Kindred collaborates with Playtech on AI-powered AML technology
Operators, regulators and academics publish first white paper after three-year project
Kindred and Playtech-owned responsible gambling tool BetBuddy have published the first findings of a collaboration with City University into new ways of combatting money laundering activities in the online gambling sector.
The partners yesterday published a white paper on the issue, detailing how artificial intelligence could be used to identify anomalous behaviours.
The paper made several technical recommendations, including the development of a centralised system for submitting suspicious transaction reports (STRs), suspicious activity reports (SARs), and the development of a single database of customers flagged for suspicious gambling activity.
In addition, the paper calls for the development of more efficient methods of monitoring player behaviour, and investment in the modernisation and simplification of KYC processes.
Other contributors to the white paper included the Remote Gambling Association, the Malta Gaming Authority, Financial Intelligence Unit, EPIC Risk Management, and the UK Gambling Commission.
Maris Bonello, head of player sustainability and integrity analytics at Kindred Group, welcomed the cooperation, saying: “Collaboration across research, regulators, operators and other partners is crucial if we are to improve techniques and tools to fight fraudulent behaviour across digital platforms. We believe that engaging in research such as this will encourage more transparency and help bridge the work done by operators and academia.”
AML failings have seen several operators hit with fines in the UK, and was one of four areas of focus identified by the UK Gambling Commission last week in its inaugural enforcement report.
Simo Dragicevic, CEO of BetBuddy, added: “This initial phase has been important in obtaining stakeholder validation of where areas for improvement exist in AML monitoring. Whilst this is a very complex challenge, expectations for continuous improvement and investment in research and development using new technologies is high amongst stakeholders.”
The second phase of research will use real-world online gambling data to detect signs of money laundering.
Professor Artur Garcez, head of City’s research centre for machine learning, added: “We are looking forward to starting the next phase of the research using real-world online gambling data. Some of the techniques available today to detect anomalous behaviour, including state-of-the-art recurrent neural networks, have shown promising results in the analysis of such complex streaming data”.