How Online Gambling Companies Use AI to Prevent Fraud

The realm of online gambling has experienced exponential growth over the years, attracting millions of players from New Zealand and across the globe. With this growth, the risk of fraud looms large. With the increased risk, companies like Mr Bet NZ are leveraging cutting-edge AI technologies to stay ahead of sophisticated threats, ensuring that players' securities are prioritised and improving the overall operational integrity of the gaming process. Join us as we venture on a journey to disclose how online gambling companies have been using artificial intelligence to prevent fraud in the trade.

An Overview of Artificial Intelligence Fraud Prevention

The realm of technology is increasingly changing to keep up with the prevailing times. With the pertinent changes in the field, AI has taken a leading role in the fraud detection capabilities of many online gambling site systems. As such, machine learning (ML) and pattern recognition are the frontline soldiers in this intriguing battle to keep the fraudsters away. These artificial intelligence systems possess analytic capabilities that can handle large data sets, helping to detect suspicious patterns that may point the powers that be towards fraudulent behaviours.

You see, conventional systems often rely on a predefined set of rules. What makes the infusion of AI into the fraud detection subject is the technology's ability to adapt, learn from new data, and offer improvements in regards to its detection capabilities. For instance, these advanced algorithms may analyse wagering behaviours and patterns across thousands of transactions. This analysis may become the basis for constituting what can be regarded as a "normal" way of acting for different punters. As such, if a player exhibits what is perceived to be abnormal behaviour, such as placing a significant wager at an unusual time, the system flags it as suspicious. Before getting ahead of ourselves, let's take you on a step-by-step journey of how the fraud detection process unfolds.

Modelling User Behavior

So, when looking out for fraudulent behaviours, what kind of accounts do the iGaming systems have to look out for? Consider, on one hand, a legitimate account and, on the other, a malicious account that has been compromised by a user who is not its original owner. Since newly created gaming accounts are rarely the subject of hacking, the major focus of both the systems and the fraudsters will be the developed accounts that have been active for several months or so. One aspect that will ultimately help detect fraudulent activities will be the historical data associated with the account. This historical data may be collected from the following sources:

• The user application journey: Which interface does the user normally interact with, and in which specific order? Is this contrary to the norm?
• The user journey features: Are there delays between clicks, swipes, taps, or any other actions in the gaming journey that may differ from the norm? Are the bonuses selected different from what is usually selected?

In traditional systems, anomalies may go unnoticed. However, with AI-powered systems, you have an algorithm that will automatically suspend the account, require additional authentication, or flag suspicious accounts for manual review.

Enhancing Security Measures With AI

While detecting anomalies is a great way to prevent fraud, it goes beyond just spotting the anomalies. For instance, the Know Your Customer (KYC) regulations that are usually enforced by many platforms often play a pivotal role in ensuring that user data is not compromised in any way or form. While traditional security measures usually entail manually verifying these details, the new world-order AI systems can automate this process. By enforcing measures like facial recognition, document scanning, and behavioural biometrics, you have a better working system.

On the part of secure transactions, artificial intelligence is also useful in analysing payment patterns and drawing out what it deems to be suspicious transactions. For instance, if a player who usually makes small transactions suddenly makes a big transaction out of the blue, then the system should automatically detect this transaction and put it on hold until the site verifies that it is the true account owner who is initiating the transaction.

Advanced algorithms are also vital for preventing money laundering activities which is prevalent in the industry. Once more, the key thing is in analysing the historical transactions. It may be looking out for suspicious transactions like massive deposits or withdrawals. This will go a long way towards ensuring that iGaming sites comply with Anti-Money Laundering (AML) regulations.

The Future of AI in iGaming Fraud Prevention

AI is still evolving, and as it is evolving, the fraud detection landscape in the industry continues to look promising. With emerging networks like deep learning and neural networks, we can only imagine how the online gambling landscape will look a few years from now on. Our early prediction is that we will have a safer gaming landscape moving into the future.