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The global sports betting market is growing rapidly, forecast to grow from USD $68.3B in 2022 to USD $117B by 2027, a compound annual growth rate of 14.3%. Sports betting operators provide an exciting form of entertainment for their patrons, combining knowledge of the game and associated statistics, with the possibility of winning big. Although sports betting can be a fun social outlet, for some it comes with the risk of going overboard. According to the Mayo Clinic, problem gambling is the uncontrollable urge to continue gambling despite the toll it takes on your life. Various studies estimate that gambling disorder affects approximately 3% of the world’s population. It is therefore incumbent upon sports betting operators and regulators to ensure that responsible gaming (RG) controls are made available to players to reduce this risk.
AWS customers realize that a powerful approach to address this issue is to use data and machine learning (ML) models to detect and prevent risky behavior before it becomes a bigger problem. Detecting RG cases involves processing numerous data streams, including behavioral, transactional, and financial information. Betting operators typically have access to a limited amount of data, without a full view of an individual’s history across multiple betting sites. AWS customers may collect user journey information from multiple channels, including betting anonymously through a network of physical betting terminals or through intermediate resellers and partners. By using the power of their own data, betting operators can develop risk detection models that align with their specific businesses and applicable governing regulations.