Definition
Anti-fraud in affiliate marketing and iGaming is the set of systems and practices used to detect and reject traffic and conversions that are fake, manipulated or against the rules, so that advertisers pay only for genuine users. It spans the whole funnel: filtering bot and data-centre traffic before a click is counted, catching duplicate and geo-mismatched leads, identifying bonus abuse and multi-accounting among players, and clawing back conversions later found to be fraudulent.
The toolkit combines several layers. Signal-based checks look at IP reputation, device fingerprint consistency, user-agent plausibility, click-to-conversion timing, and behavioural patterns.
Rule engines apply hard filters — block known bad IP ranges, reject a second lead with the same phone within a window. Statistical and machine-learning models score traffic sources and individual sessions on how much they resemble known fraud.
And post-hoc review reconciles cohorts against quality benchmarks and reverses payment on the ones that fail.
In context
Anti-fraud is a balance, not a switch. Filters set too tight reject genuine users — a real player on a shared mobile IP, a legitimate lead from a VPN user — and depress conversion and payouts; filters set too loose let fraud through and inflate the advertiser's costs.
Both the advertiser and honest affiliates want the balance right, because unchecked fraud eventually forces the advertiser to cut payouts or tighten qualification for everyone, and over-aggressive filtering punishes clean traffic.
For an affiliate, engaging with anti-fraud constructively means disclosing sources honestly, keeping the traffic mix stable between test and scale, providing SubID-level transparency so the advertiser can see where traffic originates, and cooperating on investigations rather than treating every rejection as an attack. For an advertiser, it means publishing the rules, giving specific rejection reasons, and reserving termination for clear, evidenced breaches.
A network with a transparent, well-run anti-fraud process is more valuable to a legitimate affiliate than one that either ignores fraud or rejects traffic arbitrarily.
Worked example
An anti-fraud system flags a traffic source because 40% of its clicks come from a narrow set of data-centre IP ranges and click-to-registration time averages under two seconds — both bot signatures. The advertiser rejects that source's conversions, shares the evidence with the affiliate, and the affiliate blacklists the sub-publisher responsible and resubmits clean traffic.
Related terms
Frequently asked questions
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