This first edition of our FAQs addresses a range of introductory questions about AI and machine learning.

This Research Brief analyzes the current options under consideration for addressing concerns that declining credit scores could make it harder for consumers and small businesses to access the credit they need to ride out and rebuild from the pandemic, as well as providing related historical and market context.

This report provides a detailed snapshot of the use of cash-flow data in U.S. consumer lending and the development of the system for transferring data between firms, in addition to analyzing policy and regulatory issues raised by cash-flow underwriting in both consumer and small business credit markets.

This overview highlights key themes from our longer market context and policy analysis, including outlining options for action by industry, regulators, and Congress.

FinRegLab research finds that resolving data transfer issues could facilitate use of cash-flow data for credit underwriting, with particular opportunity to expand access for millions of underserved consumers and small businesses.

FinRegLab research finds that cash-flow information is being used by both new entrants and traditional lenders to extend smaller loans to smaller businesses and to increase credit to underserved borrowers.

This report details the evolution of the use of cash-flow data in small business lending. It explains the reasons why electronic cash-flow data may be particularly useful in the small business context, presents evidence of its increasing use by a diverse range of incumbents and new entrants, and notes market and policy issues that may affect the nature and pace of further expansion.

FinRegLab research finds that cash-flow data can help both to underwrite applicants who lack traditional credit history and improve risk scoring among borrowers who are ranked similarly by traditional scoring systems.

We conducted an independent analysis of data from six firms that use cash-flow metrics to assess consumer and small business applicants. Using loan level performance data, we evaluated the information’s implications for predictiveness, inclusion, and fairness.