Fraud detection and prevention have become crucial facets of the eCommerce arena and many other industries in recent years as online shopping surges in popularity and more individuals and companies are targeted. eCommerce fraud is expected to spike 18 percent this year and cost more than $20 billion globally, up from the $17.5 billion it cost last year.
Businesses are expected to spend $40.8 billion on cybersecurity, fraud prevention and other forms of protection by 2026, an increase from $18.2 billion in 2020. These expenditures will largely focus on legacy fraud prevention measures like digital signatures, multifactor authentication (MFA) and password improvement initiatives, however, which can cause customers severe frustration and can even scare them away entirely through false positives.
Behavioral analytics, on the other hand, is a fraud prevention method that runs seamlessly in the background and can reduce customer friction as well as analyze which points in the checkout process result in the highest abandonment rates. This makes the technology uniquely capable of providing vital data to companies to improve their conversion rates. The following Deep Dive examines the frictions customers face with legacy fraud prevention systems and explores how behavioral analytics can ease these processes and improve conversion.
Frictions in traditional fraud prevention systems
The main problem with traditional fraud prevention systems is that they require additional information from customers on top of what they provide to open accounts or make purchases, such as entering passwords. This can be quick and easy by itself but is frequently complicated by websites’ insistence on specific rules such as requiring numbers, capitalization or special characters. This essentially leaves most customers with two options: painstakingly memorizing each password they have and its particular formatting quirks, or joining with the 72 percent of their peers who recycle passwords despite the known security risks of doing so.
Many eCommerce websites have attempted to introduce password alternatives like MFA to limit this practice and improve customers’ security, but this can come at the severe cost of customer convenience. Sixty-nine percent of consumers abandon purchases at checkout, and some of the most-cited reasons involve excessive security complications. Twenty-one percent of consumers said that the process took too long, for example, while 18 percent pointed to excessive security checks and 11 percent said their payments were declined, possibly due to a false positive fraud flag. Only 17 percent said they abandoned their carts because they were concerned about payment security, indicating that convenience and seamlessness trump fraud risks for many consumers.
Removing security checks entirely is obviously not an option, but eTailers can certainly improve their conversion rates by implementing more seamless fraud detection methods like behavioral analytics. These systems have the added bonus of detecting other frictions at the point of checkout, boosting conversion rates even further.
How behavioral analytics improves conversion
Behavioral analytics is unlike other verification systems in that it does not require customers to perform extra steps. It instead observes users’ entry of details that are already required, such as their names, usernames or addresses. Legitimate customers have presumably been spelling their own names for years and can enter them quickly and with few errors, while fraudsters might introduce misspellings while typing in unfamiliar names or copying and pasting them into fields from another form — which can be a warning sign as well. These behavioral analyses are performed behind the scenes, reducing the steps required for a checkout or application process and eliminating potential roadblocks.
Customer conversion can be further improved by deploying behavioral analytics to examine other frictions in the checkout process in addition to monitoring for fraud. An application form that asks for an obscure piece of information that requires potential customers to get up and hunt down a document could cause them to abandon the process entirely, for example, but traditional systems might not detect this exact breakpoint. A behavioral analytics system will, however, according to Neuro-ID’s director of behavioral analytics James Craddick. He mentioned in a recent interview with PYMNTS that one Neuro-ID partner was able to reduce customer friction on a birthdate field by 20 percent, ultimately reducing the company’s abandonment rate by 40 percent.
Fraud is a massive issue that can cost companies huge sums of dollars, but the opportunity cost from customer abandonment can equal or exceed these sums. Behavioral analytics could be the key to reducing both threats in one fell swoop.
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