Responsible Gambling in the Era of Individualisation, by Rasmus Kjærgaard, CEO of Mindway AI

Rasmus Kjærgaard, CEO of Mindway AI, talks to iGamingFuture about the importance of an individualised approach to problem gambling.

Average is over. We are increasingly expecting a personalised service. Be it an online shopping experience with personalised recommendations or education of our children at school. Or if we fall ill, we expect personalised treatment tailored to our specific situation and variation of disease.

This is not egocentric arrogance but matters of efficiency. Shoppers save time when content is sorted appropriately and yes, stores likely sell more goods, and children learn more and quicker as education respects each student’s particular circumstances. And, there is no average patient. Although classical large-scale randomised clinical trials, guiding treatment around the globe, assume just that. However, evidence has it the other way around.

The most recent example is COVID-19. For some COVID-19 means a vague cold, for others it costs them their lives. The same with the vaccine – some experience no side effects at all while others fall ill.

Treatment strategies acknowledging lifestyle, demographics and genetic variations improve outcome. Similarly with early detection of disease: While there are population-wide so-called normal ranges, these may easily mask individual developments signalling a decline in important functionalities. Hence the classical importance of the family doctor, who follows individuals and notes changes in well-being.

So why would the same not hold true for detection and intervention in problem gambling? No two gamblers are alike, neither when it comes to their gambling behaviour nor their financial means, social background, educational level, mental health state, game type preferences etc. That also means that what is normal spending, normal behaviour etc. to one gambler can be signs of gambling getting out of hand for another gambler.

Identifying problem gambling is a complex task, particularly in the early stages. Symptoms may be vague just like with other diseases, for instance, cancer.

What we also know is that the earlier the detection, the better the treatment outcome. That is why we need to know what is normal for a particular gambler in order to identify changes.

So to truly understand a gambler and their risk profile, we need to consider his/her own pattern and level of gambling. Easier said than done.

With thousands of gamblers in a database who all differ we need to apply the family physician approach to avoid a similar scenario as we have seen with the COVID-19 example above. Gambling can be deadly to the very few who end up losing everything including the wish to be alive. But how do we identify for whom gambling will be fun and for whom it will be detrimental?

It is never enough to do a simple screening by looking at single factors such as money or time spent exclusively. We need an individualised approach.

To properly identify at-risk and problem gambling, a lot of data need to be analyzed at the individual level.

GameScanner by Mindway AI reveals the behaviour and decision making that lies behind gambling by analysing data and it clearly pinpoints how and why a gambler is categorized as an at-risk or problem gambler. In that sense, GameScanner can be compared to a virtual family physician or a virtual psychologist who knows the gamblers, so to speak, and follows their every move by monitoring them around the clock.

The solution assesses the data trail by looking at every event of every game of every single gambler, taking a broad number of factors and their interrelations into account. So, just like Google knows its users and presents search results based on their data trail and search history, GameScanner knows the preferences and behaviour of a gambler and therefore also knows when something is different and unusual.

But identifying isn’t enough – what good would it be for Google to know what their users like if they don’t convert this knowledge into giving them the right search results? The same with GameScanner – what good would it be for operators to know exactly what their gamblers’ risk profiles are without converting this knowledge into intervention?

The good news is that GameScanner delivers everything that is needed for risk profile specific intervention and thus both identifies possible problems and “treats” gamblers according to their profile. That is why we call GameScanner a virtual psychologist who knows the individual gambler well and understands when variations in his/her particular gambling style are harmless and when they become a cause of concern.

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