Fraud Detection

Transaction risk monitoring systems make real-time decisions (100ms) to avoid business losses because of fraudulent activity, but suffer from immense operational costs due to false positives.

• Problem: Real-Time systems' accuracy are constrained by average latency budget.
• With moco: Create rule to identify transactions that can avoid model execution.
• Impact: Reduced compute required for easy transactions -> enabling intelligence + better features where they're needed.
• Outcome: Enables additional model capacity and feature complexity within existing latency constraints.

Credit Card Fraud Detection — Inference Acceleration

Delivered a 55% speed-up and major FLOP reduction on a production-style fraud classifier.