Overview
Our research priorities are informed through engagement with policymakers and with input from industry, academia, and advocate groups. Through our empirical work, market monitoring, and convening activities, we produce timely reports that provide fact-based insights and legal and policy analysis to inform the financial sector.
AI in Financial Services
AI and machine learning are transforming financial services, from underwriting loans and trading securities to customizing products and answering customer questions. These advanced modeling techniques may enhance the accuracy and speed of models used to identify potential customers and assess their risks, expand access to underserved populations, and reduce losses and other costs. But they also carry significant risks—of enhancing bias, eroding data privacy, and obscuring oversight of model’s behavior. FinRegLab’s research is focused on informing both market practice and policy to promote fair, responsive, and inclusive use of AI and machine learning systems across financial services.
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AI & Data for Identity Proofing & Transaction Monitoring
Read more: AI & Data for Identity Proofing & Transaction MonitoringFinRegLab is assessing the potential value of conducting empirical tests and other research to analyze particular data and technology solutions for identity proofing and transaction monitoring to improve financial inclusion and combat bad actors.
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Machine Learning Underwriting Models & Cash-Flow Data
Read more: Machine Learning Underwriting Models & Cash-Flow DataFinRegLab is launching a ground-breaking comparison of the financial inclusion benefits of using machine learning underwriting models with and without cash-flow data to increase responsible access to credit for consumers who may otherwise find it difficult to obtain safe and affordable loans.
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Explainability and Fairness in Machine Learning for Credit Underwriting
Read more: Explainability and Fairness in Machine Learning for Credit UnderwritingFinRegLab worked with a team of researchers from the Stanford Graduate School of Business to evaluate the explainability and fairness of machine learning for credit underwriting. We focused on measuring the ability of currently available model diagnostic tools to provide information about the performance and capabilities of machine learning underwriting models. This research helps stakeholders…
Alternative Data in Credit Underwriting
Millions of consumers and small businesses struggle to access affordable credit because of gaps and weaknesses in traditional financial information systems. FinRegLab is investigating non-traditional data sources to evaluate their effects on predictiveness, fairness, and inclusion, with a particular focus on additional sources of financial data that can be used for credit underwriting.
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Machine Learning Underwriting Models & Cash-Flow Data
Read more: Machine Learning Underwriting Models & Cash-Flow DataFinRegLab is launching a ground-breaking comparison of the financial inclusion benefits of using machine learning underwriting models with and without cash-flow data to increase responsible access to credit for consumers who may otherwise find it difficult to obtain safe and affordable loans.
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The Use of Cash-Flow Data in Underwriting Credit
Read more: The Use of Cash-Flow Data in Underwriting CreditRecords from consumers’ deposit and card accounts and from small businesses’ accounting software can provide a relatively detailed and comprehensive picture of how applicants manage their finances on an ongoing basis. FinRegLab conducted an empirical assessment of the data’s benefits and risks, as well as market and policy analyses of the challenges to its wider…
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Utility, Telecom & Rental Payment History
Read more: Utility, Telecom & Rental Payment HistoryUtility, telecom, and rental payment history can help to assess how credit applicants manage housing and other recurring expenses. FinRegLab and the Urban Institute have examined available research, historical and recent initiatives to increase data access and use for credit underwriting, and market and policy issues that will determine whether such efforts can reach scale.
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Innovations for Underwriting Minority and Small Business Enterprises
Read more: Innovations for Underwriting Minority and Small Business EnterprisesFinRegLab is investigating ways to improve credit access for minority-owned companies and other underserved small businesses through the use of non-traditional data sources and mission-based lenders.
Building inclusive recoveries
The COVID-19 pandemic has highlighted how households’ and small businesses’ ability to rebound from financial shocks affects not only their own future financial health, but the nation’s broader racial wealth gaps and economic resiliency. FinRegLab is investigating the use of data and technology innovations and other strategies to promote faster, more inclusive recoveries.
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Debt Management Insights for Distressed Borrowers
Read more: Debt Management Insights for Distressed BorrowersFinRegLab is working with teams at The Ohio State University and Charles River Associates to evaluate new workout structures and data and technology applications for consumers who are struggling with unsecured credit. The project will use data from pilots organized by the National Foundation for Credit Counseling and other sources.
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COVID-19 Triage (Series)
Read more: COVID-19 Triage (Series)Rapidly adjusting credit reporting and underwriting practices and processing small businesses’ Paycheck Protection Program applications posed substantial challenges in the first months of the pandemic. In 2020, FinRegLab produced a series of research briefs highlighting emerging issues and innovations.
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Data for Underwriting MSEs in Emerging Markets
Read more: Data for Underwriting MSEs in Emerging MarketsFinRegLab is investigating the financial inclusion and consumer protection implications of using new data sources for credit underwriting of micro and small enterprises (MSEs) in Kenya with a particular focus on women-owned small businesses.
Recent Publications
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This landscape paper details gaps in traditional systems that both make it difficult for millions of consumers to access financial services and for financial institutions to detect and protect against bad actors. The paper also summarizes emerging data and technological developments, concluding that more stakeholder engagement is critical as financial institutions make substantial investments to…
LEARN MORE: Innovations for Identity Proofing and Transaction Monitoring: Advancing Financial Inclusion Through Data & Technology -
This report details the experiences of mission-based lenders such as community development financial institutions (CDFIs) and minority depository institutions (MDIs) as they adopt electronic bank account data and lending platforms to increase lending to minority-owned businesses and other underserved entrepreneurs. The paper provides both a practical snapshot of how lenders manage data and technology adoption…
LEARN MORE: Transforming Small Business Credit: Technology and Data Adoption in Mission-Based Lending -
This report delves into the evolving landscape of small business lending following the pandemic, identifying significant trends that are shaping the lending ecosystem. As the economy improves, lenders will face critical decisions about how to meet the capital needs of more small businesses, including record numbers of minority- and women-owned startups since 2020.
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The market context report finds that current market conditions may present a unique window to build on substantial interest among industry, advocates, and policymakers in using non-conventional data sources such as digital wallet information and supply chain records for credit scoring and underwriting.
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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.
FinRegLab Events & Webinars
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Harnessing Data and Technology for Financial Inclusion in Identity Verification and Transaction Monitoring
Read more: Harnessing Data and Technology for Financial Inclusion in Identity Verification and Transaction MonitoringFinRegLab co-hosted a convening with the Aspen Institute Financial Security Program for a level-setting conversation about challenges in identity proofing and transaction monitoring, their impacts for consumers’ financial access and stability, and emerging data and technology trends. Learn More
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2024 FinRegLab AI Symposium
Read more: 2024 FinRegLab AI SymposiumThe 2024 FinRegLab AI Symposium presents an unparalleled opportunity for dialogue and collaboration at the intersection of financial services, technology, public policy, and social and economic impact.
About FinregLab
FinRegLab is an independent, nonprofit organization that conducts research and experiments with new technologies and data to drive the financial sector toward a responsible and inclusive marketplace. The organization also facilitates discourse across the financial ecosystem to inform public policy and market practices. To receive periodic updates on the latest research, subscribe to FRL’s newsletter and visit www.finreglab.org. Follow FinRegLab on LinkedIn.
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