New Open Source Model Detects Risks in Online Gambling According to the University of Amsterdam

Researchers from the University of Amsterdam have developed an open source model aimed at assessing players' risk behavior in online casinos, based on the analysis of their gaming actions. The algorithm, now available through the official website of the Kansspelautoriteit, was introduced as a transparent and autonomous tool capable of anticipating potentially problematic patterns in the sector.

How the Open Source Model Works to Detect Risk in Online Gambling

The algorithm, the result of the work of Charles de Leau (PhD candidate), along with professors Reinout Wiers (Psychology) and Johan Bollen (Computer Science), is based on real user behavior data. It analyzes patterns in online casino behavior to identify early warning signals of risky conduct, thereby contributing to the prevention of gambling-related problems.

The model's approach does not rely on self-reports or predefined criteria, but rather on empirical data collected from online gaming platforms. This data architecture seeks to provide operators and authorities with a more accurate view of profiles and the moments when a player may require intervention.

Independence and Funding: The Role of Kansspelautoriteit and Academia

The development of the model was carried out independently thanks to the collaboration between the University of Amsterdam and the Kansspelautoriteit, the Dutch gambling regulator. Funding came from the Verslavingspreventiefonds, a fund specifically intended for addiction prevention initiatives administered by the Kansspelautoriteit.

The public release of the algorithm in open source format was a decision aligned with principles of transparency and reproducibility, allowing for both peer review and future adaptation by other actors involved in monitoring responsible gambling.

Applications and Regulatory Perspectives of the New Model

This advancement provides operators, developers, and regulators with an objective tool to detect risks before harm materializes. The Kansspelautoriteit recommends applying the model as part of comprehensive prevention strategies, facilitating personalized, evidence-based interventions, both in the local Dutch market and replicable in other European jurisdictions.

With the model publicly available, technology providers and operators can assess its effectiveness in various environments and adjust their own monitoring protocols. Regulatory authorities, for their part, gain an instrument to reinforce oversight and substantiate new player protection policies.

“Open access to the algorithm represents a step forward in transparency and risk prevention,” emphasized a spokesperson for the Kansspelautoriteit.

Implications for the Industry and the Prevention Landscape

Beyond online casinos, the model could set a precedent for the development of similar algorithms in other segments of digital gaming. The cooperation between academia and regulators, with funding directed towards prevention, is seen as a crucial mechanism to address emerging risks in a constantly evolving sector.

The publication of the algorithm on the Kansspelautoriteit's website facilitates access and collaboration among operators, researchers, and entities dedicated to responsible gambling.

The University of Amsterdam highlighted the independence of the process and the potential for the scientific community to evaluate, improve, and expand the model in the future.

Next Steps and Collaboration Opportunities

The official announcement from the University of Amsterdam invites both industry players and other academic institutions to join in the development and testing of the tool. Its open source nature opens the door to independent research and integration into early warning systems at the international level, including initiatives within the European Union and other regulated markets.

The Kansspelautoriteit will continue to oversee the adoption of the model and promote cooperation among various sector stakeholders and the research community.