affiliate-fraud-detection

Affiliate Fraud Detection Build the rule set a program owner uses to flag fraudulent affiliate activity, then investigate and escalate it. This is a defensive skill: it protects programs from being defrauded, and describes each fraud pattern only to the depth needed to recognize it. No canonical affiliate-fraud detection framework exists. The only ratified standard is the IAB/MRC invalid-traffic split, an ad-measurement standard the affiliate industry borrows rather than one written for affiliate programs: GIVT - caught by routine list filtration: known bots, data-center IPs, non-browser user agents. SIVT - needs advanced analytics and corroboration: hijacked devices, adware, cookie stuffing. The PMA's Toolbar and Software Industry Standard is a voluntary, non-binding proposal, not a ratified standard. Force-fit no other framework. The single highest-leverage control is a commission hold/validation window of 30-90 days, not a detection algorithm. The strongest independent evidence agrees: Edelman's research (related to Edelman & Brandi, JMR 2015) found delaying affiliate payments by two to four months could eliminate more than 70% of fraud without decreasing profit. Control Leverage Four controls compete for the hours before the next payout cycle. Rank them before writing a single rule. Show more Installs 1.2K Repository mbfinotti/partn…s-skills GitHub Stars 1 First Seen Sep 13, 2026 Security Audits Gen Agent Trust Hub Pass Socket Pass Snyk Pass