A new report by FinRegLab traces institutions’ growing use of new data sources, artificial intelligence, and other innovations in identity proofing and financial crimes monitoring, highlighting the potential benefits and risks to consumers particularly as the sector responds to escalating fraud and scams activity since the pandemic.
Speaking Engagements & Conferences
Harnessing Data and Technology for Financial Inclusion in Identity Verification and Transaction Monitoring
FinRegLab 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
Mission-based lenders are increasingly using electronic bank account data and technology platforms to expand credit access to underserved entrepreneurs, according to a new FinRegLab working paper that details both current practices and future challenges as lenders work to scale their lending programs. Transforming Small Business Credit: Technology and Data Adoption in Mission-Based Lending focuses on […]
The 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.
Speaking Engagements & Conferences
2024 National Minority Enterprise Development Week
www.nmsdcconference.orgSpeaking Engagements & Conferences
National Bankers Association 2024 Conference
www.nationalbankers.orgSpeaking Engagements & Conferences
Revolutionizing Homeownership: Innovations in Mortgage Tech, AI, and Data
www.eventbrite.comTestimony & Comment Letters
FinRegLab Responds to Treasury Request for Information on Artificial Intelligence
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.