The ability to analyse player data collected from customer loyalty programs, smart cards, and on-line systems by risk for problem gambling has the potential to change the gaming industry and how it operates. Gambling providers are coming under increasing pressure to make use of player tracking data to identify and subsequently help at-risk and/or problem gamblers. Although the prospect of successful identification and intervention is vastly improved by the use of such a system, there are still legitimate concerns surrounding how to implement and evaluate the use of player data for these purposes. To inform ongoing debate, this paper will provide an overview of lessons learned through the authors’ work in creating gambler risk assessment models by using loyalty data. This paper has particular relevance for social policy, regulatory oversight, and corporate social responsibility applications.