Online gambling operators face a fraud challenge that’s broader and more operationally demanding than many other digital businesses. The combination of real-money transactions, high-value promotional programs, strict regulatory requirements, and a global player base creates a fraud surface that spans the full player journey, from registration through deposit, gameplay, withdrawal, and beyond.
In this blog, we’ll be going over iGaming fraud prevention, addressing each of these touch points and how to protect net gaming revenue and player trust at the same time.
Different types of iGaming fraud
There are many different tactics that fraudsters can implement to scam others in the iGaming industry. Here are all of the main ones:
- Account creation fraud and multi-accounting: Fraudsters register fake accounts on a large scale to claim welcome bonuses, free bets, and promotional credits intended for new players. The economics of the scam are direct. If a welcome bonus is worth $50, creating 100 accounts that each claim the bonus yields $5,000 in extracted value. Multi-accounting at this scale can erode player acquisition economics significantly across an operator’s promotional calendar.
- Account takeover: ATO targets existing player accounts with deposited funds or accumulated loyalty rewards. Fraudsters use credential stuffing, phishing, and SIM-swapping to compromise the existing accounts and initiate withdrawals before the legitimate player becomes aware their account’s been compromised. For VIP players with substantial account balances, a single ATO event can represent a five- or six-figure loss.
- Payment fraud: Fraudsters use stolen payment credentials to deposit funds, gamble (sometimes deliberately losing to other fraudster accounts), and withdraw the proceeds. This form of money laundering through gambling platforms results in chargebacks and exposes the operators to regulatory action.
- Bonus abuse: Beyond the multi-accounting variant, bonus abuse includes arbitrage (placing simultaneous bets across platforms to guarantee a positive outcome), collusive play (coordinated accounts cooperating to extract bonus value), and advantage play that exploits promotional mechanics beyond their intended use.
- Responsible gambling circumvention: In regulated markets, players who have set deposit limits, loss limits, or self-exclusions are legally protected from further gambling harm. But with the use of multi-accounting, fraudsters will bypass these protections, which creates both regulatory exposure and harm to players the operator is required to protect.
iGaming fraud detection strategies
Detecting iGaming fraud effectively requires signal coverage across the full player journey, not just at deposit or withdrawal.
- Registration-time controls: Device intelligence and behavioral analytics at registration catch automated account creation, bot-driven multi-accounting, and identity fraud at the earliest possible point. While catching a bonus abuser after they have claimed the bonus and initiated results in a loss, catching them at the point of registration costs the operator nothing.
- Continuous session monitoring: Player risk profiles should update throughout each session. A player who registers normally but exhibits unusual bet patterns, moves toward withdrawal immediately after bonus activation, or shows behavioral characteristics inconsistent with their history is exhibiting post-registration risk signals that warrant review.
- Cross-account linking: Sift assesses thousands of signals throughout the user journey to produce a Sift Score, or an overall risk score between 0 and 100, that’s informed by cross-network activity. Linking accounts through shared device infrastructure, IP ranges, behavioral similarities, and payment method relationships reveals multi-accounting networks that appear independent in per-account analysis.
- Withdrawal risk scoring: Withdrawals are the monetization event in player journey fraud. Real-time risk scoring at withdrawal, with Sift Score and behavioral signals evaluated in the context of the player’s full account history, allows operators to flag and review high-risk withdrawals before funds leave the platform.
Regulatory context for iGaming fraud prevention
iGaming fraud prevention can be tricky, due to the fact that regulated markets face compliance obligations that intersect directly with fraud prevention. Know Your Customer (KYC) requirements, Anti-Money Laundering (AML) monitoring, and responsible gambling protections all require the same underlying player risk intelligence that fraud prevention depends on.
An operator that cannot reliably link a new registration to a previously self-excluded player faces both regulatory sanction and the harm of enabling compulsive gambling. An operator that can’t detect structuring (breaking large deposits into smaller amounts to avoid AML thresholds) faces compliance exposure similar to a financial institution.
The most operationally efficient approach treats fraud prevention, KYC compliance, and responsible gambling monitoring as overlapping programs built on shared player risk intelligence, rather than as separate systems requiring separate data.
If you’re an iGaming operator currently dealing with fraud challenges, then don’t worry. Sift provides machine learning technology that scans for fraudsters in your system during every point of the customer journey, and stops it in its tracks before it causes significant financial damage to your business.
Frequently Asked Questions
Bonus abuse is a deliberate scheme to extract promotional value by exploiting promotional mechanics, typically through multi-accounting or arbitrage. Responsible gambling fraud is specifically the use of multi-accounting or other methods to circumvent deposit limits, loss limits, or self-exclusions a player has set or that the operator is required to enforce. The two overlap frequently, as bonus abusers and problem gamblers both use multi-accounting. The key operational distinction is that responsible gambling violations carry regulatory consequences, not just financial losses.
Risk-based friction applied through Dynamic Friction reserves verification requirements for players exhibiting fraud signals rather than applying them universally. Low-risk player sessions proceed with no additional friction. High-risk sessions trigger step-up verification or review. This concentrates friction on the sessions where it is warranted, preserving the experience for the vast majority of legitimate players who exhibit no elevated risk signals.
The most predictive ATO signals in iGaming include login from a new device or IP address not seen in the player’s history, rapid movement toward withdrawal or bonus activation shortly after login, a password change immediately following login from an unfamiliar device, and behavioral biometric patterns that differ from the player’s established baseline. The combination of device novelty and immediate high-value action (withdrawal request or payment method change) is the highest-confidence ATO signal combination.
