Welcome back to Model Citizens: AI Compliance for Banks and Fintech Lenders, a six-part miniseries from the Fintech Takes podcast in partnership with FairPlay.
With FairPlay’s Kareem Saleh (Founder & CEO) at my side, we unpack: how can banks and fintechs build fair, compliant lending systems in a time of regulatory uncertainty?
In Episode 2, we’re joined by Kevin Moss (Senior Advisor at Baselayer, former CRO) and Andrada Pacheco (EVP & Chief Data Scientist at VantageScore) to explore how AI is reshaping credit modeling, and where caution is still very much required.
We trace the evolution from decision trees and logistic regression to gradient boosting, cash flow data, and the emergence of AI. Along the way, we tackle the core dilemma: how to boost predictive power without losing explainability or fairness.
Highlights include:
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AI isn’t new in credit risk modeling; tree-based methods like CART, CHAID, and gradient boosting have been around for decades (what’s changing now is the scale, the data, and the complexity)
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LLMs are great for fraud, operations, and consumer education, but they’re not safe for credit decisions just yet)
We close with a reminder: credit modeling doesn’t just need to be effective. It needs to be explainable, equitable, and defensible; especially as AI raises the stakes.
Don’t forget to subscribe and catch more insights on Model Citizens in upcoming episodes!
This miniseries is brought to you by FairPlay.
FairPlay is an AI enablement company for financial services. They help companies build, test, optimize, validate and govern AI models. Learn more at Fairplay.ai
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https://www.linkedin.com/in/andrada-pacheco-ph-d-26731a1/
Learn more about FairPlay here.
