<ul><li>This study proposes a credit card fraud detection method based on Heterogeneous Graph Neural Network (HGNN) to address fraud in complex transaction networks.</li><li>The approach constructs heterogeneous transaction graphs incorporating multiple node types: users, merchants, and transactions.</li><li>The model uses graph neural networks to capture higher-order transaction relationships and employs a Graph Attention Mechanism to assign weights dynamically.</li><li>The proposed method outperforms existing GNN models on the IEEE-CIS Fraud Detection dataset, achieving notable improvements in accuracy and OC-ROC.</li></ul>

Detecting Credit Card Fraud via Heterogeneous Graph Neural Networks with Graph Attention

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