Bonus abuse is a silent killer in iGaming, hard to identify and stamp out despite causing massive losses for operators. But every problem is an opportunity in disguise.
Stian Enger Pettersen, Casino CEO at EveryMatrix, reveals how technological advances could help stamp out bonus abuse for good.
Tightening regulations, new advertising restrictions, and tax increases in various markets around the world mean it is more important than ever for iGaming operators to find ways to improve margins.
One promising area that has emerged recently as an opportunity to save serious money is bonus abuse. According to one report, bonus abuse constitutes 70% of all fraud in iGaming. “Bonus abuse is by far the most overlooked cost in our industry, and it often goes unnoticed until the damage is done,” explains Stian Enger Pettersen, chief executive officer of casino at EveryMatrix and a veteran in the iGaming space.
“In comparison, chargeback represents 5.6% of total fraud and has been on everyone’s lips since this industry’s infancy. The reason is that bonus abuse is a lot harder to spot, and also drives activity that an operator wants, such as sign-ups and deposits. However, the financial impact of bonus abuse can be massive if it’s not addressed proactively.”
To understand the implications of bonus abuse, we must first establish what exactly the term means.
For Pettersen, bonus abuse comprises a “range of different techniques, which all have in common that a player is more likely than not to end up with real money based on a promotion (most commonly, but not limited to, bonus cash).”
Such abuse ranges from singular, clever players that only play when there’s a bonus to exploit, to organised syndicates that abuse bonuses at an industrial scale.
Abuse can be perpetrated by both bad actors and legitimate, genuine customers, making prevention particularly difficult and sensitive.
“Multi accounting is a common practice to scale abuse, and particularly common for syndicates. What it boils down to is that operators are under constant pressure to deliver attractive promotions that drive acquisition and retention, all while trying to keep abuse under control.”
Professional bonus abusers and syndicates meticulously browse the market, targeting the most lucrative opportunities, and stay on top of new offers, casinos, and affiliate promotions, Pettersen says.
Abusive practices force operators to impose stricter promotional terms, creating a less attractive and unfair environment for genuine players.
For example, abusers will comb over the terms and conditions, looking for avenues for exploitation. This causes friction for genuine users, who must navigate strict and convoluted bonus T&Cs, or may not bother signing up due to conservative sign-up offers.
Is completely eliminating bonus abuse a realistic possibility? With cutting-edge technology, EveryMatrix thinks it is.
“The only truly effective way to detect organised bonus abuse is by both analysing player identity and behavioural patterns,” Pettersen continues.
“This includes monitoring of a wide range of indicators, starting with registration details (location and device data, email, phone, etc). On the bonus side, the system monitors and tracks the number and type of bonuses granted (deposit vs no-deposit), wagering progress, bonus-to-deposit ratios, bonus claims frequency, trigger types.”
Gameplay, he explains, can be closely analysed by monitoring the games and game types played, games’ volatility, changes between wallets (real and bonus), bet amounts and timing, and sequences of actions. He says abusers tend to favour games with exploitable features and use irregular play strategies, such as switching between high and low volatility games, to maximise bonus value.
These behavioural signals and irregular playing patterns open up opportunities to detect abuse as it happens, if the right tools are in place. But manually monitoring those signals is utterly unfeasible at scale. New advances in AI technology, however, provide an answer.
“The only way to truly approach bonus abuse in a proactive way is through automation and leveraging artificial intelligence to analyse thousands of behavioural patterns,” Pettersen adds. “It helps operators pinpoint potential bonus abuse attempts and provide actionable insights on how to prevent those attempts from succeeding.
“For example, our Bonus Guardian tool detects bonus abuse through a combination of cutting-edge AI-driven analysis and behavioural modelling. It builds predictive models based on user activity and continuously adapts to new abuse techniques. By analysing thousands of behavioural patterns, it efficiently predicts potential abuse, ensuring that operators can act swiftly to prevent it.”
EveryMatrix’s Bonus Guardian is a comprehensive tool in the fight against bonus abuse, leveraging cutting-edge AI algorithms and machine-learning technology to analyse thousands of user behavioural patterns.
Trained on massive amounts of data, EveryMatrix says Bonus Guardian can proactively predict and prevent bonus abuse in what represents a cost-effective approach to player rewarding. It automates the detection of potential bonus abusers – a process designed to save operators time, effort and expense.
Bonus Guardian works by analysing user activity, flagging potential bonus abuse and assigning a role to the user based on its findings. Operators can then define specific conditions and actions for each role. For instance, flagged users can have their bonus options paused, or a hold put on their withdrawals, or other restrictions which can be tailored to fit a defined business strategy.
“Working with Bonus Guardian is straightforward,” Pettersen claims. “Operators are immediately notified the moment bonus abuse is detected, with all flagged cases displayed in a dedicated widget inside the BonusEngine back office.
“Restrictions are applied automatically and are fully configurable – whether it’s blocking bonus usage, holding withdrawals, disabling logins, or even fully blocking the account.
Configurability is important in the context of bonus-abuse detection, as different operators may have different risk tolerances, or may be worried about the impact on KPIs such as sign-ups or deposit targets.
To cap it off, reinforcement learning means users of the tool benefit from the network effect – as more iGaming sites use it, the better it becomes.
“Through the widget, operators not only review detected players but also provide direct feedback, which is used to continuously improve the model’s accuracy and adapt it to new abuse strategies,” Pettersen adds. In the gaming industry, new technology is often prematurely described as a silver bullet – but it is clear that in the fight against bonus abuse, AI-enabled technology holds promise for real and meaningful value in tackling bonus fraud in iGaming.
The original version of this article was published by iGamingBusiness.
Read all the articles in our EveryMatrix Effect series here.
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