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Advancing the Safe & Smart use of Technology & Data in Financial Services

FinRegLab


    • Mar 15, 2022 LATEST EPISODE
    • infrequent NEW EPISODES
    • 43m AVG DURATION
    • 6 EPISODES


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    Latest episodes from FinRegLab Podcasts

    #6: Arthur – Adam Wenchel, CEO

    Play Episode Listen Later Mar 15, 2022 34:10


    Arthur's Adam Wenchel discusses regulation's effect on AI underwriting models & the need for explainability & fairness.

    ai
    #5: Michael Akinwumi/Talia Gillis/Peter Zorn: Reimagining Fairness in AI/ML Underwriting Models

    Play Episode Listen Later Dec 21, 2021 57:50


    We discuss ways to improve the fairness of AI/ML models with Michael Akinwumi, Talia Gillis & Peter Zorn.

    models reimagining fairness zorn gillis ai ml underwriting
    #4: Stephen Hayes/Deborah Hellman/Manish Raghavan: Measuring Fairness in AI/ML Underwriting Models

    Play Episode Listen Later Nov 16, 2021 48:20


    We discuss how lenders approach model fairness with Stephen Hayes, Deborah Hellman & Manish Raghavan.

    models measuring fairness ai ml underwriting manish hellman raghavan stephen hayes
    #3: Agus Sudjianto / Scott Zoldi: The Case for Interpretable Models in Credit Underwriting

    Play Episode Listen Later Oct 6, 2021 50:29


    We discuss interpretable ML models and their significance to the financial sector with Agus Sudjianto and Scott Zoldi.

    credit models ml underwriting agus
    #2: John Dickerson / Patrick Hall: The Current State of ML Explainability

    Play Episode Listen Later Oct 6, 2021 37:03


    We discuss ML explainability in credit underwriting with John Dickerson (UMD) and Patrick Hall (bnh.ai). 

    2john current state ml john dickerson explainability patrick hall
    #1: Scott Lundberg: The Evolution of the Data Science of Explainability

    Play Episode Listen Later Oct 1, 2021 34:43


    We discuss the evolution of data science and the current landscape of explainability with Microsoft's Scott Lundberg.

    microsoft evolution data science lundberg explainability

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