InferX scores every transaction in under 50ms using adaptive ML models trained on payment-specific behavioral signals. No rules engine required.
Generic fraud tools miss the patterns that matter in payment flows. InferX was designed from scratch for the specific data structures, velocities, and attack vectors your infrastructure faces.
Every transaction receives a fraud risk score between 0-1000 in under 50ms via REST or gRPC. Scores update continuously as new signals arrive from connected data sources.
Models retrain on your transaction history every 6 hours. When fraud patterns shift — new card testing attacks, burst velocity fraud — InferX recalibrates without manual rule updates.
Ingests device fingerprints, IP reputation, typing velocity, session duration, and 200+ behavioral attributes. Correlates these across transactions to identify account takeover and synthetic identity patterns.
Maps relationships between merchants, cards, devices, and accounts. Detects fraud rings and organized card-testing campaigns that individual transaction analysis misses entirely.
Set accept, review, and decline thresholds per merchant category, transaction amount, or geography. Changes take effect in under 2 minutes — no code deployment required.
Every score includes the top 5 contributing factors in human-readable format. Dispute resolution teams get the specific signals that triggered each decision, not just a number.
Most payment processors are scoring live transactions within 5 business days. The REST API follows the same request structure as major payment gateways.
Send transaction events to the InferX ingest endpoint via REST API or Kafka consumer. Supports Stripe, Adyen, Braintree, and custom payment gateway schemas.
Upload 90 days of historical transaction data. InferX trains your initial model on your specific merchant mix, ticket sizes, and known fraud labels.
Each authorization request calls the InferX scoring endpoint. Sub-50ms response includes risk score, decision recommendation, and contributing signal breakdown.
Use the dashboard to review flagged transactions, submit outcome labels, and adjust thresholds. Model accuracy improves continuously from your feedback loop.
Most fraud platforms were built for e-commerce merchants and retrofitted for payment processors. InferX was built the other way: starting from interchange data, BIN tables, and processor-specific velocity patterns.
The result: 60% fewer false positives compared to rule-based systems, and a false positive rate below 0.3% on real production deployments. Your approval rates improve. Your chargeback ratios drop.
Explore the Platform
Three plans built for different processing volumes. All plans include full API access, real-time scoring, and the core ML pipeline. No setup fees.
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