كشف الاحتيال بالذكاء الاصطناعي

Fraud datasets are often highly imbalanced, and patterns can change as behavior and controls evolve. Graph models represent relations among entities and transactions, which can help detect network patterns in a defined dataset. Performance depends on data coverage, label delay, and graph construction. A score does not establish misconduct; suspicious-activity reporting and investigative duties follow applicable rules. Graph fraud methods can represent relationships among transactions and entities, but a GNN study notes that neighbor message propagation and network hubs can amplify class-imbalance effects; linked accounts are not proof of guilt. FinCEN’s November 2024 alert describes deepfake media and fraudulent identity documents used in suspected schemes to evade identity verification or authentication. Investigators must review alerts; models and signals do not establish legal culpability.