KSA-backed algorithm aims to score players’ high-risk behaviours

The Dutch gambling authority is utilising an algorithm developed to estimate the risk of online casino players based on their actual gambling behaviour.

Kansspelautoriteit (KSA) describes the algorithm as an ‘independent, transparent tool for the early detection of high-risk gambling behaviour’, based on machine learning that looks at a player’s actual behaviour to calculate a risk score.

Calculating the risk score involves analysing an individual’s patterns of how much or how often they gamble, at what times and frequency they wager, as well as how winning and losing streaks change their gambling habits.

KSA noted that the model can be used by licensed operators to improve their own duty of care, but the regulator highlighted that it offers ‘no guarantees; it can only serve as a supplementary component of duty of care measures’.

The algorithm is designed by researchers from the University of Amsterdam (UvA) – PhD candidate Charles de Leau and Professors Reinout Wiers (Psychology)..

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