Fraud-Preserving Dual-Horizon Temporal Heterogeneous Graph Contrastive Learning for Credit Card Fraud Detection
On a 30,000-event synthetic stream with a 2.40% overall fraud rate, the proposed dual-horizon FPAA model achieves an average precision of 0.427 ± 0.038 across three training seeds.