This policy analysis explores the regulatory and public policy implications of the increasing use of machine learning models and explainability and fairness techniques for credit underwriting in depth, particularly for model risk management, consumer disclosures, and fair lending compliance.

This additional study of COVID-19 loan forbearances probes the benefits of combining short-term payment relief with longer term assistance plans for the most vulnerable consumers struggling with credit card debt.

This additional study of COVID-19 loan forbearances probes the benefits of combining short-term payment relief with longer term assistance plans for the most vulnerable consumers struggling with credit card debt.

This working paper focuses on consumers who struggled to manage credit card and other unsecured debt during the pandemic, analyzing the extent to which consumers obtained card and other forbearances from lenders and shifts in patterns of consumers who sought credit counseling and enrolled in debt management plans through September 2021.

FinRegLab research highlights the benefits of combining short-term payment relief with longer term assistance plans for the most vulnerable of consumers struggling with credit card debt.

This research brief highlights the need for consumer engagement and administrative flexibility to help distressed borrowers transition smoothly into longer-term repayment plans as pandemic deferral programs end and new programs are implemented.

FinRegLab research finds that tools for managing explainability and fairness in machine learning underwriting models hold promise and that regulatory guidance could encourage more consistent, responsible use.

This paper summarizes the machine learning project’s key empirical research findings and discusses the regulatory and public policy implications to be considered with the increasing use of machine learning models and explainability and fairness techniques.

This empirical white paper assesses the capabilities and limitations of available model diagnostic tools in helping lenders manage machine learning underwriting models. It focuses on the tools’ production of information relevant to adverse action, fair lending, and model risk management requirements.

This report surveys the options that are available to consumers who are struggling with unsecured debt, including available research on the options’ scope and outcomes. It provides an overview of market and policy challenges as stakeholders ponder strategies to help consumers recover more quickly from personal and broader economic crises such as COVID-19.