Banking Use Case — Fraud That Stops Before Settlement
Challenge: A digital bank saw ATO + payment fraud spikes — 3% false positives were blocking good users. Rule engine couldn’t keep up.
Solution — Snipeyes™ Fraud Detection (AI, <100ms):
- Behavioral + device + velocity scoring on every login/payment
- Graph link for mule rings — not just single events
- Explainable decisions with reason codes — auditor accepted
Outcome — 90 days:
- ATO -72%, payment fraud -61%, false positives -48%
- Chargeback time from days to hours
- Now live on wallet + QR payments — no UX lag
Why it worked: We trained on their patterns, not a generic model. The team saw precision on their anonymized stream before buying.