Fraudulent activity can cause significant damage to businesses, individuals and even entire economies. In fact, it’s estimated that billions of dollars are lost every year due to this type of crime. With this in mind, it’s safe to say that traditional methods of detecting and preventing fraud are limited and somewhat ineffective. However, thanks to the rise of machine learning, significant improvements are being made every day.

This is great news for businesses that want to keep themselves safe from financial deception which can be so devastating. Want to find out more? Keep reading as we explore how machine learning algorithms work and how they can be used to combat fraud.


What is machine learning?

Machine learning is a subset of artificial intelligence that involves training algorithms to learn patterns and make predictions based on data. In the context of fraud detection, machine learning models analyse information from various sources to identify patterns and anomalies that may indicate suspicious activity. These models can adapt and improve over time as they are exposed to more data, allowing for more accurate predictions and more effective fraud prevention.

How artificial intelligence can be used to fight against fraud

There are a number of ways that artificial intelligence can be harnessed to fight against fraud. Each has different advantages and can be used effectively in certain situations. When it comes to creating the strongest possible defense, it’s important to combine a variety of strategies. Below, we break down three examples of how artificial intelligence is currently being used to combat fraud.

1.  Analysing transaction data

One of the most common applications of machine learning in fraud detection is analysing transaction data. Machine learning models can be trained to detect unusual patterns or anomalies in transaction data that may indicate criminal activity. For example, if a customer suddenly starts making large purchases in a new location or from a new device, a machine learning model can flag this activity and alert the appropriate authorities. This approach can be particularly effective in detecting credit card fraud, which is common.

2.  Predictive modelling

Another way that machine learning can be applied to fraud detection is through the use of predictive modelling. Predictive modelling involves using historical data to make predictions about future events. When it comes to fraud detection, this strategy can be harnessed to identify customers who may be likely to engage in criminal activity. For instance, if a customer has a history of making high-risk transactions or has previously been flagged for fraud, a machine learning model can use this information to predict the chances of them engaging in fraudulent activity in the future.

3.  Network detection  

Machine learning can also be used to identify fraudulent networks or groups. Fraudulent networks can be difficult to detect using traditional methods, as they often involve multiple individuals working together to commit financial crimes. However, machine learning models can analyse data from many sources to identify patterns that may indicate the existence of a fraudulent network. For example, if several customers are making purchases from the same location or using the same device, a machine learning model can flag this activity for further investigation.

What’s on the horizon? The future of machine learning and fraud detection

Overall, machine learning has the potential to significantly improve fraud detection and prevention. By analysing transaction data, using predictive modelling, and identifying fraudulent networks, artificial intelligence models can help businesses and individuals stop fraudulent activity more effectively than ever before. As machine learning technology continues to evolve, it’s likely that we will see even more sophisticated and effective methods emerge.

Safeguard your brand by working with the best in the business

Want to safeguard your critical information? You need to work with the best in the business. At FraudWatch, we specialise in keeping brands like yours safe from fraud and criminal activity. Look to us for a range of security solutions relating to phishing, social media, mobile apps and more. Our experts can also help with dark web monitoring and threat intelligence.

Get in touch today to book a consultation with our team.