When operators focus on anti-fraud primarily in terms of anti-money laundering and KYC verification, cheaters have already shifted their tactics. Bonus abuse—exploiting promotional offers for arbitrage—is causing the European gambling industry to lose about $5 billion annually, which is equivalent to 10% to 20% of the industry's total revenue. More concerning is that by 2024, 83% of European operators report that the problem has worsened year over year. Simply put, the practice of exploiting these systems is becoming more professional, and traditional "blocking" methods are no longer sufficient. In the AI-driven battle of offense and defense, operators need to shift from "passive pursuit" to "active prevention." Want to know how to use behavioral intelligence to combat bonus abuse? Follow the latest anti-fraud technologies continuously on PASA's official website.
First, the escalation of the problem: AI makes cheaters "more like real people"
In the past, monitoring multiple account registrations could catch most cheaters. But now, cheaters use AI tools to disguise themselves as ordinary players:
Behavior dispersion: Spreading activities over time to avoid suspicion from extreme betting
Precise strikes: Acting only when appropriate promotions are available, rather than indiscriminate attacks
Organized operations: Multiple accounts or even collaborative efforts, sharing profitable promotional information
Game adaptation: Using automated scripts to control betting rhythms in slot machines, and robots to play table games like poker
Cheaters also use AI for simulation testing, data analysis, and web scraping, discovering new promotional loopholes faster than operators and exploiting them on a large scale. Traditional rule systems simply cannot keep up with tactics like device information hiding, IP rotation, payment method rotation, and mass production of fake identities.
Second, behavioral patterns: the "fingerprints" left by cheaters
Although cheaters strive to "go invisible," their behavioral patterns still leave traces. Stian Enger Pettersen, head of CasinoEngine at EveryMatrix, points out that behaviors worth noting include:
Only active when there are rewards, and playing only a very few games
Extremely regular betting patterns, which appear meticulously calculated rather than casual entertainment
Targeting games with high RTP (Return to Player) and low volatility, to meet wagering requirements with minimal loss
Withdrawing immediately after meeting wagering requirements, then remaining inactive for a long time
A single behavior might not mean much, but a combination of multiple characteristics often signals definite cheating. Bohdan Bezrukyi, product manager of Bonus Guardian, emphasizes that patterns like registration behavior sequences can only be effectively recognized by well-trained models.
Third, the solution: Using AI against AI, precise rather than overreactive
Facing AI-driven cheating, traditional rule systems are inadequate. EveryMatrix's AI and machine learning tool, Bonus Guardian, is designed to meet this challenge.
Core advantages:
Continuous learning: Based on billions of game rounds, identifying patterns that are imperceptible to the human eye
Scalable response: When activities suddenly attract a large number of cheaters, there is no need to increase manpower, as the system responds automatically and swiftly
Low false positive rate: More accurate than manual analysis, reducing collateral damage to normal players
Pettersen emphasizes that the key is not to "overreact" to cheaters—such as suddenly restricting all accounts or canceling rewards, which would harm normal players. A smarter approach is: quietly adjusting who can receive promotions and the extent of those promotions based on player behavior and risk level. When cheating becomes unprofitable, they naturally leave; normal players continue to enjoy their experience as usual.
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This article is from "PASA-Global iGaming Leaders," a gambling industry news channel: https://t.me/pasa_news
Original in-depth gambling channel: https://t.me/gamblingdeep
Free data reports: @pasa_research
PASA Matrix: @pasa002_bot
PASA official website: https://www.pasa.news
