The growth and evolution of ecommerce over the past two years has been nothing short of stunning.
Do you know what else has been stunning? The growth and evolution of the targets and techniques of those who seek to profit from online fraud and policy abuse. The COVID-19 pandemic and the dramatic shift to online shopping it caused have opened new and broader opportunities for those who game the system.
Think: payment fraud, return abuse, false claims that delivered items didn’t arrive, and the deployment of bots to aid in fraud schemes. These elements all present rising dangers to online merchants in 2022—but maybe not the dangers you first think of.
Fraudulent orders might not be the biggest threat to merchants’ revenue
Of course it’s bad for business to be swindled by a fraudster who’s using someone else’s credit card or returning counterfeit luxury items for refunds...but the bigger danger is that innovation by fraud rings could lead some to overreact—to decline legitimate orders for fear they might be fraudulent. Or perhaps they’ll look to build other barriers, such as making returns more difficult or slowing down refunds in order to be sure they are not being taken advantage of.
While such caution is understandable, these barriers to commerce devastate the relationship between consumers and retailers. Turning down a solid order from a good customer costs a retailer the immediate sale, of course—Research 451 found that retailers missed out on $16 billion in sales over a 12-month period due to incorrectly declined orders. But giving in to fear of fraud and policy abuse also does severe—and often fatal—damage to a retailer’s relationship with their customers. In fact, more than 65% of consumers said they would refuse to shop again with an online retailer that rejected their order for no apparent reason, according to a Signifyd consumer survey conducted by Survata.
And requiring customers to jump through hoops to return an item—or rejecting a legitimate return request altogether—is just as disastrous. Three-quarters of consumers surveyed by Signifyd said having a bad return experience was enough for them to quit shopping with a retailer altogether.
All this leads us to two questions: How did we get here? And what can merchants do to avoid turning away good orders, good returns and good customers?
How did we get here?
The increase in fraud and abuse followed the growth of ecommerce that began with the early pandemic lockdowns and continued as consumers increasingly discovered they liked the convenience of online shopping. According to Signifyd Ecommerce Pulse data, ecommerce sales increased by nearly 50% during the first year of the pandemic, including consumers who had never shopped online before. And while growth has cooled as the pandemic has dragged on, ecommerce continues to grow at an impressive pace.
Unfortunately, fraudsters followed. At its most recent reading in February 2022, Signifyd’s Fraud Pressure Index was up 400% over its level at the start of the pandemic. The index tracks the change in the number of orders on Signifyd’s network that contain enough red flags to be assumed fraudulent.
What can retailers do?
In the face of the rapid changes in the nature and frequency of ecommerce fraud, retailers need to strike a balance between protecting their businesses and providing their customers with a buying experience that will keep them coming back. One path to achieving this? Understanding the identity and intent behind every order.
Gaining this high level of insight calls for building or joining a large network of retailers that can provide a vast amount of transaction data. By applying machine learning to mountains of network transaction data, models can recognize patterns that instantly establish whether incoming orders are legitimate or fraudulent—all while automating a merchant’s order flow.
The same principle holds for assessing chargeback claims—claims that an order never arrived or that the item that did arrive was significantly different from its description. Knowing the identity and intent behind return requests also means a merchant can determine how a request should be handled based on the level of risk the return presents.
The strength of a network and the power of machine learning allow merchants to stay a step ahead of fraudsters in a time of transformation, all while providing customers with memorable experiences that will keep them coming back.
Given the greater fraud and abuse threat that merchants now face, retailers should consider:
- Building an intelligence network beyond its brand by recruiting other retailers to share limited transaction data to help provide insight to the identity and intent behind every order.
- Expanding the use of their customer data platform beyond marketing to provide intelligence concerning customer behavior when it comes to returns and refunds
- Creating a feedback loop based on customer complaints that identifies false declines and points the way to reducing them.
- Turning to commerce protection providers like Signifyd to supply insights driven by the transaction and behavioral intelligence produced by thousands of merchants around the world.
Contributed by the Editorial Team of Miva Partner Signifyd
