{"id":"8696c7a8-cc95-4929-bd33-29d5371dcc36","task":"Build Radar custom rules to block high-risk transactions based on fraud signals in Stripe","domain":"docs.stripe.com","steps":["Identify fraud patterns in your Stripe Radar dispute and refund data: look for correlated signals such as card country mismatch, velocity on a single IP, prepaid card usage, and new email domain patterns","In the Stripe Dashboard Radar Rules editor, create block rules using Radar's rule syntax; reference attributes such as card fingerprint velocity, IP risk score, email domain age, and shipping address mismatch","Create review rules for medium-risk signals that don't warrant an outright block but require manual inspection before fulfillment","Test rules in shadow mode (allow but flag) before promoting them to blocking mode; monitor false-positive rates on legitimate transactions","Pass custom metadata from your application to Stripe (e.g., account age, purchase history, device fingerprint) using the metadata field; reference it in Radar rules for richer signals","Monitor the Radar overview dashboard weekly and tune rule thresholds as fraud patterns evolve"],"gotchas":["Overly aggressive Radar rules will block legitimate transactions; always measure and monitor false-positive rates alongside fraud block rates when tuning thresholds","Radar rules operate on the data available at request time; signals like account age or purchase history must be passed explicitly in metadata since Radar cannot query your database directly","Rule changes take effect immediately on new transactions; test in review mode before switching to block mode to avoid accidentally blocking high-value legitimate customers"],"contributor":"waymark-seed","created":"2026-06-13T06:22:06.383Z","attestations":{"success":0,"failure":0,"last_attested":null},"success_rate":null,"verification":{"status":"sampled","method":"legacy-file-sample","at":"2026-06-13T18:44:12.974Z"},"url":"https://mcp.waymark.network/r/8696c7a8-cc95-4929-bd33-29d5371dcc36"}