Building on their report about the use of utility, telecommunications and rental payments history for credit underwriting, FinRegLab and the Urban Institute hosted a webinar in April 2022 to examine the current state of play and the evolving policy landscape. Leaders from the field discussed data access and quality and how to build more robust scoring and underwriting models.
Podcasts
Arthur – Adam Wenchel, CEO
Arthur’s Adam Wenchel discusses regulation’s effect on AI underwriting models & the need for explainability & fairness.
We discuss ways to improve the fairness of AI/ML models with Michael Akinwumi, Talia Gillis, & Peter Zorn.
We discuss how lenders approach model fairness with Stephen Hayes, Deborah Hellman & Manish Raghavan.
Testimony & Comment Letters
FinRegLab Responds to Comments on Proposed Third-Party Relationships Guidance
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.
We discuss interpretable ML models and their significance to the financial sector with Agus Sudjianto and Scott Zoldi.
We discuss ML explainability in credit underwriting with John Dickerson (UMD) and Patrick Hall (bnh.ai).
We discuss the evolution of data science and the current landscape of explainability with Microsoft’s Scott Lundberg.
Machine learning models are being used to evaluate the creditworthiness of tens of thousands of consumers and small business owners each week in the U.S., increasing the urgency of answering key questions about their performance, governance, and regulation.
“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.”