With last year’s enormously rapid migration toward digital transactions, crooks saw tons of new opportunities to exploit unaware online shoppers. 

Synthetic identity fraud is one of the schemes that are steadily on the rise, where criminals use a mixture of factual and false information (including phone numbers, emails, physical addresses) – to build an identity that can be used to purchase products online.

These artificial identities are built to seem like a person who is “new to the world”, with just enough info to make it seem like someone who has recently changed their name or address. This is to make it seem like there is just enough pieces of info to where it is compelling to say that it’s a real person. Criminals then use these fake identities to get access to credit, and then use that to purchase goods online.

Security Experts have been aware of synthetic identity fraud since around January 2019, flagging it as one of the fastest-growing type of financial crime. Now, in 2021, with online stores bigger than ever, fraudsters are taking full advantage of this tactic.

How does this impact online merchants?

For the most part, your store most likely won’t be targeted by these fraudsters, but the trickle-down effect could still effect the eCommerce industry as a whole, as large-scale fraud increases the cost of business for everyone. 

Also, since a fragment of the information criminals use is factual, retailers should secure their systems to prevent data breaches – to prevent the leaking of any personal information of their shoppers.

Criminals use these fake identities to purchase, or effectively “steal” from online merchants.

Ultimately, the impact of this, and other fraud schemes, might lower the chances of shoppers choosing an online retailer – costing merchants valuable business.

How are companies combating synthetic shoppers?

The problem with spotting synthetic identities, is locating what information is being manipulated and how. This makes it extremely difficult to detect and develop detection methods for this type of fraud, as all this information may look very real.

One of the companies on the frontlines of fighting online fraud , Experian, are attempting to artificial intelligence and machine learning to identify how criminals are manipulating data.

Experian then uses this information to target synthetic identities, but this approach requires a large amount of data to be collection in order to compare and cross reference information – to spot small statsitical anomalies.

Even the U.S Federal Reserve System is working stakeholders to fight this incredibly nuanced fraud method.

However, Experian has run into a big problem using this method – false positives, which might lead to suspecting a perfectly good customer of fraud. Unfortunately, this is just the nature of artificial intelligence, as it learns from its own mistakes; whether you are an online store or a bank, you don’t want to lose a customer like that.

A light at the end of the tunnel though, is that there is value in selling the product to someone who is potentially a criminal, but might not be. This is where artificial intellegence comes in handy – as a second line of defence. In this scenario, the AI will flag a potential high-risk consumer, but it is up to the owner of the store to decide how to manage that risk. This is very helpful, as the store owner can then attempt to reach out to the customer, to ensure their validity. Although this sacrifices frictionless shopping, it is well worth the effort.

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