Explainable Machine Learning for Fraud Detection

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.