Problem scope

Bonus abuse is iGaming's most studied fraud problem — and still its most costly. Our 2025 research across 40+ European operators found total annual bonus abuse losses of €3.2B, representing approximately 4.7% of total operator gross gaming revenue. Despite a decade of investment in detection technology, this figure has grown year-over-year as abusers industrialise and operators' defences fail to keep pace.

The research question that motivated this report is not "how much is lost" — that figure is well-documented — but "why does traditional detection consistently fail?" Understanding the failure modes is a prerequisite for building defences that actually work.

The economics

The economics for abusers are compelling. A bonus with 20x wagering requirements and a maximum withdrawal cap of €200 requires a bankroll of approximately €100 to exploit optimally, yields an expected value of €60–80 per account per bonus cycle, and can be scaled to hundreds of accounts with modest automation investment. At scale, a single operation can generate €50,000+ per month with a team of two.

Abuse patterns

We identified six primary abuse patterns across our study cohort. In descending order of prevalence: multi-account bonus stacking (exploiting the same offer across multiple accounts), account resale (selling bonus-credited accounts to third parties), arbitrage (exploiting cross-operator bonus differentials), VPN cycling (rotating IP addresses to claim geo-restricted bonuses), family account abuse (legitimate household accounts used for bonus multiplication), and professional bonus hunters (individuals who treat bonus exploitation as a primary income source within TOS).

Why detection fails

Traditional detection fails for three structural reasons. First, point-in-time checks evaluate accounts in isolation — multi-account rings are specifically designed to have each account pass every individual check. Second, rules become public knowledge — operators who rely on documented detection heuristics will find those heuristics published in abuse forums within weeks. Third, there is a fundamental asymmetry: operators must correctly classify millions of accounts; abusers only need to find one technique that works and scale it.

Modern solutions

The only sustainable solution to bonus abuse is graph-native detection that evaluates account relationships rather than individual account signals, combined with behavioural intelligence that identifies exploitation patterns regardless of the account's surface-level legitimacy. Serixo's Identity Graph and Behavioural Engine together reduced bonus abuse losses by an average of 89% across our study operators who had deployed both modules for more than six months — without any detectable impact on genuine player bonus uptake.