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Commerce

Fraud Alert

Add verification friction when transactions or actions look risky. Say why the challenge happened and how to finish legitimate activity. False positives need a fast human or alternate path.

Interactive demo

Overview

How might we design fraud alert so people can trust and act on AI output?

When to use

  • Essential for payment systems, financial applications, and platforms handling sensitive data where AI-powered fraud detection protects users and systems.

When to skip

  • Low-value actions where friction costs more than fraud.
  • Challenges with no recovery path for false positives.
  • Opaque blocks with no support escalation.

Rules

  • Same heavy MFA for every purchase.

  • Decline with no reason code or next step.

  • Training users to approve every prompt blindly.

  • Fraud UI that looks like phishing.

Evidence

ProductImplementation
StripeRadar rules and step-up auth on risky charges.
PayPalSecurity checks and confirm identity flows.
SquareRisk alerts for sellers on anomalous transactions.
Banking appsPush confirm for out-of-pattern card spend.

FAQ

What triggers fraud friction?

Velocity, geo mismatch, device fingerprint, amount anomalies, and merchant category signals.

How explain to user?

We need to verify this payment with plain next steps, not error codes alone.

Fraud vs return prediction?

Fraud flags abuse and theft. Return prediction forecasts product send-backs.

False positives?

Offer alternate verification and fast human review path.