DERIV
The Challenge: In the high-stakes world of online trading, traditional risk management is often "too little, too late." Sophisticated bad actors use "Smurfing" (rapid-fire small transactions) and complex "Circular Laundering" paths to bypass standard rule-based filters. The Solution: Sentinel is a proactive safety layer designed to sit between the user and the platform, processing every transaction through a multi-stage Hybrid Decision Engine: Behavioral Analysis: A real-time Velocity Engine that identifies bot-like patterns and "Smurfing" attempts by tracking transaction frequency. ML Statistical Scoring: A high-precision model that evaluates 7-dimensional feature payloads to assign a "Probability of Fraud" score based on historical anomaly signatures. Graph Structural Intelligence: A neighborhood-mapping engine that detects structural risk. It identifies circular fund movements and "Laundering Hubs" by analyzing the relationship between senders and receivers in a dynamic graph. The Intelligence Layer: When Sentinel identifies a high-risk event, it doesn't just provide a number. It leverages Forensic AI (LLM) to generate a human-readable "Reasoning" report. This allows security teams to understand the why behind a "CRITICAL" alert instantly.
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