Real-Time Fraud Detection

Static rules catch the fraud patterns that were understood when the rules were written, and fraudsters iterate faster than change control.

• 1Static rules catching only previously understood fraud patterns
• 2Novel attack patterns passing until losses accumulate enough to notice
• 3Money-laundering networks invisible to rules that evaluate single transactions

CloudGate builds a hybrid detection engine combining deterministic rules, machine learning models and graph analytics, scoring every transaction in under 100 milliseconds against behavioral baselines for that customer, device and counterparty.

• Hybrid engine combining rules, machine learning and graph analytics
• Sub-100ms scoring on every transaction across all channels and rails
• Behavioral baselines per customer, device, counterparty and channel

Typical outcomes for this solution pattern, not the results of a named client engagement.