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Stop bad charges before they become chargebacks

Risk scoring and rules work quietly at authorization time—legitimate shoppers barely notice; risky patterns get challenged or blocked.

How protection shows up

Machine learning plus controls you can tune as you learn your traffic.

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Models trained on payment behavior

Signals from device, velocity, and history combine into a score per attempt.

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Approve, review, or decline—automatically

Set thresholds so obvious fraud never settles and edge cases hit a human queue.

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Rules where you want certainty

Country lists, amount caps, or MCC quirks—codify what you already know about your business.

Decisions in milliseconds

Checkout stays fast for customers who look like customers.

What merchants usually measure

Fewer disputes, fewer manual reviews, more good orders sailing through.

Outcomes teams track

  • High capture of confirmed fraud attempts
  • Material drop in chargeback volume for many merchants
  • Sub-50ms scoring so latency doesn’t tank conversion

Revenue vs. friction

  • Fewer false positives than blunt “block entire countries” rules
  • Lower manual review headcount as automation improves
  • Policies you can adjust without a code deploy

Curious how aggressive to set controls?

We’ll balance your vertical, ticket size, and appetite for review work.

Talk to risk