Going shopping used to mean heading to a store or mall. But today, customers are migrating from shopping in person to shopping online. The last two years of the pandemic accelerated the shift to ecommerce. As was noted in the Business Journals, for many brick-and-mortar malls, “the picture is grim” because the pandemic has stymied foot traffic and in-person activities and put online shopping into overdrive.

As shopping behavior changed, it’s important to recognize that businesses can still use traditional physical stores to offer differentiated services in a “hybrid” model. For example, retailers might offer customers the option for Buy Online Pickup In Store (BOPIS) and/or Buy Online Return in Store (BORIS).

Based on these trends, businesses must shift to ecommerce, gearing up with more advanced fraud prevention technologies. Keep in mind that if the company enables BOPIS and/or BORIS, it has to authenticate a customer instantly. If it’s a manual process and takes 24 hours, then the customer won’t wait—or this method might open the door for a fraudster to pick up the merchandise. Yet if an organization has made itself ready for ecommerce, there are even more sophisticated fraudsters they must watch out for. 

Recognizing fraud—it’s not abuse 

The effort to distinguish customers from fraudsters must go beyond a company’s internal data. Start with a global dataset. Since fraud has been perpetrated by individuals who are not customers, security teams need an identity graph to recognize bad actors. And since fraudsters are clever about spoofing their IP and hiding their identities, the team has to look beyond the obvious to identify patterns in usual characteristics. That takes sophisticated technology to surface those patterns and make decisions on transactions accurately and instantly—especially at scale. 

Now that’s just to stop fraud—policy abuse is entirely different. While fraud has been well-defined and black-and-white across merchants, abuse has more “gray area” and it’s harder to pin down. Fraud almost always takes place when an individual obscures their identity, while abuse often originates with legitimate consumers capitalizing on flexible return policies and promotions. To avoid deterring potentially good, long-term customers, businesses must stay thoughtful about where they set policy thresholds and how they manage abuse on an ongoing basis. 

Flagging false fraud alerts

A persona graph tool can also help merchants with false alerts on fraud. According to the Gartner Market Guide for Online Fraud Detection, merchants lose up to 75 times more revenue to false declines than to fraud. In the wake of COVID-19 and the shifting shopping patterns that it created, many new, completely legitimate online shoppers ended up getting declined because they were flagged falsely by fraud alerts. 

Research shows that it’s the new users on any ecommerce site who are the most vulnerable to this trend, being five to seven times more likely to be declined erroneously than returning customers. The top reason for this: with new users, the business lacked data on them. We refer to this as “new user, missed opportunity,” or NUMO. With a persona graph, merchants can notice and flag any similarities in both new and known customers. This significantly decreases the number of false declines, which helps merchants drive revenue and increase customer lifetime value.

It’s clear that forward-thinking merchants should focus on fraud as a way to address false declines while improving their customers’ experience and growing business revenue. The tools and technologies that online merchants use can help them effectively fight the increasing online fraud that’s an outcome of the consumer shift to ecommerce.

Yohanna Andom, senior product marketer, Forter