Build, Run and Manage Risk Models for Performance, Bias, and Explainability

Abstract: For lenders, additional factors in an applicant's credit history create an opportunity to extend services to a larger, more diverse pool of borrowers, but they also introduce a greater likelihood of unexpected correlations and potential bias based on an applicant’s age, gender and other personal traits. Join this workshop to learn how lenders can avoid black box AI and opaque predictions, limit risk exposure from regulations, and ultimately create more fair and explainable outcomes for customers.

Bio: Coming soon!