Data Both Helps to Underwrite Applicants Who Lack Traditional Credit History and Improves Risk Sorting Among Borrowers Who Are Ranked Similarly by Traditional Scoring Systems
WASHINGTON, D.C., July 25, 2019 – FinRegLab today issued one of the first ever public evaluations of cash-flow data—variables and credit scores that are derived from bank account records and other sources—as a potential alternative or supplement to using traditional credit scores in underwriting credit for consumers and small businesses. The report, The Use of Cash-Flow Data in Underwriting Credit: Empirical Research Findings, can be found here.
The study, which analyzes data from six nonbank financial services providers, found compelling evidence that the cash-flow variables and scores tested were predictive of credit risk and loan performance across the diverse set of companies, populations, and products studied.
“Millions of consumers and small businesses struggle to achieve access to credit in today’s markets,” said FinRegLab CEO Melissa Koide. “These results suggest that cash-flow data may provide an important part of the answer.”
Today’s credit markets depend heavily on information provided by credit bureaus to underwrite consumers and small businesses. But an estimated 45 to 60 million consumers lack sufficient credit history to generate reliable credit scores, and millions more struggle to access affordable credit because their scores are too low. The lack of easy access to reliable underwriting information also makes it hard for business start-ups to obtain loans.
In light of these gaps, industry is increasingly looking for additional information sources that can improve its ability to forecast credit risk. Cash-flow information—such as records of transactions in and out of consumers’ deposit and card accounts, or feeds from small business accounting software—is one of the most promising options because it provides a more detailed and timely picture of how applicants are managing their finances than traditional credit reports. More than 96 percent of American households have bank or prepaid accounts, and account data is increasingly easy to access electronically.
FinRegLab’s study looked at the predictiveness of cash-flow data, its ability to increase access to credit, and its potential fair lending effects. The study was based on data from six nonbank financial services providers – Accion, Brigit, Kabbage, LendUp, Oportun, and Petal – that have begun using cash-flow variables and scores in an effort to provide unsecured credit to consumers and small businesses who may have difficulty obtaining loans from traditional sources. FinRegLab retained Charles River Associates to help design and conduct an independent analysis of the predictiveness of the participants’ cash-flow variables and scores based on actual loan performance.
The study has four main findings:
- General predictiveness: The predictiveness of the cash-flow scores and attributes was generally at least as strong as the traditional credit scores and credit bureau attributes studied. The strength of the results and the nature of the participating companies’ underwriting practices suggest that cash-flow variables and scores can provide meaningful predictive power among populations and products similar to those studied where traditional credit history is not available or reliable.
- Combined models: The cash-flow scores and attributes appeared to separate risk in somewhat different ways than traditional scores and attributes, such that the cash-flow data frequently improved the ability to predict credit risk among borrowers that are scored by traditional systems as presenting similar risk of default. These results occurred across traditional credit score bands.
- Inclusiveness: The participants appear to be serving substantial numbers of borrowers who may have historically faced constraints on their ability to access credit, although data limitations did not permit a consistent quantitative analysis to be applied across all companies. Among participants where such data was available, for example, the percentage of borrowers with traditional credit scores below about 650 was approximately 45 to 50 percent.
- Fair lending effects: When divided into subgroups based on likely race, ethnicity, and gender, the degree to which the cash-flow data predicted credit risk appeared to be relatively consistent across subpopulations. Moreover, when compared to traditional credit scores, the cash-flow based metrics appeared to predict creditworthiness within the subpopulations at least as well as the traditional scores and attributes, and better in selected cases.
FinRegLab will release two additional reports later this summer. One will focus specifically on the use of cash-flow data in small business credit markets, where cash-flow data appears to be spreading more rapidly than in consumer markets. The report synthesizes these recent market developments with FinRegLab’s research results to identify policy issues that may be particularly important in determining the pace and nature of adoption going forward.
The second report will provide broader market context and policy analysis that bridges across consumer and small business markets. In particular, the report will provide a detailed description of market, legal, and policy issues raised by cash-flow based underwriting and by the underlying transfers of data between companies for credit and other purposes. The report builds on three working groups that FinRegLab convened in late 2018 to solicit insight and opinion from more than 80 representatives of fintech companies, banks, data aggregators, advocacy organizations, and research institutions.
FinRegLab was established with generous support from Flourish. Flourish also provided support for FinRegLab’s evaluation of cash-flow data in consumer and small business credit underwriting and the summary report, The Use of Cash-Flow Data in Underwriting Credit: Empirical Research Findings. Additional support for this report was provided by the Milken Institute, which enabled FinRegLab to evaluate cash flow data in small business credit underwriting.
For more information, please contact Kerrigan Molland at kerrigan.molland@finreglab.org.