The future of commerce and the threat of card fraud


‘Contactless’ appears to be the most notable trend to gain attention over the past year and a half, and consumers around the world are turning to the quick, easy, and contactless shopping experience they are experiencing. can get online. With the rise of e-commerce, it’s clear that cardless payments (CNP) are likely to become the norm over the next few years. In fact, recent data from Mastercard shows that in 2021, more than half of Americans are now using contactless payments.

About the Author

Tan Truong is CIO of Vesta.

However, every light has its shadow, and with the increase in CNP payments so does the increase in CNP fraud. For those unfamiliar with the term, CNP fraud is a credit card scam in which a fraudster uses someone else’s compromised card information to make a purchase remotely. Since the card and cardholder are not physically present (and fraudsters often steal additional information like CVV and billing address), it can be extremely difficult for merchants to verify identity. of the buyer. It also forces merchants to recruit additional labor in order to pay close attention to new payment methods, transaction dynamics, and customer preferences that are continually changing at a rapid pace.

Two types of CNP fraud

At Vesta, we’ve been helping merchants prevent CNP fraud for over 25 years, and what makes it such a difficult issue is the fact that scammers are constantly evolving their tactics. There are two main types of CNP fraud. The first is direct link fraud, which means that there is some kind of red flag that a merchant can look for to identify a transaction as fraudulent. For example, if the same credit card is used to make multiple purchases within a five minute window and the shipping address does not match the billing address, this is a clear sign that the orders may be fraudulent. and the trader should investigate further before approving the transactions.

With an indirect link, there are no clear signs for traders to watch out for, making it incredibly difficult to spot and prevent, especially on a global scale. In fact, data from our recent Global Card Not Present Fraud (CNP) report revealed that indirect-linking fraudulent transactions are on the rise, with the percentage of overall indirect-linking fraud steadily increasing quarter-to-quarter throughout. of 2020. And to make matters even more difficult, the value of fraudulent transactions with an indirect link is generally higher than those with a direct link, making it an even more expensive and complicated problem for traders to deal with.

Machine learning to fight fraud

With all of this in mind, there is no doubt that CNP fraud with an indirect link presents one of the most unique and costly challenges for traders, but there is hope. Thanks to advances in machine learning, traders have the means to tackle this problem head-on. Sophisticated machine learning models can identify connections between disparate transactional data points to identify potential frauds in real time, allowing traders to make an instant decision on whether to accept or reject a transaction. While machine learning models can effectively prevent CNP fraud with an indirect link, it is important to consider the data they are trained on when evaluating different solutions.

These models are only as good as the data that feeds them, so traders need to pay attention to both the depth and breadth of the data. To be more specific, you want models that have been trained over years of transactional data – that’s depth – and you also want them to have been trained on global data sets, that’s where it comes in. the width. Historical data ensures machine learning models understand how CNP fraud has evolved over time, and global data ensures that these models can identify fraud no matter where it came from. Scammers don’t operate from one place – they’re all over the world, so your machine learning models need to have a global perspective.

Invest in protection

For retailers who are still in the early stages of their digital transformation, implementing a brand new machine learning solution just to tackle CNP fraud with an indirect link may seem more complicated than it is worth. worth it, but I caution against this state of mind. Aside from the chargeback fees, which can add up quickly and really eat into your margins, there is a reputational risk to consider. If you were going to order new shoes and the retailer refused your order for no apparent reason, would you shop from that retailer again? No, and neither do most consumers. In a highly competitive retail market, it’s important to protect your brand’s reputation and provide a seamless experience for buyers.

Without an effective CNP fraud solution, you will either end up rejecting too many legitimate transactions or accepting too many fraudulent transactions, which is why it is important to invest in a solution that strikes the right balance between maximizing sales approvals. legitimate and block the bad ones. Whether you build this solution in-house or in partnership with a third party depends on your own unique needs and existing resources, but investing in this solution today will allow you to stay ahead of scammers and protect your business for the better. coming years.

If you are concerned about online security, check out our best online cybersecurity courses.

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