Fraud, filtered. Approvals, maximised.
A streaming risk engine that scores every authorisation in milliseconds, learns from your traffic, and routes only the right transactions to step-up authentication.
What you get
ML risk scoring
Real-time models trained on multi-merchant signals, with explainable risk reasons.
Velocity rules
Per-card, per-IP, per-device, per-email controls with sliding windows.
Device fingerprinting
Stable device identifiers across sessions to detect mass-test attacks early.
3-D Secure 2 routing
Send only ambiguous transactions for step-up; keep low-risk traffic frictionless.
Allow / block lists
Merchant-managed lists for known good or bad cards, customers, BINs and countries.
Manual review
Optional review queue with case management for borderline transactions.
From integration to settlement
- Step 1
Signal
We collect 100+ signals per authorisation — device, behavioural, network, historical.
- Step 2
Score
Streaming ML score returned in under 50ms with reason codes.
- Step 3
Decide
Approve, step-up via 3DS, send to manual review, or block — based on your policy.
- Step 4
Learn
Outcomes feed back into the model continuously, sharpening accuracy on your traffic.