The Board of Governors of the Federal Reserve System, the Federal Deposit Insurance Corporation, and the Office of the Comptroller of the Currency released a guide for community banks on conducting diligence of financial technology companies. Drawing on existing guidance that articulates risk management expectations for third-party relationships, the guide highlights areas where required diligence processes can be adapted to reflect constraints related to doing business with early or expansion stage companies.

“I believe we’ve reached a crossroads in consumer finance, where things will probably get either much better, or much worse, due to the technological transformation of products, providers, cost structures, business and market models, and infrastructure.”

As recent developments have renewed interest in harnessing new data and analytical techniques for credit underwriting, stakeholders are asking questions about potential benefits and risks particularly for addressing racial equity issues. FinRegLab Deputy Director Kelly Thompson Cochran wrote an article summarizing recent initiatives and issues for an edition of the Community Development Innovation Review titled “Fintech, Racial Equity, and an Inclusive Financial System” that has been published by the Federal Reserve Bank of San Francisco and the Aspen Institute.

FinRegLab’s forthcoming research will help to inform the extent to which current laws and regulations are able to be satisfied in light of the emergence of more complex underwriting models, how well tools to develop and monitor those models perform in identifying effective ways to pursue greater inclusion and fairness, and considerations for policy and market developments that can support the safe, inclusive, and nondiscriminatory adoption of machine learning.

FinRegLab CEO Melissa Koide testified in the Task Force’s hearing on “Equitable Algorithms: How Human-Centered AI Can Address Systemic Racism and Racial Justice in Housing and Financial Services.”

We discuss fairness and explainability with Jay Budzik – Chief Technology Officer of Zest AI.

We discuss the need to combine insights from data scientists and from credit risk and compliance managers when vetting ML models with Laura Kornhauser, cofounder and CEO of Stratyfy.

We discuss causal inference in machine learning with Molham Aref – CEO of Relational.AI.

We discuss managing risks of bias in historical data when using ML models with Sri Ambati, cofounder and CEO of H2O.ai.

We discuss the evolution of risk monitoring and machine learning with Krishna Gade, founder and CEO of Fiddler Labs.