As sports betting legalization has expanded across the world and iGaming platforms have moved into new regulated markets, the fraud economy targeting operators has grown in parallel. And it’s easy to see why: the global online gambling market is steadily growing to a valued $140 billion annually, making it an incredibly lucrative fraud market.
In this post, we’ll be going over the online gambling industry’s current fraud landscape, which types are rising, and how your iGaming business can improve its fraud prevention operations.
The primary fraud types hitting iGaming operators
- Bonus abuse and multi-accounting: The most pervasive fraud type across iGaming platforms, bonus abuse exploits the promotional economics operators use to acquire players. Welcome bonuses, free bet credits, no-deposit bonuses, and reload offers are all targets. Fraudsters create networks of fake accounts to claim the same promotion multiple times. Sophisticated operations use device farms, residential proxies, and synthetic identity fraud to make each account appear independent. For operators with generous acquisition promotions, uncontrolled bonus abuse can make player acquisition economics negative.
- Accessing stored value to transfer off-platform: Fraudsters targeting iGaming accounts have strong financial motivation, as player accounts hold deposited funds, bonus balances, and accumulated winnings. ATO attacks on iGaming platforms use credential stuffing, phishing, and social engineering to gain access to existing user accounts to transfer their funds off-platform. High-value VIP accounts are the highest-priority targets, as a single successful takeover can result in as much as a five- or six-figure theft.
- Multiple Account Creation (Multi-Accounting): This is where fraudsters create multiple player identities to evade responsible gambling restrictions, bypass self-exclusion programs, circumvent betting limits, manipulate referral programs, and collude in peer-to-peer games or poker tournaments. These account networks often share underlying device, network, behavioral, or payment characteristics while appearing to belong to different individuals. When left unchecked, multi-accounting distorts player data, increases operational costs, and undermines regulatory compliance.
- Promo/Policy Abuse: Not all promotional abuse involves fake identities. Legitimate players frequently exploit gaps in bonus terms, VIP programs, cashback offers, referral incentives, and withdrawal policies to maximize payouts beyond what operators intended. Organized groups share techniques online, coordinate promotional activity, and rapidly exploit newly launched campaigns before operators can adjust controls. While each incident may appear low-risk in isolation, widespread policy abuse can significantly erode promotional ROI and create unfair advantages over legitimate players.
- ACH Fraud / Cryptocurrency Exchanges: Payment fraud remains a major challenge for iGaming operators, particularly where instant deposits and rapid withdrawals are supported. Fraudsters use stolen bank accounts, compromised payment credentials, or unauthorized ACH transfers to fund gambling accounts before attempting to withdraw winnings or convert balances into cryptocurrency. Others exploit payment timing windows, depositing funds before bank transfers fail or are reversed. Because cryptocurrency transactions are difficult to recover once completed, operators face significant financial exposure if fraudulent deposits are not detected before funds leave the platform.
Trends shaping online gambling fraud
To understand how online gambling fraud works, it’s vital to know how it’s shaped and the resources used by fraudsters. Here are the biggest ones to know.
- Market expansion creating new fraud opportunities: Each new regulated market that opens brings a wave of promotional activity, and with it, a corresponding wave of bonus abuse targeting those promotions. Operators entering new US states have consistently reported elevated bonus abuse volumes in the first months of operation as fraudsters respond quickly to new promotional calendars.
- AI-generated synthetic identities: The same generative AI technology that produces deepfake images now produces synthetic identity data on a large scale. Fraudsters creating fake iGaming accounts have access to increasingly convincing fabricated identity materials, including AI-generated ID documents that challenge standard KYC verification. The synthetic identity problem is worse for iGaming than for many other sectors because the promotional economics justify the effort of sophisticated account creation.
- Organized fraud rings: iGaming bonus abuse has professionalized into an organized industry segment. Fraud rings operate dedicated pipelines for account creation, device management infrastructure, and teams assigned to specific platforms and promotions. These operations move quickly across platforms and adapt to enforcement actions faster than individual operators can respond without network-level intelligence.
- Payment method diversification: The expansion of deposit options, including digital wallets, cryptocurrency, and prepaid cards, creates new fraud vectors. Crypto deposits reduce reversibility and increase the attractiveness of money laundering through gambling.
What fraud teams should focus on
Given this landscape, the highest-return fraud prevention investments for iGaming operators center on three areas.
Registration controls that catch multi-accounting before bonuses are claimed: Every fraudulent account that passes registration costs the operator the full value of its promotional offer. Catching multi-accounting at registration is the highest-leverage intervention in the iGaming fraud stack.
Continuous player monitoring that extends risk assessment through the full player journey: Fraud in iGaming frequently does not manifest at registration. It manifests at deposit, at bonus activation, or at withdrawal. A risk scoring system that only evaluates players at onboarding misses the majority of fraud events.
Network intelligence that extends beyond platform-specific data: Sift assesses thousands of signals throughout the user journey to produce a Sift Score (or risk score) informed by cross-network activity. Fraudsters targeting one iGaming platform are often active across multiple operators, and device, identity, and behavioral signals from those encounters inform risk assessments on new platforms.
If your fraud team is struggling with gambling fraud on your iGaming platform, then Sift might be the perfect solution. Sift uses machine learning technology that scans for fraudsters in your system at every point of the player journey, and stops it before it causes financial damage to your platform.
Frequently asked questions
Industry research has found iGaming to be one of the highest-fraud digital sectors, driven by the direct financial value of player account balances and the promotional economics that incentivize abuse. A recent study from Sumsub found that fraud losses account for 10-20% loss of annual iGaming platforms’ revenues.
KYC requirements vary significantly by jurisdiction. Most regulated markets require operators to verify player identity before allowing withdrawals above certain thresholds, and some require verification at registration. In markets with strong KYC requirements, fraudsters must produce convincing synthetic identities to create accounts, which raises the cost of entry. In markets with lighter requirements, account creation fraud operates at lower cost and higher volume. Strong KYC and fraud prevention share the same underlying signal requirements.
iGaming platforms are used for money laundering in two main ways. Deposit-then-withdraw laundering involves depositing funds from stolen payment credentials, performing minimal or no gambling activity, and withdrawing the balance to a different payment method. Structured layering uses gambling activity itself to make fraudulently acquired funds appear to be gambling winnings. Both patterns are detectable through transaction monitoring combined with player behavior analysis: unusual deposit-to-play ratios, rapid movement from deposit to withdrawal, and payment method mismatches are all actionable signals.
