Explainable Fraud Detection with GNNExplainer and Shapley Values
This addresses the need for transparent AI systems in fraud detection for regulators and analysts, but it appears incremental as it builds on existing explainability methods.
The paper tackled the problem of increasing financial fraud in digital payments by developing an explainable fraud detector to meet transparency standards and aid fraud analysts, but no concrete results or numbers were provided.
The risk of financial fraud is increasing as digital payments are used more and more frequently. Although the use of artificial intelligence systems for fraud detection is widespread, society and regulators have raised the standards for these systems' transparency for reliability verification purposes. To increase their effectiveness in conducting fraud investigations, fraud analysts also profit from having concise and understandable explanations. To solve these challenges, the paper will concentrate on developing an explainable fraud detector.