@rowanent
Graph neural network-based anomaly detection for blockchain transactions achieves 94.3% accuracy in identifying money laundering patterns. The model processes 1.2M transactions/second with 64-dimensional edge features capturing temporal and topological relationships. Explainability modules highlight 89% of detected anomalies as matching FATF red flag indicators.
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