‘AI vs. AI’: The only way to battle sophisticated iGaming bonus abuse

Stian Enger, Head of Casino at EveryMatrix, introduces Bonus Guardian – a new AI tool designed to tackle the ever-growing threat of bonus abuse in iGaming. With fraudsters becoming ever more sophisticated in their techniques, manual reviews are no longer effective enough to protect promo budget leaks. Enger outlines how Bonus Guardian, as part of the EngageSuite product portfolio, helps operators protect those budgets, offer better bonuses to genuine players and, ultimately, protect their bottom line.

Keeping your promotions safe from bonus abusers has become more difficult over the years. The tactics used by fraudsters have evolved.

Many operators still rely on manual checks and rigid rule-based systems, but they no longer match the scale or sophistication of today’s techniques. This kind of fraud isn’t new, yet it remains underestimated. Too many operators treat it as a ‘cost of doing business’, assuming the financial impact is negligible. That assumption no longer holds.

Reports show that around 15% of promotional budgets leak directly to abusers. That loss could fuel genuine player acquisition, better offers, or improved retention strategies. With technological advances, keeping your promotions safe from bonus abusers turns into a task that is harder to manage.

iGaming fraud in 2025

iGaming fraud is rising. Data shows that 63.8% of all fraud in the sector comes from bonus abuse (Sumsub, 2025). That’s billions every year. Recent industry studies show:

• 83% of operators saw increases in fraud in 2024 (Sumsub, 2025)
• The deposit phase has become the primary flashpoint, with 41.9% of operators reporting fraud, not just during registration (Sumsub, 2025)

This means abusers aren’t looking just for bonus offers. They are building multi-step strategies to extract value deeper in the player lifecycle. The more complex the strategies become, the harder the operator keeps up through traditional methods.

Shift in bonus abuse tactics

What’s changed? Bonus abuse has been industrialised. Fraudsters now leverage AI-powered tools to scale operations. Now they can:

• Generate realistic identities
• Mimic genuine player behaviour patterns
• Operate multiple accounts at scale
• Bypass basic checks and rules

This means abusers act faster than your team can review. The result is a widening gap between how quickly abuse happens and how slowly traditional defences respond.

The strain on operational teams

Manual reviews made sense. A trained team could spot suspicious patterns, block risky accounts, and keep promotions under control. Today, the volume and sophistication of bonus abuse is overwhelming for human review methods solely.

Your teams fall behind because AI-driven bonus abuse works in milliseconds, not minutes. Additionally:

• Review queues grow unpredictably, forcing rushed decisions
• Human bias and fatigue bring inconsistencies, which abusers learn to exploit
• Operational cost scales, while abuse techniques scale exponentially

Constraints of rule-based systems

Rule-based systems are a necessary foundation, but they’re not sufficient alone. The problem is they can only detect what has already happened.

Bonus abusers are unpredictable, and even when a pattern is known, they adapt quickly. This creates several issues:

• Rules become too restrictive, impacting genuine players
• Every new abuse tactic forces a new rule, turning your system into a maze of patches
• Rules can’t weigh hundreds of behavioural signals simultaneously, while AI scripts can

You can combat bonus abusers by creating strict wagering requirements, restricting certain games, but this will affect genuine players as well, so it’s not a good way to go. Relying too heavily on rules puts you in a defensive position, constantly reacting, never anticipating.

Mitigating bonus abuse in 2025 and beyond: AI vs. AI

To keep up, or outpace modern bonus abusers, you will need defences that adapt as fast as the threat evolves. This is where AI-powered prevention becomes decisive.

Unlike manual reviews and static rules, AI learns continuously from player behaviours, device signals, transaction patterns, and historical data. It doesn’t rely on guesswork or fixed thresholds; it identifies risk in real time.

Static rules stop where the playbook ends, but AI keeps learning, spotting new patterns, adapting, and meeting bonus abusers on the same technological level.

Introducing Bonus Guardian, EveryMatrix’s AI-powered bonus abuse prevention tool

To match the speed of bonus abusers, EveryMatrix developed Bonus Guardian as part of BonusEngine and EngageSuite stack. This AI/ML-driven bonus abuse prevention tool stops fraudsters before they get away.

Bonus Guardian is not just another fraud filter. It is a living shield that adapts to everything that is thrown at it thanks to the power of AI.

Bonus Guardian helps operators maximise ROI on marketing spend, preventing losses caused by bonus abuse. It addresses bonus abuse directly, offering a context-aware solution that can be integrated with operators’ systems, such as payment processing and player account. Unlike generic anti-fraud platforms, it is designed specifically for bonus abuse scenarios.

Not only that, but it also continuously learns from real-time player data, reducing manual workload and false positives, helping operators to prevent revenue loss by flagging and stopping bonus abuse early; improve their segmentation accuracy and player lifetime value; reduce operational friction with intelligent, role-based fraud controls; and future-proof operations against evolving fraud mechanisms such as deepfakes, AI-generated accounts, and coordinated abuse rings.

The original version of this article was published by iGaming Expert.