Spain to Introduce an AI-Powered RG System Which Flags Issues in Real Time

Spain Plans to Launch an AI-Based Responsible Gambling System

Spain’s gambling authority, the DGOJ, has initiated a public consultation running until September 25, 2025. The purpose is to develop an innovative AI-powered system aimed at identifying signs of gambling harm and excessive spending by monitoring 60 specific behavioral indicators.

An Ambitious Regulatory Initiative

If implemented, this system would represent one of the most comprehensive regulatory tools in Europe. The DGOJ’s criteria include tracking factors such as the frequency of gambling sessions, patterns of wins and losses, and the ways deposits and withdrawals happen.

The system will leverage advanced machine learning techniques, specifically XGBoost algorithms, to analyze the gathered data and better assess whether a player might be experiencing gambling-related problems.

Scope and Limitations of the Proposal

Despite its broad approach, the system will focus solely on sports betting and online casino activities, excluding lottery games. This exclusion is significant since lotteries are extremely popular in Spain and often involve a wide demographic, including younger individuals.

By not including lotteries, the DGOJ’s initiative may face criticism for not fully aligning with its objective of safeguarding all players effectively. Currently, major lottery operators such as SELAE and ONCE are not part of the system, though this aspect could be re-evaluated during ongoing discussions.

A Collaborative and Comprehensive Regulatory Effort

The DGOJ is actively seeking feedback from a broad range of contributors including operators, researchers, stakeholders, technology companies, and the general public. With its 60 parameters, the system is still in development and far from launch.

This project aims not to penalize operators arbitrarily but to provide a government-supported framework that empowers licensed gambling companies to promote safer and more responsible gambling behavior among their customers.