Operating in the iGaming industry is challenging by default: fierce competition, strict regulations on responsible gambling, AML (Anti-Money Laundering) compliance, and KYC requirements. On top of that, operators are frequent targets of fraud — and one of the most damaging forms is affiliate fraud, especially as affiliate marketing in iGaming has grown rapidly since 2020 and continues to expand in 2025.
Main Types of Affiliate Risks
Affiliate risks depend heavily on the payment model offered. Since online gambling relies strongly on affiliates (Google and social platforms often restrict casino ads), fraudsters exploit these models.
- CPA (Cost Per Action): The most vulnerable model. Fraudsters can generate fake traffic using stolen data and advanced bots. In 2025, bots are so sophisticated they can create accounts, make deposits, and even claim bonuses — blurring the line between affiliate fraud and bonus abuse.
- PPC (Pay Per Click): Here, traffic can be redirected without user consent. Techniques include malicious browser extensions, hidden redirects, and fake clickable links. Operators usually spot this via high bounce rates and poor KPI results, but detection is becoming harder.
- Revenue Share (RevShare): This model can be exploited through collusion. Groups of high-stakes players may coordinate bets against the casino, minimizing personal losses while inflating affiliate revenue, leaving operators with heavy payouts but little income.
Additional Fraud Risks
Regardless of payment model, iGaming affiliates may attempt:
- Using stolen identities or credit cards to simulate deposits.
- Domain hijacking with URLs mimicking operator brands to steal referral traffic.
- Installing spyware or adware on user devices to automatically trigger affiliate codes.
- Content scraping from legitimate affiliates to divert SEO traffic.
- Brand bidding on Google Ads, competing with the operator’s own keywords.
How Operators Can Protect Themselves
- Traffic Monitoring & Analytics
Strong monitoring tools can track affiliate traffic quality, showing conversions, rejected signups, and suspicious patterns. - Device Fingerprinting
Fraud prevention providers like SEON recommend device fingerprinting to detect hidden connections between accounts. A “hash” is generated from hardware and software data, revealing repeat fraud attempts even if users switch browsers, clear cache, or use incognito/VPN. - Behavioral Analysis
Risk rules can highlight suspicious users — e.g., disposable email domains, VPN logins, abnormal speed of form completion. Machine learning systems are now widely used to filter and flag such cases automatically. - Automated Filters
Blocking traffic from VPNs, proxies, duplicate IPs, or non-target regions prevents large volumes of fake signups.
Why It Matters
Affiliate fraud remains one of the costliest threats to iGaming operators. According to industry reports, affiliate fraud caused over $2 billion in global losses by 2024, and the figure is expected to rise with the spread of AI-driven traffic manipulation. For operators, building strong anti-fraud strategies and monitoring affiliate performance is no longer optional — it’s essential to survival in the competitive European and global markets.
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