In the digital age, where online gambling has become increasingly popular, the question of safety and responsible gambling has never been more pertinent. Despite numerous attempts to address the issue, the ever-escalating statistics on global gambling problems remain alarming. In this article, we present the groundbreaking approach developed exclusively with DigitalEjis, aiming to enable a safer environment for gamblers worldwide.
Imagine if someone could warn you to pause just before you were about to trip, preventing the fall and ensuring you continue your journey safely. That’s the essence of the new tool we have created with DigitalEjis for the world of gambling – foreseeing problems before they happen to protect players.
Other anti-addiction solutions rely on analysing betting data to determine if someone is becoming addicted. This is too late ! Once someone is on that path it is very difficult to reverse the decline without ceasing access to gambling platforms.
What makes our solution unique is that it predicts an individual’s chance to spiral into addiction before they have placed one bet ! Thus enabling the gambling operator to create a safe environment from the first bet and prevent them from ever becoming dangerously addicted.
The science behind the prediction
At the heart of this innovative approach is RAG (Red, Amber, Green). This unique application determines users’ predisposition to developing gambling addiction before they bet by combining our vast knowledge of psychology and neuroscience with cutting-edge computational methods with DigitalEjis’ operational expertise in the industry.
The resulting methodology is both complex and intricate but, at the same time, pragmatic and easy to deploy for the gambling operator.
The methodology was created by first aggregating all known scientific data about traits and mechanisms of addiction, specifically focusing on sports betting. Using advanced computational techniques, we distilled psychological scales that reflect specific traits predictive of a propensity to develop gambling addiction. We did not stop there. We then incorporated meta-data and innovative ways of capturing neurocognitive mechanisms from user interactions with online platforms. Using AI and data from thousands of sports betting users, models were developed to infer the risk of gambling addiction. Users were labeled green (low risk), red (high risk), or amber (uncertain but elevated risk). The gold standard of diagnostic criteria was used to identify users with gambling problems and label them for the AI models to accurately learn. The result was an astonishing 90% + accuracy in predicting an individuals’ predisposition to develop gambling addiction.
In essence we took the universally established methods of DIAGNOSING addiction and extended their power to PREDICTION.
What sets this model apart are its abilities to:
- predict risk even before problematic gambling patterns emerge; and
- determine a individuals’ propensity to develop a gambling addiction, even though they have never engaged with gambling in their life.