How Machine Learning (ML) is used in iGaming

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The advent of technology has spurred revolutions in nearly every industry today. When we mention technology here, we refer to all its various branches, which we possibly can’t discuss in detail in one article. So, this article will focus on the huge impact machine learning, a relatively new field that has come to the limelight in recent years, has on the online gaming industry.

Machine learning (ML) is the ability for a system to learn and improve through the experience without being programmed to do so. In essence, systems can learn from data, recognize patterns, and make choices independently with little or no human intervention. It’s a subset of a much broader discipline known as artificial intelligence or AI. A common application of machine learning is to generate weather forecasts. According to PWC’s predictions, AI would have contributed a whopping $15.7 trillion to the global economy by 2030.

With such stats, it’s no surprise AI and ML have had such easy penetration into industries, with the gaming industry being no exception. Without a doubt, the introduction of ML and AI in the gambling world has partly been responsible for the emergence of iGaming as one of the world’s fastest-growing industries. As of 2016, it had a net worth of $41.78 billion. According to Transparency Market Research, it’s expected to almost triple that by 2024.

Applications of Machine Learning in iGaming

Mobility is unquestionably one of the most appealing aspects of modern technology. Nobody likes to go great distances to casinos or spend their weekends cooped up in a congested betting shop. This tech-savvy generation of gamblers and gamers wants a user-friendly experience that allows them to play whenever and wherever they choose. You could say it was inevitable the gaming industry would eventually embrace ML to bring forth some of the following innovations we see today.

1. Detecting fraudulent activities

Fraudulent activities on their platforms have always been a significant issue for managers of online gaming platforms. It damages your brand reputation, invariably turning players away. Tackling this has not been an easy task, at least not until now.

Through ML tools, it is now possible to have all game proceedings continuously monitored, and any suspicious activity can be timely investigated and dealt with. Even the most skilled fraudsters would be left with nothing but the slimmest of chances against a constantly improving system.

2. 24/7 customer support

Whenever issues spring up, users can have their issues resolved in just a matter of seconds as they are provided with a service feature known as a chatbot. Although some problems may prove too difficult, chatbots can adequately handle 80 percent of issues users may present them with.

3. Collecting and analyzing customer data

Operators of gaming platforms often use ML tools to collect data on users and analyze that data. This practice provides a better understanding of the users and develops ways to boost retention and engagement. It could be achieved by various means.

For example, players give their impressions of the game’s interface, albeit unconsciously, by their actions. These behaviors are analyzed, providing operators information that will help them make the game more appealing to players.

Another scenario would be to use the data gathered on a user, such as their betting preferences, to provide offers, promotions, and other services tailored just for them, resulting in larger sales.

4. Adaptable player characters

As a user transverses from a beginner to a pro, the conventional NPCs (Non-Playable Characters) with pre-determined functions put up less of a fight. Having become familiar with their movements, it’s just not that interesting anymore, and you’re left with this bittersweet feeling after leveling up your skills.

However, ML takes away this predictability and keeps users excited. The more your skills develop, the smarter the NPCs become. Companies are putting in immense work to try to implement this technology. For instance, EA trains its NPCs by imitating the most skilled players.

5. Generating sportsbook datasets

Data is an invaluable asset to any business in the iGaming industry. Take a sports betting platform, for example. To provide the best of odds, they need a constant supply of data and quite a large amount. But most importantly, the data has to be accurate. Machine learning software makes this incredibly daunting task quick and efficient.

The best is yet to come

One thing is for sure – we haven’t seen the full potential of machine learning and what it has to offer the iGaming industry. After all, games can still become even more realistic and provide users with even more mesmerizing experiences. The fact that this goal, among others, hasn’t been achieved yet can only mean there are still some hurdles to overcome. Hence, we can only anticipate these greater innovations that have yet to be actualized.

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