Now that it’s well into 2020, we’re in the midst of a
rapidly evolving fraud landscape. Gone are the days where fraudsters primarily
operated in the physical world, using stolen credit cards to make transactions.
Instead, as society has become increasingly digital, so have fraudsters.
Card-not-present fraud has proliferated, with everything from account takeovers
to synthetic identity fraud on the rise.

To better understand the shifting fraud landscape and what
solutions are needed to keep up, PaymentsJournal sat down with David Barnhardt,
Chief Experience Officer at GIACT, and Tim Sloane, VP of Payments Innovation at
Mercator Advisory Group.

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The Frankenstein of
fraud: Synthetic identity fraud is on the rise

As Barnhardt has previously discussed,
synthetic identity fraud has become a major problem in the payments industry.
However, despite its prevalence, this fraud vector remains hard to detect.
Worse yet, many in the payments industry don’t even know what it is.

“A lot of times, companies confuse synthetic identity with
account takeover and true name fraud,” explained Barnhardt. Synthetic identity
fraud is when criminals combine both real and fake information to make an
identity for an account. “I like to use the term Frankenstein to refer to this
type of fraud,” said Barnhardt.

For example, the real information could be a person’s social
security number or address. That piece of real information is then coupled with
fake details, such as a name, phone number, or email address.

Once the Frankenstein—synthetic— identity is established,
the criminal can create an account at a financial institution, use that account
to increase their credit, and then cash out once they’ve reached the desired
credit limit, explained Sloane. Some criminals will cash out immediately, but
waiting longer to develop a higher credit limit is a more lucrative approach.

What makes synthetic identity fraud particularly pernicious
is that it’s so hard to detect. Part of the problem is that traditional fraud
solutions, including ones that rely on generating a probabilistic fraud score,
are built on data that’s “provided within the institution,” noted Barnhardt. Because
of this, “they don’t have anything to compare the application to, nothing that
alerts them that a particular piece of PII,