Real-time fraud detection at 10TB+ daily

Challenge

Legacy rule-based fraud detection missed sophisticated patterns across multi-terabyte daily transaction flows. Prior AI consultancies delivered strategy decks; internal POCs stalled for months.

KPI targets

• Process 100% of transaction volume in real time
• Sub-second inference p99
• Reduce false-positive review queue by 30%

Approach

1. 1.Week 1: KPI lock and data audit; confirmed ML was the right tool vs. rule expansion
2. 2.Week 2–3: Feature pipeline + ensemble model training on historical labeled data
3. 3.Week 4–5: Real-time serving integration, shadow mode, and governance documentation
4. 4.Week 6: Production cutover with drift monitoring and on-call runbook

Production artifacts

• Streaming feature pipeline with CI/CD
• Model serving API with shadow/canary deploy
• Drift detection dashboards and PagerDuty alerts
• Model cards and audit trail for compliance review
• Runbook for retraining and rollback

Outcomes

• Full transaction volume scored in real time
• Months of stalled POCs replaced with production in six weeks
• Client team trained on pipeline operations before close

Stack