Fraudster innovation is a constant. As the defenders of payment transactions thwart one fraud vector, these innovators, playing offense, switch tactics.
Today, the problem of knowing who you are, that you are who you say you are, in the digital domain demands stronger authentication techniques. Many of those rely on the attributes, the data, provided by the user or by the applicants in the case of credit extension.
In turns out that even the data supplied by applicants can be both entirely bogus and sufficient to convince a credit issuer to onboard the applicant and extend credit. This is the problem of synthetic identity.
To explore the synthetic identity challenge, take a listen to this conversation with Naftali Harris, CEO of SentiLink, a company focusing on detecting synthetic identities. Coming from years at Affirm, Naftali and the SentiLink team serve credit issuers struggling with this new fraud vector.
First, let’s define synthetic identity using the Fed’s Synthetic Identity Fraud in the U.S. Payment System Payments Fraud Insight white paper as the source:
“The generally agreed-upon definition of synthetic identity fraud is a crime in which perpetrators combine fictitious and sometimes real information, such as SSNs and names, to create new identities to defraud financial institutions, government agencies or individuals.”
Now we’re looking for phantoms. Uh-oh.
There are terabytes of personally identifiable information for fraudsters to use because of data breaches and our own over-sharing of our personally identifiable information. Knowledge-based authentication based on static data like SSNs, birthdays, and the name of our hometown isn’t hard to break. Nor is this static data generally protected by tokenization or encryption in any way.
The fraudsters know what we know. Uh-oh.
And because the real data presented by the fraudster creating a virtual identity is often that of a child or an elder or even the deceased, well, it’s super hard to detect. That comes from my GLenbrook colleague Yvette Bohanan who has years of risk management experience at Amazon, Google, eBay, BofA and others.
Of course, the fraudster’s goal in making up a new identity is to open a credit line in order to subsequently defraud the issuer, perhaps by carefully using a credit line carefully for years to build up a high credit limit before busting out with a lot of spending and then disappearing to a beach somewhere.
Multiple Types of Synthetic Identities
A startling aspect of some synthetic identity fraud is that it doesn’t take advantage of purloined PII. All of the data used by the credit application is made up out of whole cloth and thin air. The proper format of a social security is well known so why not generate a random one? After all, the federal government doesn’t operate a central SSN repository with realtime validation. A variant approach relies on real and fake data, combining, for example real names with made-up SSNs.
To explore the synthetic identity challenge, take a listen to this conversation with Naftali Harris, CEO of SentiLink, a company focusing on detecting synthetic identities. Coming from years at Affirm, Naftali and the SentiLink team serve credit issuers struggling with this new fraud vector.
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