How protected are you from bonus abuse? You might be surprised

For operators attempting to navigate the complex challenge of fraud in iGaming, bonus abuse has emerged as an increasingly problematic issue.

While anti-fraud strategies have traditionally focused on anti-money laundering (AML) and Know Your Customer (KYC) verification, fraudsters have increasingly shifted their attention elsewhere.

As a consequence, bonus abuse – where users exploit promotional offers meant for others – is leaving operators across the industry increasingly out of pocket.

In Europe, bonus abuse is estimated to cost operators between 10% and 20% of their turnover. With a valuation of $58bn annually, this means some $5bn is being sucked out of the European iGaming sector every year. More concerning still, 83% of European operators claimed in 2024 that the issue had grown year-on-year.

An AI-accelerated problem

One reason for this growth is that bonus abuse has become much harder to spot than it used to be.

In the past, straightforward monitoring of player behaviour could yield results – particularly attempts by individuals to create multiple accounts.

However, such a scattergun approach is becoming a thing of the past. Armed with AI-powered tools, fraudsters are finding success in their attempts to blend in with legitimate players.

Often, they spread their activity over time, avoid extreme bets that will raise suspicion and wait for the right promotion before acting. Furthermore, given the potential financial rewards, it is hardly surprising that there is a greater degree of organisation involved in the fraud in gambling than ever before.

Most incidents of serious bonus abuse today involve more than one account and often more than one person. Groups have been known to share information about profitable bonuses and use tools to hide links between accounts.

Their approach also adapts to the games in question.

Automation is deployed on slot games to manage timing and betting behaviour, rather than playing directly. For table games, such as poker, the focus shifts to bots that can automate gameplay. Sophisticated bonus abusers leverage AI to run simulations, test behaviours, deploy scripts and try to stay a step ahead of the operators and the authorities.

Historical data analysis can also be harnessed by AI tools in the wrong hands, giving wrongdoers the ability to act more quickly and on a larger scale.

Additionally, web-scraping activities that monitor new casinos, bonus campaigns, game releases and in‑game features are commonly deployed to identify and exploit new bonus‑abuse opportunities.

Behavioural trends

That said, there are deeper behavioural trends that can give operators justifiable reason to take preventative action.

Common behaviours to look out for include players who only become active when bonuses are available and focus on a very small number of games.

Perhaps they show very consistent and calculated betting patterns that do not look like casual or authentic play. Or maybe they target high RTP (return-to-player) and low-volatility games that are ideal for meeting wagering requirements while incurring minimal loss.

In the AI and automated era of bonus abuse, external tools are making it easier for abusers to look like legitimate players. Software can hide or alter device information – such as residential IP addresses – or help to rotate payment methods.

AI tools can also help them generate fake personal information more easily, enabling tens, hundreds, or even thousands of accounts to be created at speed, overwhelming the operator’s defences.

The challenge, therefore, is to identify red flags and act upon them in a timely manner before bonus abuse leaves a dent in an operator’s gross gaming revenue.

With that in mind, traditional, rigid detection methods that fail to adapt to change are struggling to keep up. Modern bonus abuse usually happens slowly and across multiple accounts, which makes it harder to detect unless behaviour is analysed over time.

An AI-driven solution

While AI is being leveraged by fraudsters to exacerbate the task, though, external tools and technologies are also increasingly helping proactive operators to tackle bonus abuse. This helps to shift from reacting to incidents of bonus abuse – and constantly playing catch-up – to proactively guarding against it. That was the concept behind the development and launch by EveryMatrix of Bonus Guardian – an AI-powered and machine learning-driven tool that identifies complex bonus abuse patterns rule-based systems solely cannot.

“Traditional systems struggle because they often rely on fixed rules based on isolated actions. They treat every player the same way no matter what its profiling is,” Stian Enger Pettersen, head of CasinoEngine at EveryMatrix, says.

“Bonus Guardian scales well so if you have campaigns that suddenly attract many bonus abusers you don’t need to have more staff on duty. It acts faster and creates less false positives than manual analysis.

“Bonus Guardian continuously learns from billions of game rounds. It adapts and can detect patterns not visible to the human eye, continuously keeping you and your operations safe, not just for the moment.”

Powered by deep data, the solution enables operators to act on intelligence that simply would not be accessible to them via manual means.

Bohdan Bezrukyi, product owner at Bonus Guardian, adds: “A rule‑based approach often leads to configuration complexity. Each bonus campaign requires its own manual setup, making the process more error‑prone. Furthermore, every new bonus‑abuse strategy that emerges must be added as a separate rule or flag – again requiring manual configuration.”

Understanding the data patterns

It is a common but understandable misconception that while fraudsters follow the money, fraud detection methods should do the same.

Indeed, the early warning signs indicating a user may be abusing bonuses – before financial damage is done – usually appear in how they behave, rather than how much money they win.

Deploying highly structured betting patterns, playing only when bonuses are active, or withdrawing immediately after completing wagering requirements and then becoming inactive again are behaviours that may not signal bonus abuse in isolation.

However, identifying a combination of these issues is often a strong indicator that a player is using bonuses in a calculated way, rather than for game-playing enjoyment.

Bezrukyi adds: “There are several behavioural features and event patterns that operators often overlook. Because bonus abusers actively try to stay below detection, these signals may go unnoticed during manual reviews. However, such patterns, like registration behaviour and activity sequences, can be effectively identified only by a properly trained model.”

Targeted and proportionate

Acting on the information in a decisive and proportionate manner is as important as identifying the problems in the first place.

Bonusing remains a central lever for player engagement and retention in a highly competitive landscape, and overreacting to isolated incidents may have an adverse impact on the experience for legitimate players. Therefore, the challenge is to tighten bonus abuse prevention without damaging trust.

A common misstep is to react too quickly to abuse by introducing strict rules that also affect normal players. Another mistake is to assume that any player who wins consistently must be abusing bonuses.

“The key is to avoid heavy restrictions that deter genuine players,” Pettersen says. “Instead of blocking bonuses or suddenly limiting accounts, operators can quietly adjust who receives certain offers and how generous those offers are.”

When bonuses are tailored according to player behaviour and risk, abuse becomes less profitable while legitimate players continue to have a normal experience. At the same time, responsible gaming standards are pushing operators to think more carefully about how bonuses influence player behaviour.

Regulators are paying closer attention to how bonuses are offered and enforced, as shown by recent changes in the UK. Operators such as those that work with EveryMatrix are expected to apply clear rules, treat players fairly and be able to explain why action was taken against an account.

Therefore, effective and targeted steps may not mitigate financial headwinds due to bonus abuse, but they may also keep them in authorities’ good books.

Explore the complete guide to bonus abuse here, including expert insights and video explanations.