RiskRadar Investigation Copilot

RiskRadar is an AI investigation copilot that helps fraud teams understand risk — not just review data. Today, fraud and financial crime teams are overwhelmed by alerts, and 80–95% turn out to be false positives. Investigators spend 30–90 minutes per case manually reconstructing activity — interpreting transactions, login behavior, device changes, and identity signals just to decide whether fraud actually occurred. RiskRadar shifts investigations from data gathering to decision-ready reasoning. The system ingests raw behavioral events — logins, security changes, withdrawals, device activity, and identity signals — and applies transparent, rule-based detection to surface meaningful risk patterns. On top of these deterministic signals, GenAI produces a clear, investigator-friendly explanation of what likely happened and why it matters. Currently RiskRadar supports Account Takeover (ATO), Digital Identity Fraud (DIF), Money Laundering (ML). Instead of a black-box score, investigators receive: • A clear AI conclusion with confidence • A structured explanation of suspicious or safe behavior • Highlighted key risk signals and timeline context • Suggested next steps for resolution This explainability-first design ensures AI supports human judgment rather than replacing it. Every conclusion is grounded in observable signals, making decisions defensible and auditable. By reducing cognitive load and cutting investigation time by up to 80–90% per case, RiskRadar enables teams to review 4–5× more cases with greater consistency. Faster, more confident decisions can help reduce fraud losses by an estimated 20–40%.