Credit Scores vs Bank Data: Why Lenders Are Switching

Episode notes

Cash flow underwriting, explainable AI, and credit risk analytics are changing how lenders approve borrowers and set loan terms. Tedd Huff, CEO of fintech advisory firm Voalyre and founder of Fintech Confidential, sits down with Jamie Twiss, CEO of Carrington Labs, and Kasey Kaplan, Chief Product and Commercial Officer, to break down how behavioral signals in bank transaction data outperform traditional credit scores. Over 50 percent of loan applicants cannot produce a reliable credit score, leaving self-employed workers, gig earners, and younger borrowers locked out of the system. Carrington Labs uses billions of lines of transaction data to build personalized, explainable machine learning models per lender, per product, and per customer segment. The conversation covers their "control point" approach to AI, lifecycle underwriting beyond origination, open banking friction in the US, and a five-year outlook on embedded, agent-driven lending. FIND OUT MORE 1️⃣ Map analytics to every step of your lending funnel to find exactly where borrowers drop off and why. 2️⃣ Buy best-of-breed origination and servicing tools instead of building proprietary underwriting tech in-house.

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