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A new report by FinRegLab underscores the importance of continuing technology and data improvements to expand credit access among smaller, younger businesses. From Crisis to Opportunity: Financing for Underserved Small Businesses since COVID-19 analyzes recent lending trends, including initiatives focusing on underserved businesses, lender technology adoption, and the effect of high inflation and interest rates on both loan demand and supply. 
FinRegLab announced that it is conducting new empirical research to evaluate the inclusion impact of machine learning credit models, including those built with bank account data as well as traditional credit report information. The organization has also been invited by the Office of the Comptroller of the Currency (OCC) to co-chair a new Technology Working Group within the OCC’s Project REACh initiative.
A new report by FinRegLab details strategies for improving data sources for credit scoring and underwriting of Kenyan micro and small enterprises (MSEs), finding that tapping multiple non-conventional (or alternative) data sources is particularly important to expanding credit access and growth among women-owned MSEs.
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.
FinRegLab is extending its investigation of the adoption of artificial intelligence in financial services through a policy analysis focused on the growing use of machine learning models for underwriting credit and a January 17 webinar with senior federal financial regulators to discuss generative AI and other recent developments.
“Melissa discusses her organization’s work in evaluating the explainability of complex machine learning algorithms in credit underwriting, model governance and adverse action notices. The conversation covers the CFPB’s recent guidance on credit denial by lenders using artificial intelligence as well as the role explainability plays in promoting fairness and inclusion in lending, methods and tools emerging for lenders to explain credit-related decisions based on AI models, and the ongoing work required to adapt to the digital economy and evolving regulatory landscape.”