Explainable Machine Learning for Fraud Detection
Ismini Psychoula, Andreas Gutmann, Pradip Mainali, S. H. Lee, Paul Dunphy, Fabien A. P. Petitcolas · Computer · 2021
The application of machine learning to support the processing of large data sets holds promise in many industries. We explore explainability methods in the domain of real-time fraud detection by investigating the selection of appropriate background data sets and runtime tradeoffs on supervised and unsupervised models.