Using Shapley Values to Enable Machine Learning-driven Adverse Action

This paper lays out best practices we have developed to better leverage Shapley values in enabling ML model deployment in credit issuance. Through a variety of analyses and comparisons to existing Adverse Action methodology, we demonstrate how Shapley values can be used to satisfy the Adverse Action requirements and break down a common barrier that lenders face in adopting more sophisticated ML models.