Responsible Gaming in the Age of Machine Learning

Let’s face it, casino gaming is a huge business. It brings more than $500 billion in revenues every year from all around the world and the rise of the internet has fuelled its growth further. Today, online casino games has reached several people across all age groups through popular fantasy games.

The case of responsible gaming.

But with its growth comes another issue: the need to draw the line before excessive casino gaming becomes a problem, or as we like to call it, ‘irresponsible gaming’. Being a part of the industry, there’s no way we can shy away from addressing this issue.

Casino gaming is a lucrative business. It cuts across all social and demographic groups and can impact anybody – for whom the anticipation and thrill of casino gaming creates a natural high that can become addictive. So much so, that doctors are now prescribing drugs like Naltrexone, which is normally used to treat drug addicts and alcoholics, in an effort to stave off the craving of gamers.

According to reports, it is estimated that about 3 to 5 percent of people who indulge in casino gaming, get hooked on to it. And then the situation becomes a bit tricky. Because, this issue spews a web of difficulties for players themselves, their families and friends and the society at large.

Today, this is a serious issue in several parts of the world. And every year, millions of dollars are spent on helping players adhere to irresponsible gaming.

But, it’s a problem that can be solved.

But there are ways businesses can solve this. That too, efficiently. Think about it, using advanced technologies, we can analyse the users’ behaviour, preferences, actions and so much more.

Only, the data required to do this is not so easily available. All this information is hidden underneath the blanket of complex arrays of information, which when decoded, gives us the answers we are looking for.

So, how can organizations draw definite conclusions from varied sources of customer data and interpret them to help curate a positive change? The answer lies in revolutionary machine learning and business analytics.

ML and Business Analytics to the rescue.

Adaptive machine and business analytics, applying cutting-edge machine learning and other technologies are proving helpful in spotting anomalies among users in real-time and fighting this issue. Several data mining and machine learning techniques are being developed that are able to foresee and predict high-risk players by tracking their actions while he or she is still engaged in gaming.

There are several ways in which they work. One in specific works by calculating a risk score for players. Once the player crosses the safe threshold, he or she is sent out a personalised message along with a test that lets them reflect upon and understand their own behaviour – so that the problem can be nipped in the bud.

At BizAcuity, we’re helping our clients with it even smartly.

We are partners with several leading companies in the casino gaming industry. While we do our best each day to offer our clients the best uninterrupted casino gaming environment, we also try to create a healthy ecosystem of gamers and casinos.

Rooted in a comprehensive and proactive approach to real-time data analytics we aggregated player lifetime and frequency metrics and computed them to predict and analyse problem gaming behaviours or trends in players.

Some of the metrics we used were Lifetime Deposit, Last-7-Days Deposit, Last-15-Days Deposit, Last-30-Days Deposit, Minimum Deposit, Maximum Deposit, Average Deposit and so on. We used similar metrics for bets and wins and pre-computed and aggregated them.

This new approach is smarter and is helping organizations intervene and communicate with their customers in an intelligent, proactive and targeted manner.