Countermeasures to Synthetic Fraud are Essential for Consumer Protection

Here’s a startling figure: online customers will abandon roughly seven out of ten transactions they initiate. Ecommerce merchants are under tremendous pressure to reduce friction, speed up processes and optimize the customer experience to try and prevent fraud, keep customers engaged and prevent cart abandonment. In response, merchants often feel incentivized to cut corners on security best practices.

For example, the 2017 Financial Impact of Fraud Study reveals that one in five merchants opt not to use 3-D Secure for fear that it will create more transaction friction. The result: Merchants end up experiencing more fraud incidents. The same report reveals the average merchant loses a shocking 8% of their annual revenue to fraud.

Of course, we shouldn’t think about fraud as a singular issue with clearly defined risk factors. Instead, merchants are under attack from a variety of different sources. Synthetic identity fraud is among the fastest growing of these, which is little surprise given the abundance of consumer data floating around out there.

The Synthetic Fraud Threat

Like an account takeover attack, synthetic identify fraud (or simply synthetic fraud) is a form of identity theft. Both tactics involve a fraudster leveraging stolen consumer data. With synthetic fraud, though, the criminal uses real user information to create a fake, “synthetic” identity.

Bad actors may have pieces of data produced by multiple different users. Social Security numbers (SSN), especially those with little or no established credit history, are popular targets for synthetic fraudsters. This makes children especially attractive targets for these attacks. More than one million children fell victim to synthetic fraud in 2017 alone, and roughly 10% of all children currently have someone using their SSN for lines of credit.

Synthetic fraud is also very difficult to detect, which makes it an exceedingly popular tactic. Eighty-five percent of all identity fraud attacks perpetrated in the U.S. are synthetic, and we can trace up to 80% of all criminal fraud losses to a synthetic source. Banks suffer from this too, with synthetic fraud causing nearly 20% of credit card charge-offs, or bad and uncollectable debts that weigh on these institutions’ ledgers.

All totaled, synthetic identity fraud may drive up to $48 billion in losses every year by 2023 – and that’s only counting what we can identify. This appears to put merchants in a difficult position: Apply greater scrutiny to transactions and risk losing more sales or keep standards lax and suffer the resulting fraud losses. Fortunately, it’s not as black and white as it seems.

A Multilayer Approach to Synthetic Fraud

So, merchants need a way to verify users that specifically addresses these synthetic fraud concerns. The problem is that this calls for access to substantial amounts of customer data to gauge effectively, which merchants generally do not have. Not only that but conducting individualized reviews of each transaction would be incredibly time- and resource-intensive.

The best solution is to employ a combination of machine learning and multilayer authentication techniques. Using redundant technologies to validate users provides a much more detailed profile of each individual. You also have greater insight regarding legitimate and fraudulent transactions, which will refine your system’s ability to identify threats in the future.

There are numerous tools and techniques available to help identify fraud. That said, merchants still need outside help.

Financial institutions should make use of advanced screening before issuing lines of credit to users. Most rely primarily on the customer’s SSN, which isn’t helpful when they are so often stolen. At this point, the majority of Americans are at risk of personal data compromise. Thus, banks need to be proactive and take it upon themselves to both review their authentication methods and promote consumer education as a priority within their operations.

There’s no guaranteed way to stop synthetic fraud attacks. However, a coordinated and dynamic effort involving merchants, consumers and banks can go a long way toward preventing incidents.

Monica Eaton-Cardone is the COO and co-founder of Chargebacks911