Third party vendor fraud risk assessment using shapley additive explanations for value attribution

Abstract

A method for managing value attribution for a data system includes obtaining, by the data system, order data associated with a plurality of data vendors, wherein the order data comprises variables about client devices, in response to obtaining the order data: applying the variables in the order data to a classification model to obtain fraud prediction models, performing an explainable mechanism on the fraud classification predictions using a shapley additive explanation (SHAP) to obtain localized SHAP values, applying a set of custom transformations to obtain normalized features, applying a value attribution algorithm on the normalized features using vendor information associated with the order data to obtain vendor values each associated with one of the plurality of data vendors, and performing a vendor remediation on the plurality of data vendors based on the obtained vendor values.