1. Pattern recognition and anomaly detection: Generative AI models can analyze vast amounts of financial transaction data to identify unusual patterns or anomalies that may indicate fraudulent activity. By learning normal transaction behaviors, the AI can flag deviations for further investigation.
2. Natural language processing of documents: AI can rapidly process and extract key information from large volumes of unstructured text like emails, chat logs, and financial documents. This can help investigators quickly sift through data to find relevant evidence and connections.
3. Predictive modeling of criminal networks: By analyzing historical data on known financial crimes, generative AI can create models to predict potential criminal networks or forecast likely future criminal activities. This allows investigators to take a more proactive approach.
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