Responsible gaming: preparing for data-driven solutions
Insight provided by Walid RaadEY Americas Forensic & Integrity Services Financial Services Leader and Bob BoyleSenior Manager, Forensic & Integrity Services, Ernst & Young LLP

Incoming responsible gaming regulations 

Land-based casinos and digital operators are teaming with companies to invest in responsible gaming initiatives as an increased focus on monitoring for problem gambling emerges. The onus to identify gaming risk and harmful gaming behaviors is no longer driven by patrons opting to self-exclude. There are a number of state-specific responsible gaming regulations in place, including self-exclusion, advertising limits and wager limits, credit restrictions and hotlines available to patrons; however, regulators are considering enhancements where operators are to integrate advanced data analytics, setting new standards for responsible gaming compliance in the industry. Operators are beginning to leverage data analytics and artificial intelligence (AI) algorithms to analyze datasets to identify events consistent with harmful gaming behavior and take action to provide services to those patrons who may be in need. 

Integrating AI and data analytics in the gaming industry 

Operators have an opportunity to enhance the way they address responsible gaming measures by using the data provided to them. Online gaming platforms currently collect large amounts of data that can be used when conducting responsible gaming analysis:

  • Deposit and withdrawal amounts
  • Patrons’ average wager amount
  • Wagers outside of patrons’ standard deviation
  • Time spent on platforms
  • Pace of bets placed
  • Various betting patterns

Using data to assess customer risk 

The data can be analyzed to identify patrons who have a higher risk of exhibiting harmful gaming behaviors as compared to those patrons who have elected to self-exclude. The gaming and sports wagering industry has taken data modeling and predictive analytics to new heights; many refer to these measures as an advanced form of customer relationship management (CRM). CRM systems record data on their patrons and use data modeling to create profiles that help them assess risks for each patron. AI can be used to develop algorithms to detect the traits of patrons demonstrating harmful gaming behaviors and position preventative measures, showcasing a responsible gaming forefront. For example, in the UK, casino machines use AI to develop a cooling-off system that locks patrons out of the gambling platform when detecting problematic behaviors and promoting safe gambling practices on the screen. 

Active measures for operators 

Operators should consider having both proactive and reactive measures in place to address responsible gaming. Proactive approaches allow operators to observe changes in patron behavior over time and work to help identify behaviors where preventative measures can be implemented at a much earlier stage in the patron’s lifecycle. Operators should leverage their already existing data and incorporate creative AI/analytical solutions to address responsible gaming issues. Conversely, reactive approaches allow operators to meet responsible gaming standards on a timely basis for patrons identified as problem gamblers through self-exclusion and limit setting. 

Reactive approaches use scenario and rule-driven monitoring to comply with state and other jurisdiction regulations. Scenario-driven monitoring identifies potentially known persons for self-exclusion to ensure those patrons are not able to place wagers, participate in daily fantasy sports contests and play casino games. Queries are run across product options to address outstanding wagers or contests to properly allocate marketing restrictions for certain patrons. Currently, in the UK, operators must take steps to remove the name and details of a self-excluded individual from any marketing database within two days of receiving the completed self-exclusion notification. To continue to evolve in an increasingly digital and data-focused regulatory landscape, operators should consider human behavior variables and other external factors by using data-driven solutions to develop measures to proactively address responsible gaming.


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Views expressed in this article are those of the authors and do not necessarily represent the views of Ernst & Young LLP or other members of the global EY organization.