Explainable Fraud Detection with GNNExplainer and Shapley Values

• URL: http://arxiv.org/abs/2509.12262v1
• Date: Fri, 12 Sep 2025 20:00:36 GMT
• Title: Explainable Fraud Detection with GNNExplainer and Shapley Values
• Authors: Ngoc Hieu Dao,
• Abstract summary: The risk of financial fraud is increasing as digital payments are used more and more frequently.<n>Society and regulators have raised the standards for these systems' transparency for reliability verification purposes.<n>To increase their effectiveness in conducting fraud investigations, fraud analysts also profit from having concise and understandable explanations.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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