While every operator budgets for promotions as a customer acquisition cost, very few budget for the version of that cost that never converts into a real player. Bonus abuse and multi-accounting now account for the single largest fraud category in iGaming, making up 64% of fraud according to a recent study. But unlike chargebacks or payment fraud, this kind of loss hides inside your own marketing spend until it shows up as a margin problem nobody can explain.
Why bonus abuse has become the top threat to net gaming revenue
The majority of fraud losses operators absorb today trace back to welcome offers, deposit matches, free spins, and loyalty incentives designed to attract genuine players.
A single fraudster who opens 50 accounts to farm a $25 free-play bonus will extract $1,250 in promotional value with no intention of ever becoming a real depositor. Multiply that across thousands of synthetic identities and coordinated fraud rings, and the promotional budget meant to grow net gaming revenue instead funds the people actively working against it. A recent report found that a third of operators estimate fraud costs them 10% to 20% of annual revenue, a range large enough to swing a quarter from profitable to underwater.
How multi-accounting turns one fraudster into a hundred
Multi-accounting is the mechanism that makes bonus abuse scale. A fraudster registers repeatedly under slightly altered names, synthetic identities, or stolen credentials to claim first-deposit bonuses again and again. The same report from earlier found fraud rates in iGaming rose 18% year over year and nearly 40% since 2024, with suspicious transaction volume up 4.5 times between Q1 2025 and Q1 2026 alone.
What used to require manual effort now runs at industrial scale. Coordinated groups build device farms, rotate residential proxies, and generate synthetic documents to pass verification checks one account at a time. Fraud analysts who rely on manual reviews or static rules see only the individual account, never the network behind it. That is precisely the gap multi-accounting rings are built to exploit.
The revenue math Trust and Safety teams need to make
Fraud fighters are often asked to justify prevention spending by the amount of revenue that is protected, rather than the number of incidents blocked. Bonus abuse gives you a clean way to do that.
Start with three numbers your team likely already tracks: the average promotional value per new account, the percentage of new signups your review queues flag as suspicious, and your current false-positive rate on account rejections. Multiply flagged volume by average bonus value to estimate gross exposure. Then subtract the cost of over-blocking, since every legitimate player wrongly declined also erodes net gaming revenue, just on the acquisition side instead of the loss side.
This framing shifts the conversation from “how much fraud did we stop” to “how much net gaming revenue did we protect and how much did we generate by approving more real players faster.” Both halves of that equation matter to a chief financial officer. Only one half is typically measured.
Why identity signals alone cannot catch coordinated abuse rings
Know your customer and verification checks confirm a person is who they claim to be. They were never built to answer whether this is the same person who already claimed this bonus under three other names. That requires looking across the entire user journey, not a single point-in-time check at registration.
Sift’s approach ties together device fingerprinting, behavioral analytics, payment patterns, and network analysis to surface connections between accounts that look unrelated on paper but share a device, a payment instrument, or a behavioral fingerprint. A Sift Score aggregates thousands of signals across the user journey into a single 1-100 rating, where 1 signals a trustworthy user and 100 signals likely fraud, so fraud analysts can prioritize the accounts that matter instead of chasing every new signup manually.
Building a bonus abuse defense that scales with your promotions calendar
Promotions calendars are aggressive by design. Marketing teams want to launch offers fast, and every new promotion is also a new attack surface fraud rings will probe within hours of it going live. A defense strategy that works needs to move at the same speed.
That means real-time risk assessment at registration and at bonus claim, not just at withdrawal. It means risk-based friction that adds authentication steps for suspicious signups while leaving the path frictionless for real players. It also means Workflows that route high-risk bonus claims to a queue for review automatically, instead of forcing analysts to build detection logic by hand every time marketing launches a new offer. Operators who wait until a promotion has already been exploited are measuring the damage instead of preventing it.
What to measure once a bonus abuse program is in place
Net gaming revenue protection is not a one-time project. Fraud rings adapt within days of a new offer, and static rules stop working the moment fraudsters map them. Track approval rates for legitimate new depositors alongside your bonus abuse block rate. If one improves while the other stalls, the underlying detection model needs re-tuning, not just a new rule.
Set a cadence for reviewing Insights on where bonus abuse attempts cluster: geography, device type, payment method, time of registration. Coordinated rings tend to leave patterns even when individual accounts look clean. The teams that catch multi-accounting early are the ones treating fraud data as a living signal, not a quarterly report.
If your fraud team is struggling to stop fraudsters before they strike your iGaming business, then you might want to invest in Sift. Sift uses advanced artificial intelligence and machine learning technology to identify and stop fraud attempts before they have a chance to strike. If this sounds like a good fit for your business, request a demo today.
Frequently asked questions
What is the difference between bonus abuse and multi-accounting in iGaming?
Bonus abuse refers to exploiting promotional offers such as deposit matches, free spins, or loyalty rewards without the intent to become a real player. Multi-accounting is the technique that makes bonus abuse scale, where one person or fraud ring opens multiple accounts under different identities to claim the same offer repeatedly. Most large-scale bonus abuse losses trace back to multi-accounting rings rather than isolated individuals.
How much does bonus abuse actually cost iGaming operators?
A recent fraud report on iGaming found bonus abuse accounts for 63.8% of all fraud in the sector, and a third of operators estimate total fraud costs them 10% to 20% of annual revenue. Because bonus abuse draws directly from promotional and marketing budgets, the losses often go unrecognized as fraud until an operator compares acquisition cost against actual player conversion.
Can Know Your Customer verification alone stop multi-accounting?
No. Verification confirms identity at a single point in time but was not designed to detect whether the same person or fraud ring has already claimed a bonus under a different identity. Catching multi-accounting requires connecting signals across the full user journey, including device, payment, and behavioral data, to reveal links between accounts that appear unrelated on the surface.
How do fraud teams justify bonus abuse prevention spend to leadership?
The strongest case ties prevention directly to net gaming revenue rather than fraud incidents alone. Fraud analysts can calculate exposure by multiplying flagged signup volume by average promotional value per account, then weighing that against the cost of false positives that turn away legitimate players. This reframes prevention as a revenue function, not just a cost center.
