The Key to Preparing for E-Commerce Fraud in 2020
With online fraud transactions forecast to reach $25.6 billion in 2020, retailers need to heavily prioritize fraud prevention in the first half of this year. This begins with understanding vulnerable areas and how to combat fraud while protecting profitability and customer satisfaction.
E-Gift Cards Are a Top Target
EMV chip cards achieved their intended purpose: they effectively reduced card-present (CP) fraud for in-store retail sales by 80 percent between 2015 and 2018. However, decreased CP fraud attacks subsequently increased activity in card-not-present (CNP) e-commerce transactions, particularly with e-gift cards.
The convenience e-gift cards provide for customers is critical to customer service, however, the instant delivery that shoppers expect makes them a ripe target for fraudsters. Immediate delivery and activation make it difficult to spot fraud and stop bad orders before a criminal gets their hands on an e-gift card, which is very easily monetized. According to a recent Radial CNP report, the attack rate for open-loop gift cards (those branded by Visa and Mastercard not connected with a specific retailer) is nearly 21 percent, while entertainment companies that offer digital gift cards see attack rates of 24 percent. Additionally, e-gift cards offered by jewelry merchants, which top the list, are attacked by fraudsters nearly 28 percent of the time.
With the extremely short turnaround time for transaction reviews, effective systems that automate fraud checks are paramount over manual reviews, which can take much more time. While automation may reign supreme for gift cards, it’s important to strike the right balance between man and machine when it comes to overall fraud management.
Man and Machine: How to Maximize Fraud Prevention
To preserve the customer experience and provide fast and effective fraud prevention, many retailers are taking a multipronged approach to managing fraud. It has become best practice to include manual reviews coupled with machine learning technologies to save time and money. Nearly 30 percent of merchants believe controlling fraud is too expensive, which is why many are turning to this duet of strategies. However, this approach really is all about balance for effectiveness and management, and it remains crucial to not rely on either too heavily.
Machine learning is the heavy lifting of fraud detection, and should be used to identify transactions that look suspicious. For instance, if the purchase doesn’t look like it belongs to the consumer who owns the card, transactions will then get flagged. Those flagged transactions should be followed by a manual review, which gives the company an opportunity to investigate the discrepancies and see if irregularities can be explained (e.g., the order could be shipping to another country or address that's not associated with that consumer). Manual research could identify that the consumer is simply on vacation and assuage the concerns to allow the transaction to go through, saving the sale in the process.
If retailers relied only on automated tools, it would result in turning away too many potential customers who weren’t actually fraudulent, effectively leaving money on the table. Savvy retailers today realize a comprehensive fraud strategy isn’t all about gadgets; instead, it requires both the power of data and the human touch.
Maximizing Conversions Around Suspected Fraud
Declines picked up by an automated system can happen for a number of reasons, including an invalid card, account limits exceeded or suspected fraud. In the event of suspected fraud, retailers can use alternative means of authentication, including machine learning, manual reviews and tools that provide deeper insights into customer behaviors such as device activity, in order to support a friction-free customer experience while helping to maximize sales conversions. The more data retailers can compile on consumer behaviors and specific purchasing activities will enable more informed decisions when it comes to reviewing and approving transactions.
Retailers that don’t take action to optimize conversions risk fewer sales and lower revenue. Even worse, if retailers don’t deliver a fast, convenient checkout experience, they could lose not only the sale but the entire customer relationship.
As fraud will only continue to grow as online sales increase, retailers must prioritize fraud management solutions that protect their bottom lines while still keeping customer information safe. Retailers that strike the right balance between machine learning and manual review processes will build strong customer relationships and revenue streams while fighting off today’s faceless villains.
KC Fox is senior vice president of technology services at Radial, a leading omnichannel e-commerce company with a focus on fraud prevention for some of the world’s top retail brands.