Open source model provides new insight into risky gambling behaviour
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Open source model provides new insight into risky gambling behaviour


Researchers from the University of Amsterdam (UvA) present an algorithm that estimates the risks to players in online casinos based on their actual gaming behaviour. Unlike similar tools made by commercial providers, the new algorithm will be available for free (open source). This will provide gambling industry regulators, such as the Netherlands Gaming Authority (Ksa), with an independent, transparent instrument to detect risky gambling behaviour early and better assess whether online gambling companies are actually fulfilling their duty of care.

Since the legalisation of online gambling in the Netherlands, the market has grown explosively. Through apps, games and social media, an online casino is always within reach. Recent figures from the French regulator show that around 60 percent of online casinos’ revenue comes from excessive gamblers: people who gamble frequently and for extended periods, with major financial, psychological and social consequences.

Why an independent model is needed
Dutch casinos have a legal duty of care towards their players. At the same time, they possess the most detailed data on their customers – data that can be used to bind players to them. Using that same data, tools could be developed that attempt to predict when a player is at risk of becoming addicted. Virtually all existing analytical tools for this purpose were developed by or in close cooperation 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
Charles de Leau, now a PhD candidate at the UvA, experienced first-hand the effects gambling addiction can have, within his family and circle of friends. This gave him the idea for his research. He pitched it to ZonMw, which 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 was trained on, among other things, all bets made by all players at 13 Dutch online casinos over a two-year period (30 July 2023 to 30 July 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, only person to have ever made use of that provision.

‘Analysing all bets from 13 different casinos over two years has never been done before by independent researchers,’ says De Leau. ‘With this massive 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 gambling behaviour often precede serious problems.’

Application by governments worldwide
The model was made publicly accessible on the Ksa website on Tuesday, 18 August. This will allow other parties to make use of this algorithm as well. With the model, the Ksa can calculate risk scores based on machine learning and compare them to, for example, the risk scores used by providers. As a result, regulators (and casinos) worldwide will no longer need to rely 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 shift for many parties. In my opinion, however, it is incredibly important in this rapidly growing market that we are given more opportunities to protect players.’

About the model
The model is a machine learning-based algorithm that analyses the actual behaviour of players; for example:
• Betting patterns (how much and how often someone bets)
• Frequency and times (for example, playing at night for days on end)
• Loss and win streaks and how players react to them

The model was developed in close collaboration with the Spanish regulator, the DGOJ, which is also currently developing a model itself. Based on these patterns, the model calculates a risk score. All forms of online gambling have been included in the model.

The algorithm is open source: the code and methodology are public. This means that other researchers can verify its operation and build upon it, and that regulators in other countries can also use the model as a reference for supervising online casinos.

Regions: Europe, Netherlands
Keywords: Society, Psychology, Applied science, Computing

Disclaimer: AlphaGalileo is not responsible for the accuracy of content posted to AlphaGalileo by contributing institutions or for the use of any information through the AlphaGalileo system.

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