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How gambling operators can tackle account takeover and bonus abuse fraud

December 20, 2024
How gambling operators can tackle account takeover and bonus abuse fraud

Post-account-opening fraud continues to be one of the biggest challenges faced by the online gambling industry, with fraudsters employing increasingly sophisticated techniques. In a recent interview conducted by FullCircl with experts from Sift, insights emerged on how gambling operators can address these challenges while protecting user experience.

One of the primary issues identified is account takeover (ATO), where fraudsters gain unauthorised access to user accounts using stolen credentials. Once inside, they manipulate account details, link new deposit accounts, and engage in suspicious activities. “Compromised accounts are a significant issue in the online gambling industry,” Sift experts explained. “Fraudsters gain unauthorised access to user accounts, often using stolen credentials. They then change account details, such as passwords and contact information, link new deposit accounts, and engage in suspicious spending. Behavioural analytics can help identify these changes and alert operators to potential takeovers.”

Another rising concern is bonus abuse and promotion fraud, where bad actors create multiple accounts to exploit promotional incentives. Sift highlighted patterns such as the use of single devices for multiple accounts or geolocation discrepancies as key indicators of this behaviour. “Fraudsters exploit promotional offers and bonuses by creating multiple accounts to maximise their gains… Identifying and preventing this requires monitoring for patterns such as the use of a single device for multiple accounts or geolocation discrepancies,” they said.

First-party fraud, also known as friendly fraud, remains prevalent. Legitimate users deny bets or transactions to secure refunds, making it difficult for operators to distinguish genuine disputes from fraud. Sift’s experts noted that advanced tools such as behavioural analytics are critical in managing these claims. “Operators often use behavioural analytics to identify patterns that indicate friendly fraud, such as frequent chargebacks or disputes from the same user. The latest trends in managing these types of claims involve the use of AI and machine learning to detect anomalies and predict potential fraud before it occurs,” they added.

Collusion and syndicate betting also pose unique risks, particularly as fraudsters collaborate to manipulate outcomes. Detecting these activities requires operators to analyse betting patterns and connections between accounts. “Unusual betting behaviours, such as placing bets on all outcomes of an event, signal potential collusion. Real-time monitoring and AI-powered risk scoring are key tools for operators,” Sift explained.

The role of artificial intelligence (AI) in refining fraud techniques is growing rapidly, with fraudsters leveraging AI-driven tools that are increasingly accessible. Sift emphasised the need for operators to adopt advanced fraud prevention technologies to stay ahead. “To detect patterns of collusion between accounts, gambling operators use sophisticated analysis of betting behaviours and connections between accounts. This includes monitoring for unusual betting patterns, such as multiple accounts placing bets on all possible outcomes of an event.

“Real-time monitoring and AI-powered risk scoring are also employed to assess risk based on player behaviour and quickly identify suspicious activities.”

To strike a balance between fraud prevention and user experience, operators must rely on passive datasets, such as device intelligence, geolocation, and behavioural tracking. By combining these datasets, analysts can detect anomalies like unauthorised access from new devices or unusual spending patterns.

Managing regional differences in fraud patterns and regulatory requirements adds another layer of complexity. Sift stressed that operators must customise fraud prevention strategies to align with specific regional trends, payment methods, and compliance obligations.

Looking ahead, Sift urged operators to adopt a proactive approach to fraud prevention by leveraging AI-driven tools, network data, and expert support. For teams transitioning from reactive to proactive prevention, Sift offers solutions that enable accurate, timely decision-making through innovation and industry expertise.

Read the full interview here.

Keep up with all the latest FinTech news here.

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  • TAGS
  • Account takeover
  • AI fraud detection
  • AML Compliance
  • behavioural analytics
  • bonus abuse
  • collusion detection
  • Fintech
  • Fraud prevention
  • FullCircl
  • gambling fraud
  • KYC Compliance
  • Machine Learning
  • online gambling
  • promotion fraud
  • Sift
  • Trust and Safety Architects
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