A three-component fusion architecture of LSTM, statistical, and graph modules detects fraud and AML on synthetic banking data with F1 scores of 0.787 (transactions) and 0.867 (sessions), outperforming rule-based and LSTM-only baselines.
A finan- cial fraud detection model based on LSTM deep learning tech- nique,
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An AI Security Agent for Banking: Multi-Vector Fraud and AML Detection Across Retail and Corporate Accounts
A three-component fusion architecture of LSTM, statistical, and graph modules detects fraud and AML on synthetic banking data with F1 scores of 0.787 (transactions) and 0.867 (sessions), outperforming rule-based and LSTM-only baselines.