Mitigating Bias in Automated Mortgage Underwriting Models: Evaluating De-Biasing Methods Using Counterfactual Mortgage Application Data

Automated mortgage underwriting models can replicate historical biases in lending decisions, even when prohibited factors like race or ethnicity are not used as predictors. Several methods to de-bias such models are evaluated, including averaging over prohibited variables, maximizing predictions over prohibited groups, and jointly optimizing accuracy and disparity.