Detect affiliate fraud with Stripe-query patterns and automated rules

Executive Summary

Affiliate programs often attract fraud early. Package the Stripe event-query patterns and automated detection rules the author used into a SaaS that detects, scores, and pauses suspicious affiliate payouts. The author demonstrates concrete evidence - five repeatable affiliate-fraud patterns found using Stripe event logs and SQL queries - showing detection can be built directly on Stripe telemetry. Rapid adoption of Stripe and programmatic webhooks means merchants already emit the raw signals needed. Also, shops are scaling affiliate programs earlier, so fraud shows up before revenue; that operational pain is immediate and measurable. Finally, serverless pipelines and observability tooling make it fast to deploy prebuilt queries and rules into production monitoring. Productized library of concrete Stripe event queries and pattern detectors plus rule automation and orchestration. The source article documents five repeatable fraud patterns and the exact queries that found them in Stripe event logs, proving that Stripe telemetry plus lightweight enrichment is sufficient to detect many attacks. A SaaS that ships prebuilt, tested queries, automated alerts, payout holds and investigation workflows can reach parity faster than ML-only competitors while building a data moat by aggregating anonymized pattern telemetry across customers.