FinRegLab is working with researchers from Stanford Graduate School of Business to launch a ground-breaking evaluation of emerging market practices to improve the transparency and fairness of machine learning underwriting models in consumer credit.

We recognize the breadth of urgent issues facing the Consumer Financial Protection Bureau and the nation at this time, but believe that resolving critical questions about access to financial data would substantially benefit consumers, small businesses, and financial services providers in helping to recover from the Covid-19 pandemic, address longstanding racial wealth gaps, and make U.S. financial systems more generally inclusive, competitive, and responsive to customer needs.

The Consumer Financial Protection Bureau has issued an advisory opinion concerning the establishment of special purpose credit programs to meet the needs of underserved groups consistent with the Equal Credit Opportunity Act. It is the Bureau’s first action following on a Request for Information about ECOA issues earlier in 2020.

In many smaller American towns banks and credit unions are finding usual sources of loan demand dwindling — and that was before the COVID-19 recession. Community banking institutions may find trouble if they market their credit services further afield. The solution may be to dig deeper for loans in the communities they already know, marketing loans to be evaluated with new alternative data sources (like some fintechs do).

The CFPB issued a blog post noting the potential inclusion benefits of using AI and machine learning models for credit underwriting, as well as risks and compliance challenges with respect to the delivery of “adverse action” disclosures. The agency emphasized the “built-in flexibility” in the regulatory framework and recognized emerging work by lenders and technology companies to enhance the explainability of AI underwriting models.

The CFPB has issued FAQs on implementation of CARES Act requirements concerning pandemic-related credit reporting, as well as the use of special comment codes for disaster effects and forbearances.

The CFPB issued a no-action letter template to the Bank Policy Institute recognizing terms for a standardized, small-dollar credit product, including those designed to function as “guardrails.” The template is intended to ease approval of plans by individual regulated entities to offer a product based on these standardized terms, subject to submission and approval of further information specific to each lender. Underwriting based on the applicant’s cash-flow data is specified among the essential terms set forth for the standardized product.

U.S. prudential regulators recognize the roles that both innovative technologies and data sources such as deposit account activity can play in providing responsible small- dollar loans to consumers and small businesses who do not meet supervised institutions’ traditional underwriting standards.

Resolving data transfer issues could facilitate use of cash-flow data, with particular opportunity to expand access to credit for millions of underserved consumers and small businesses

U.S. regulatory agencies recognize alternative data – and in particular cash flow data – can expand access to credit and produce benefits for consumers