In addition to credit underwriting, FinRegLab’s comment letter highlights three AI use cases with particularly important financial inclusion implications: (1) delivery of financial advice and coaching; (2) identity verification, fraud detection, and anti-money laundering activities; and (3) back-office applications to increase the nimbleness of model and product development.

FinRegLab Deputy Director Kelly Cochran joins RegFi cohosts Jerry Buckley and Caroline Stapleton for a conversation about how machine learning – including generative artificial intelligence – is used by consumer lenders and the evolving regulatory response. Kelly begins with a helpful distinction between the technologies commonly included under the broad “AI” moniker, noting that many of these algorithmic models are not new to credit underwriting. The discussion then pivots to the growing focus on generative AI and the need to balance its potential benefits with consumer protection, data privacy and explainability considerations. Kelly suggests that existing rules in the financial services regulatory framework can be adapted to address many of these issues and serve as a model for AI policymaking in other sectors.

Over the past three decades, customer-permissioned data flows have become critical to a growing range of consumer financial products and services as well as to public research focusing on household financial health, markets for consumer financial products and services, and the role of consumer financial activity in the nation’s economy.

A new research paper underscores the importance of evaluating whether the most vulnerable and distressed borrowers need longer term repayment plans soon after they first enroll in natural disaster or other emergency relief programs with credit card lenders.

FinRegLab today issued a research brief entitled “The Countdown Clock for Student Loan Forbearances” that highlights the need for quick action by consumers, federal agencies, servicers, and counselors to prepare for the August 2023 end of pandemic-era forbearances on federal student loans.

These data flows are critical to a growing range of consumer financial products and services. Modernizing the regulatory frameworks governing these flows is important both to mitigate current risks and frictions and to encourage future applications that produce greater inclusion, competition, and customer-friendly innovation, particularly for historically underserved consumers.

A new study finds that more consumers obtained short-term payment relief on their credit cards during the first 18 months of the pandemic than on any other type of loan except student debt, where forbearances were mandated by federal law. The study also finds evidence that pandemic relief initiatives may have reduced damage to the credit reports of consumers who sought long-term assistance through credit counseling and debt management programs.

Coordinated action is critical between federal regulators to continue moving the growing ecosystem for customer-directed transfers toward adoption of safer technologies and practices without undermining consumers’ § 1033 rights or frustrating the law’s potential benefits for competition and innovation.

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.

The growth and use of data is increasing exponentially in the American economy and specifically within its financial systems. This data has the potential to benefit consumers and the broader economy in myriad ways.