FRAUD DETECTION
repeat-attempt evidence for abuse review
Problem
Attackers can rotate account details, emails, phone numbers, IPs, and browser storage. A fraud system that only looks at one of those fields misses repeated attempts that are connected by device evidence.
How fingerprint.dev helps
Attach visitor_id and confidence to signup, login, checkout, and payout attempts.
Look for repeat visitors across blocked accounts, failed payments, chargebacks, or policy violations.
Allow, throttle, step up, or send to manual review based on your own risk model.
Signals to combine
Same visitor appears behind multiple accounts.
Many attempts occur in a short window.
Email, payment, or profile details overlap with prior abuse.
Origin, route, geography, and session behavior do not match the expected flow.
Decision model
A matching visitor should not automatically mean fraud. Use the confidence score as one input alongside your own account, payment, velocity, and support history.
start identifying implementation guide