rica, Ecuador, El Salvador, Honduras, Paraguay, Peru, and Uruguay ii. The centrepiece of Equifax s LatAm footprint is Peru, where it is the largest credit scoring firm. Figure 1 Equifax's Latin America Footprint EFL: Proven Global Leader in Psychometric Scoring EFL first pioneered psychometric credit scoring through research at the Harvard Center for International Development. EFL s psychometric tool enables better lending decision by creating a deep quantitative understanding of individual risk and opportunity in small business (MSME) and consumer financing. Figure 2 EFL Global Footprint EFL s technology powers lending in the world s leading financial institutions and is validated by nearly 10 years of real-world loan performance across 27 countries and over 36 financial institutions. Peruvian Market Context Peruvian banks, much like their Latin American peers, have for most of their history focused either on the corporate or microfinance segments of the market. In both of these segments, banks have excelled: Peru has an advanced corporate banking sector, and has been ranked the most microfinance friendly country on earth for six consecutive years. iii More recently, a growing need for financing in Peru s lower and middle income segment, the space between corporate and micro banking, has inspired a strategic shift in many of Peru s largest banks. Beginning in the mid 2000 s many lenders have begun to turn their attention towards Peru s micro, small and medium enterprises (MSMEs). For both Equifax and the banks who use its scores, prioritizing MSMEs presents a necessary, but difficult challenge: many Peruvian MSMEs, especially in the lower income segment of the population, lack basic credit criteria like borrowing histories, collateral, and income statements. Only 4 of Peruvians are captured
in Peru s credit bureau iv, and many of those currently included are thin-file, meaning the data recorded is sparse or incomplete. This information scarcity presents a formidable barrier to financial access, resulting in very low banking penetration in this high growth segment. In Peru s poorest 4, for example, less than 9% are able access loans from formal financial institutions each year. v Information scarcity is not the only challenge in lending to MSMEs. Individual MSME loans are typically larger than group loans, meaning that with each disbursement a lender has more at stake. Furthermore, MSME loans are often utilized by borrowers for higher risk investments: while most group borrowers will use capital for business maintenance or small, incremental growth, larger MSME loans are used to fund more significant expansion efforts, which are higher risk, and also higher reward. According to bureau data from EFL s Peruvian partner banks borrowing population, for example, 1 in 5 MSME loan applicants had some form of negative mark on their credit record. The risks associated with the massive, and growing MSME lending market makes reliable and accurate credit scoring all the more important. Project Overview Equifax, EFL, and EFL s Peruvian partner bank shared data on over 800 MSME loan applicants to determine if EFL s credit scoring methodology could be used to provide greater insight on MSME clients. Once applicants completed EFL surveys, their credit histories were analysed to determine Equifax Scores, and they were segmented into five equally sized buckets, or quintiles, based on the scores they received. This scoring system is shown in Figure 3. Next, EFL and Equifax reviewed the status of each applicant in the Peruvian credit bureau six months after their initial application to understand how those scores could complement one other. Results As expected, applicants who received higher scores defaulted less often than applicants who received lower scores for both EFL and Equifax, but EFL and Equifax scores demonstrated different levels of predictive power within each of the 5 groups. The default rate of EFL s Group A, for example, is different than that of Equifax s Group 1. Figure 3 - EFL's Granular Divisions
Comparing the performance of EFL scores and Equifax scores provides insight into the relative value of each, but more important is how the scores can be combined to uncover previously hidden risk and opportunity. The parties next set out to determine how utilizing the EFL score in addition to an existing Equifax score could increase lending while controlling risk and decrease default while minimizing portfolio reduction. Case 1: Expanding Lending First, let s consider how using the EFL score to complement the Equifax score can allow a lender to increase the size of its portfolio while maintaining target levels of default. A financial institution targeting default rates below, but with access only to traditional bureau scoring would see only 5 groupings sorted properly by risk, as in Figure 4. Using only Equifax bureau data, a lender targeting a sub- default rate would only be able to lend to Group 1, at a acceptance rate. Figure 4 - Equifax Score Groupings By leveraging the EFL score in addition to the Equifax score, however, the lender gains a more granular understanding of risk, as illustrated by Figure 5. Figure 5 - EFL Score Overlay by
With the addition of the EFL score, the lender can now better differentiate risk within and between Equifax Groups. Equifax s Group 1, for example, has a default rate of 8% when viewed as a whole. But within that group, default rates vary widely when categorized using the EFL score. Within Equifax s Group 1, those in EFL s Group E defaulted at 14%, more than 3 times as often as Group A, and more than 1.5x as much as the Group as a whole. Figure 6- Differentiating Risk within Equifax Groups Just as importantly, the addition of the EFL score illuminates the fact that the safest segments of riskier groups often performed better than the riskiest segments of safer groups. In other words, additional less-risky clients would otherwise be rejected. For example, though as a whole Equifax s Group 2 defaulted more than 5 more than Equifax s Group 1, the EFL Group A within Equifax s Group 2 defaulted at, whereas the EFL Group E within Equifax Group 1 defaulted at 14%. Figure 7- Differentiating Risk between Subsets of Equifax Groups
This granular risk analysis enables the creation of new, and better, blended portfolios. Now, re-imagine the lender targeting a sub- default rate. Using the EFL score, the lender can combine applicants from Equifax s original group 1, plus an additional subset of clients in Equifax s group 2, 3, and 4 selected by EFL. Figure 8- New EFL-enabled Portfolio Without the EFL score, the highlighted borrowers in Equifax s Groups 2, 3, and 4 would have been completely inaccessible. Using the EFL-Equifax blended score, a financial institution could now accept 48% of all applicants, with a total default rate of 8%. That s a 14 increase in lending, while still maintaining the targeted default rate of below. Using EFL to Increase Lending 6 5 48% 4 3 8% 8% Figure 9 - The addition of the EFL score enabled a 14 increase in acceptance, with a similar default rate.
Case 2: Reducing Default Next, let s examine how using the EFL score to complement existing bureau information can allow a lender to reduce the default rate of a portfolio. Imagine a lender targeting an acceptance rate of, again using the Equifax score alone. As was the case in the previous example, such an institution would only lend to Group 1, incurring a default rate of 8%. Figure 10 Equifax Score Groupings By leveraging the EFL score in addition to the Equifax score, the lender again gains a much more nuanced portrait of applicant risk, as demonstrated by Figure 11. Figure 11 EFL Score Overlay by
Incorporating EFL reveals safe subsets of the portfolio within the previously rejected Groups 2 and 3. This enables the lender to build a blended portfolio at an acceptance rate of, with a total default rate of 4%: That s half the default rate of the previous portfolio, at the same acceptance rate. Figure 12 New EFL-enabled Portfolio Without the EFL score, it would have been impossible to segment the borrowing population beyond Equifax s Group1. Using the EFL Score, a lender can not only select the lowest risk applicants within Equifax s Group 1, it can also identify additional low-risk borrowers from Equifax s Groups 2 and 3. The addition of the EFL score enabled a 5 reduction in default with the same acceptance rate. 25% Using EFL to Reduce Default 15% 8% 5% 4% Figure 13 New EFL-enabled Portfolio
Conclusion The EFL and Equifax pilot demonstrated that leveraging the EFL credit score in addition to the Equifax credit score can have a significant and positive impact on lending efforts. Not only can the EFL score accurately measure performance on its own, when used with the Equifax score it can enable financial institutions to increase lending by 14 while maintaining target default rates, or to reduce default rates by 5 while maintaining target acceptance rates. Using EFL to Increase Lending Using EFL to Reduce Default 6 5 48% 6 5 4 4 3 3 8% 8% 8% 4% Encouraged by the results of the pilot, EFL and Equifax have since launched a full-scale commercial sales partnership, and are integrating scoring capabilities to help lenders in leading markets across Latin America. i http://www.equifax.com/about-equifax/company-profile ii http://www.equifax.com/about-equifax/company-profile iii http://www.citigroup.com/citi/citizen/community/data/eiu_microfinance_2013_proof_08.pdf iv http://data.worldbank.org/indicator/ic.crd.prvt.zs v http://databank.worldbank.org/data/views/variableselection/selectvariables.aspx?source=1228#