Accuracy of Explanations of Machine Learning Models for Credit Decisions
This white paper creates a framework for using synthetic data sets to assess the accuracy of interpretability techniques as applied to machine learning models in finance. The authors controlled actual feature importance using a synthetic data set and then compared the outputs of two popular interpretability techniques to determine which was better at identifying relevant features, finding variation in results.
Andrés Alonso and José Manuel Carbó, Banco de España
June 2022