Real-Time Fraud Detection

Typical outcomes for this kind of engagement. Results depend on your data and starting point.

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

• Static rules catching only previously understood fraud patterns
• Novel attack patterns passing until losses accumulate enough to notice
• Money-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