Submission Title
RG Smart Gambling Machines: A prevention model to respond to risky play in real time
Session Title
Session 2-1-B: Technologies of Responsible Gambling
Presentation Type
Paper Presentation
Location
Park MGM, Las Vegas, NV
Start Date
24-5-2023 9:00 AM
End Date
24-5-2023 10:30 AM
Disciplines
Technology and Innovation
Abstract
Abstract:
In collaboration with industry, public health, and regulators, Focal Research developed an effective modelling process using player data and technology to identify and assist customers at-risk of having problems with their gambling. The system was originally designed using account-based player data to accurately assess play patterns. Complex algorithms scan the player data stored in an operator’s member data system, alerting operators to play behaviours typically observed among those scoring 8 or higher on the Problem Gambling Severity Index. During a live trial, the system was found to help staff interact with at-risk customers leading to measurable improvement in outcomes for ‘Players of Interest’ identified by the algorithms. The next step is to use this technology to expand player protection to customers gambling without using player identification (i.e., anonymous, or non-account gambling transactions). With industry sponsorship and co-funding through the National Research Council of Canada, Focal Research has developed a prototype model using session data to identify at-risk gambling behaviour during play and to possibly offer valuable messaging (i.e., receiving an interaction or seeing a targeted message when the player is engaged in relevant risky play practices rather than when they reach an arbitrary threshold of time or money spent).
Implications:
The prototype performed well, offering the potential for detecting at-risk play in real-time so targeted personal or automated intervention can occur when it is most likely to be beneficial for the customer. Focal will report on model performance for research underway with operators in Britain, Australia, and New Zealand.
Keywords
Safer gambling, player protection, at-risk play, algorithms, models, real-time.
Funding Sources
This research involves industry sponsorship and co-funding through the National Research Council of Canada Industrial Research Assistance Program (NRC-IRAP) and Focal Research. However, all project authors were part of Focal Research’s research team. Industry sponsors provided access to player data, IT support and funding for non-eligible project expenses, including assisting Focal in administering a risk measure (PGSI; FLAGs) to a representative sample of member customers. All research was GDPR compliant. Participating operators were not involved in any aspects of the research, including but not limited to the research questions, methodology, research conduct, analysis or reporting. The National Research provided project oversight.
Competing Interests
As authors of the research involving RG Smart Gambling Machines, we are not aware of any other competing interests with respect to the authors or any of the industry or government funding partners. Based on previous research Focal Research has developed bespoke and proprietary safer gambling systems, including the ALeRT BETTOR Protection System and BETTOR Customer Care Program, which have been acquired for commercial purposes. However, Focal research is an independent research and data analytics company without affiliation or ownership by any commercial gambling operators or affiliates.
Included in
RG Smart Gambling Machines: A prevention model to respond to risky play in real time
Park MGM, Las Vegas, NV
Abstract:
In collaboration with industry, public health, and regulators, Focal Research developed an effective modelling process using player data and technology to identify and assist customers at-risk of having problems with their gambling. The system was originally designed using account-based player data to accurately assess play patterns. Complex algorithms scan the player data stored in an operator’s member data system, alerting operators to play behaviours typically observed among those scoring 8 or higher on the Problem Gambling Severity Index. During a live trial, the system was found to help staff interact with at-risk customers leading to measurable improvement in outcomes for ‘Players of Interest’ identified by the algorithms. The next step is to use this technology to expand player protection to customers gambling without using player identification (i.e., anonymous, or non-account gambling transactions). With industry sponsorship and co-funding through the National Research Council of Canada, Focal Research has developed a prototype model using session data to identify at-risk gambling behaviour during play and to possibly offer valuable messaging (i.e., receiving an interaction or seeing a targeted message when the player is engaged in relevant risky play practices rather than when they reach an arbitrary threshold of time or money spent).
Implications:
The prototype performed well, offering the potential for detecting at-risk play in real-time so targeted personal or automated intervention can occur when it is most likely to be beneficial for the customer. Focal will report on model performance for research underway with operators in Britain, Australia, and New Zealand.