We have been following the various technologies impacting corporate banking and payments, which includes applications around various types of lending, particularly associated with trade finance. Increasingly, we see utilization of non-traditional means of assessing credit worthiness, which is generally concentrated in the non-bank lending space.
This referenced article appears in American Banker and discusses an early analysis of non-bank lending data by FinRegLab, which, by its own words, is “a nonprofit innovation center that tests new technologies and data to inform public policy and drive the financial sector toward a responsible and inclusive financial marketplace.” It is funded by several organizations, including the Milken Institute (some may remember the infamous Michael Milken, king of the junk bonds, who has changed the direction of his life).
“FinRegLab, a nonprofit that tests new technologies to foster an “inclusive financial marketplace” analyzed the data of six nonbank lenders that use cash-flow data in their underwriting: Accion, Brigit, Kabbage, LendUp, Oportun and Petal….While acknowledging the limitations of their analysis to date, including that the study doesn’t reflect the full U.S. population and range of financial services products available, the nonprofit found encouraging indications that cash-flow analysis can be used as a predictor of creditworthiness on its own and in combination with credit scores.”
While the article only summarizes at a high level and is concentrated on individuals (consumers), generally speaking, we believe the same principles are applicable to business lending. You can see this across alternative marketplace lending for small businesses in the U.S. (and elsewhere of course), which we have estimated to be in the $30-50 billion annual range. The use of AI is also a more commonly used practice, and, of course, banks must be wary of regulatory scrutiny.
Readers can download the empirical research at this link, which is a 32 page report with about 170 additional pages of data, etc. but the last sentence conclusion holds that “On balance, the results suggest that cash-flow metrics when used alone or in combination with more traditional credit reports and scoring models hold substantial promise for improving credit risk prediction, expanding access to credit, and spurring market innovation and competition.”
The article is worth a quick read, and of course the longer report (should you choose to accept the mission) will require just a bit more time.
“We talk to a lot of different financial firms and bank and nonbank lenders, and there are lots of arguments made for trying out new data or trying out new methods for underwriting,” said Melissa Koide, founder and CEO of FinRegLab. “But when you’re sitting on the government side, what you really want to know and have are fact-based insights to help then empirically evaluate the benefits and risks associated with new types of data. We undertook this research to generate those independent fact-based analyses so that regulators, policymakers and the banking and fintech industry have more facts to then think about where there may be opportunities and value of evolving regulations.”
Overview by Steve Murphy, Director, Commercial and Enterprise Payments Advisory Service at Mercator Advisory Group
