Revealing the Impact of New Tools on Online Gambling Safety

Unlike commercial alternatives, this transparent tool equips regulators like the Netherlands Gambling Authority (Ksa) with an independent method to spot problematic gambling early. As the online gambling market booms—with excessive players accounting for roughly 60% of revenues in some regions—this innovation is vital for verifying whether companies are truly meeting their player protection duties.

The Need for an Independent Assessment Tool

Dutch casinos have a legal duty of care towards their players. At the same time, they possess the most detailed data of their customers – data that can be used to bind players to them. With that same data, tools could be developed that try to predict when a player is at risk of becoming addicted. Almost all existing analysis tools for this purpose were developed by or in close collaboration with the casinos. With a public and independent model, regulators worldwide now have their own transparent frame of reference at their disposal, free from commercial interests.

A Unique Law Paving the Way for Research

Charles de Leau, now a PhD student at the UvA, has personally experienced the effects gambling addiction can have within families and circles of friends. That gave him the idea for his research. He pitched it to ZonMw, who subsequently funded it from the Ksa's Addiction Prevention Fund. De Leau developed the model together with UvA professors Reinout Wiers (Psychology) and Johan Bollen (Computer Science).

The model is trained on, among other things, all bets of all players from 13 Dutch online casinos over a two-year period (July 30, 2023, to July 30, 2025). This data was obtained through a provision in the law that requires casinos to make their user data available for independent research. 

De Leau is the first and, so far, the only one to ever make use of this provision.

"The fact that we were able to analyze all bets from 13 different casinos over two years has never been done before by independent researchers," says De Leau. "With that gigantic amount of data, which is normally used by casinos themselves for marketing purposes, we can see for the first time on such a scale which patterns in playing behavior often precede serious problems."

Global Application for Regulatory Bodies

The model was made publicly accessible on the Ksa website on Tuesday, August 18. As a result, other parties can also use this algorithm. Using machine learning, the Ksa can use the model to calculate risk scores and compare them, for example, with the risk scores used by providers. Regulators (and casinos) worldwide would therefore no longer have to depend on the closed systems of the casinos themselves, leading to more transparent supervision. De Leau: "This is a very different way of looking at player protection, and that will be quite a transition for many parties. In my opinion, it is incredibly important in this fast-growing market that we get more options to protect players."