Every order scored at checkout. Every pattern detected in milliseconds. Cellix's ML models analyze transaction velocity, device fingerprints, and cross-merchant intelligence to stop fraud before it becomes a chargeback.
From checkout to fulfillment, every order passes through a multi-layer scoring pipeline that learns and improves with every transaction.
Each transaction is evaluated against 8+ signal categories in under 100 milliseconds — address verification, velocity patterns, device fingerprints, customer history, and BIN intelligence.
Each risk tier maps to an action. Low risk auto-approves. Medium requires monitoring. High triggers review. Critical blocks automatically. You customize the thresholds.
Every outcome feeds back into the model. Chargebacks that slip through train better detection. Blocked legitimate orders reduce false positives. The system gets smarter with every transaction.
Every order scored, every risk quantified, every action logged.
Six integrated modules working together to detect, block, and learn from every fraudulent transaction.
Real-time scoring powered by models trained on millions of transactions. Transparent factor breakdown for every decision.
Detect rapid-fire orders, card testing, and coordinated fraud ring activity across accounts and payment methods.
Card-level risk assessment using issuer data, BIN reputation, and cross-network signals from millions of transactions.
Track device signatures across sessions. Detect account linking, synthetic identities, and multi-account fraud patterns.
Auto-block known bad actors by email, IP, device, address, or payment method across all connected PSPs.
Track blocked orders, false positive rates, and model accuracy. Optimize thresholds with real-time performance data.
Start scoring orders in minutes. No integration changes required.