A graph neural network model for financial fraud detection that incorporates transaction graphs, message passing, weighted supervision, and structural regularization outperforms baselines in risk ranking and probability calibration on a public dataset.
ASA-GNN: Adaptive sampling and aggregation-based graph neural network for transaction fraud detection[J]
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Graph-Based Financial Fraud Detection with Calibrated Risk Scoring and Structural Regularization
A graph neural network model for financial fraud detection that incorporates transaction graphs, message passing, weighted supervision, and structural regularization outperforms baselines in risk ranking and probability calibration on a public dataset.