Deriv's compliance teams face 2,100+ fraud alerts weekly, 95% false positives. Each investigation takes 25+ minutes, creating weeks-long backlogs. Meanwhile, fraud rings go undetected because every individual account passes KYC, AML, and risk checks perfectly. The insight: fraud is invisible individually — it's obvious at the network level. LunarGraph maps every entity (partners, sub-affiliates, clients, trades, payments) into a knowledge graph, then deploys three AI agents in parallel: Graph Anomaly Agent — Detects structural patterns like one partner controlling 20+ accounts through layered sub-affiliates sharing IP addresses and device fingerprints. Temporal Intelligence Agent — Identifies coordinated opposite BUY/SELL trades placed within 30-second windows across linked accounts (mirror trading for commission extraction). Behavioral Trajectory Agent — Compares partner behavior against known fraud signatures to predict emerging schemes 2-3 weeks before activation. The platform connects to the real Deriv WebSocket API. Partners invite affiliates via unique referral links, each generating a tracked trading account with a TradingView-style interface. Every trade feeds into the graph engine for real-time correlation analysis. An AI Copilot synthesizes findings into case reports in 28 seconds via natural language queries. Results: 99.86% alert reduction, 28-second case generation (vs 25min manual), 14-day predictive lead time, $178K+ fraud exposure detected across 3 rings and 73 entities.
7 Feb 2026
