What’s the costliest fraud-related problem for most e-commerce merchants? In most cases, it’s not fraud itself, but orders that are rejected because they’re mistaken for fraud. These false declines (also known as false positives) are an expensive problem in the short term and over the long run. That’s because not only do false declines leave money on the table, they also put merchants’ relationships with their customers at risk.
The scope of the false decline problem is huge, although exact numbers are hard to come by, for reasons we’ll discuss in a bit. Some reports estimate that as many as 30% of rejected orders are not fraud. In the retail edition of its 2018 True Cost of Fraud Survey, LexisNexis found false decline rates ranging from 18 to 28%, depending on the size of the merchant and the type of goods they sell.
With such a high percentage of good orders tossed out along with fraud attempts, it’s not surprising that the retail industry loses a lot of money on false declines. Aite Group estimated that $331 billion in CNP orders were falsely declined in 2018 (in the U.S. alone). Meanwhile, worldwide yearly e-commerce fraud losses range from $25 to $40 billion, according to Accenture.
If false declines cost so much, why haven’t they been stopped?
False declines are often invisible to merchants because of the way fraud metrics are defined. Many merchants assume that all the automated declines generated by their automated fraud screening programs are accurate. And there’s rarely any follow-up analysis or investigation to see which declines were valid and which were mistakes. That means a lot of merchants have no idea how many of their declined transactions were good orders.
It also means merchants don’t know how much those lost orders were worth—and the costs go beyond the dollar value of the rejected orders.
False declines can drive away merchants’ best customers
If the billions of dollars lost to false declines each year isn’t alarming enough, consider the effect false declines have on customer relationships. Between 33% and 40% of consumers say they won’t shop again with a merchant that falsely rejects their order. Instead, they abandon their carts and take their business to the competition. So false declines increase customer churn and reduce the average lifetime value of those customers.
What’s worse is that the customers who are most often hit with false declines are precisely the ones that merchants want to keep. More than half of orders that are declined in error are placed by returning customers. And customers in the highest income brackets—$800,000 a year and up—are at least twice as likely to be declined by mistake as consumers with lower incomes.
Why do wealthy shoppers get declined so often? Buying expensive items with rush shipping, ordering from multiple locations around the world, and shipping to a variety of addresses can indicate a well-heeled lifestyle, but those are also behaviors that can indicate fraud attempts. When a screening program can’t tell the difference, those well-to-do customers get shown the door, which is bad news for merchants.
False declines can erode a store’s reputation
Not only will many shoppers abandon online stores after they’ve been rejected, they can influence other shoppers to avoid those merchants, too. At best, a rejected customer will not recommend that store to their friends and family. But they may also share their negative experience on social media and review sites, which can spread bad word-of-mouth to a wider audience of potential customers.
False declines can skew a store’s fraud detection capabilities
Automated order screening programs that use algorithms to spot fraud are only as good as the data they take in. If all rejected orders are considered genuine fraud, then over time, the program’s definition of fraud will skew toward the criteria that lead to false positives. That can lead to more false positives, more lost revenue and more customer attrition.
What does it take to stop false declines?
The first step to reducing false declines is knowing where your store stands. This means analyzing your store’s declines to see which were truly fraud and which were declined in error. That gives your business a benchmark to see how much revenue you’re turning away and how much you stand to gain by fixing the problem.
Next, look for solutions that double-check orders when they’re flagged for fraud, before they’re declined. Most experts in CNP fraud prevention recommend a layered approach that allows for more than one evaluation of flagged transactions. Adding another layer to your screening process can reduce your false decline rate quickly. And the data it produces can help your automated screening system “learn” to better tell the difference between fraud and good orders, so that over time, fewer orders are mistakenly flagged for further screening.
Reducing false declines requires that merchants change the way they approach fraud prevention, but that change can pay off in the form of higher revenue, higher customer lifetime value, and better relationships with customers.
