Machine learning plays a pivotal role in effective fraud prevention systems. In this article, learn how machine learning can significantly improve your business’ ability to stop fraud attacks.

With the recent surge in e-commerce usage globally, the possibility of an online fraud attack is at an all-time high. e-commerce retailers stand to lose over US$20 billion in 2021 due to online fraudulent attacks.

This would represent an 18% increase in fraud losses compared to the US$17.5 billion recorded in 2020.

Customers want to have the assurance that they can purchase products without experiencing a false decline, and merchants want to feel that they can trust the legitimacy of new incoming transactions.

This is where machine learning comes into play.

In this article, we’ll take a close look at the world of machine learning as it pertains to e-commerce fraud prevention.

By the end, you should understand the benefits of using a fraud solution that leverages machine learning, and why this technology is essential to effectively stopping e-commerce fraud attacks.

What is Machine Learning?

It has been ten years since IBM’s Watson computer won Jeopardy on national television against two human opponents. It was able to do this through a set of functions that had enabled it to learn the rules of the English language.

Through these rules, it made connections between words and could work out the Jeopardy question from the answer given by the host.

This is only one example of how machine learning technology works, but it can extend to a variety of different use cases.

Machine learning is a branch of artificial intelligence (AI) that focuses on using data and algorithms to imitate the way a human would learn.

Machine learning enables fraud prevention systems to gradually improve how they identity and stop fraudulent transactions without the use of manual review.

Machine Learning in eCommerce Fraud Prevention

Similar to how the Watson computer used machine learning on Jeopardy to learn the English language, fraud solutions like Vesta Payment Guarantee use this technology to learn the patterns and behaviours associated with legitimate and fraudulent transactions.

By investigating all of the variables and pieces of data associated with an approved or declined transaction, a fraud solution can fine-tune its decisioning engine so there’s a smaller margin of error.

Here are the three key benefits to using machine learning to stop fraud attacks from impacting your e-commerce business:

1. No Impediment to the Customer Journey

If you rely on manual transaction review to identify and stop fraud, it’s likely that you deal with a high volume of false declines.

Consumers that have orders declined due to suspected fraudulent activity will almost never return to buy from that retailer, so it’s important that you work to minimise false declines as much as possible.

Machine learning enables fraud prevention solutions to accurately determine the legitimacy of a transaction without causing any unnecessary friction during the checkout process.

False declines can be significantly reduced, resulting in a smoother customer journey and quicker checkout experience.

2. Reduced Operational Costs

Machine learning can effectively eliminate the need for manual transaction review.

If you currently use a team of fraud analysts to review suspicious transactions, it might be time to consider investing in a fraud prevention solution that will perform that job quicker and more accurately.

Don’t let operational costs associated with fraud cut into your bottom line. Using a fraud solution that leverages machine learning will significantly reduce your operational costs, and eliminate the possibility of human error.

3. Drastically Reduce False Declines

Machine learning has benefits besides determining when there is a fraudulent transaction. Fraud prevention technology is also better at identifying real purchases too.

This prevents customers who have done nothing wrong from hearing they cannot make purchases. Thus your customer’s faith in your ability to detect eCommerce fraud will not diminish and their time will not be wasted.

First appeared on Vesta’s Blog on eCommerce Fraud.