Enguerrand Horel: Algorithmic Fairness in Lending

Enguerrand Horel: Algorithmic Fairness in Lending

This presentation will start with an overview of fair lending regulations and their influence on the use of machine learning in lending. It will then focus into statistical fairness metrics, emphasizing the practical challenges encountered during their implementation and interpretation. Finally, it will highlight strategies for enhancing the fairness of machine learning algorithms while preserving their accuracy.

Bio: Enguerrand Horel is a Principal Research Scientist at Upstart. He received his PhD from the Institute for Computational and Mathematical Engineering at Stanford University. His research includes applying statistical learning techniques to financial problems such as credit risk prediction, and to develop principled ways to interpret machine learning estimators.