This overview highlights key themes from our longer market & data science context report, including the state of machine learning adoption for credit underwriting and key issues in developing and managing machine learning models with regard to explainability and fairness.

This fourth edition of our FAQs focuses on emerging techniques to explain complex models and builds on prior FAQs that covered the use of AI in financial services and the importance of model transparency and explainability in the context of machine learning credit underwriting models.

This third edition of our FAQs considers the technological, market, and policy implications of using federated machine learning to improve risk identification across anti-financial crime disciplines, including in customer onboarding where it may facilitate more accurate and inclusive customer due diligence.

FinRegLab partnered with the Financial Health Network, Flourish Ventures, and Mitchell Sandler to provide a working paper summarizing the current U.S. federal legal framework governing consumer financial data with the goal of laying a foundation for future policy analyses and discussions.

This update catalogues recent initiatives involving the use of non-traditional credit data, including cash-flow information. It considers how dramatic shifts in economic conditions due to the Covid-19 pandemic and mass movements for racial justice have increased incentives to adopt new data sources and models, but also created new market and policy challenges.

This second edition of our FAQs considers more deeply issues and debates about model transparency, explainability, and the implications of using machine learning for credit underwriting.

Concerns about credit reporting and scoring issues are growing as early relief programs start to expire and the focus shifts from short-term forbearance to long-term repayment. This Research Brief updates market and regulatory developments as well as ongoing policy debates.

This Research Brief catalogues uses of new data and technologies to make it easier for small businesses to access federal Paycheck Protection Program (PPP) funds and other forms of credit. Solving PPP enrollment challenges is important to laying the foundation for a rapid and inclusive recovery and to building a more resilient small business sector going forward.

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.