Synthetic Identities – the New Friends and Family Plan?

by Stephen Coggeshall

Stephen Coggeshall

Fake Families Defraud Wireless Carriers with Invented Identities

With identity theft being one of the fastest growing crimes in America,1 an increasing number of merchants are on the lookout for customers using stolen identities. However, these criminals are adapting quickly, turning to a new kind of fraud in which identity is harder to verify because it may never have existed in the first place. These “synthetic” identities often combine real information with invented details.

In a synthetic identity case, a thief might obtain an authentic Social Security number (SSN), but then match it up with a fake name and address, and apply for credit. Once a credit account is created, the fraudster might make small charges and payments on that account to establish a pattern of good credit. Later, when that synthetic identity is used for a bigger purchase that results in a defaulted account, a collection agency might track down the real owner of that Social Security number and demand payment. This can happen months or years after the data is originally stolen.

A recent ID Analytics report shows that the rate of synthetic identity fraud has increased more than 100 percent in just the last five years.

Fake Families in North Carolina

To learn more about how synthetic identities work, ID Analytics researchers reviewed thousands of transactions that were identified as suspicious. One of the patterns they detected  led to the discovery of a synthetic identity operation in Greensboro, North Carolina, that built identities for four made-up families.

By creating a whole family’s worth of fake data, fraudsters can apply for multiple phones at once, signing up for a family plan and requesting a phone for each false identity.

These four families appeared to have credit histories that linked them to two homes in Greensboro that were only three miles apart. The fake people had similar names, and some of them shared the same Social Security number. By creating a light transaction history tied to an address, the fraudsters set up a situation where a fake identity might be accepted because that identity has no bad credit history; most basic credit checks only look for signs of late payments or defaults, rather than verifying identity details.

The Absence of Negative Information

How can someone get a phone using the wrong Social Security number? A standard credit check doesn’t actually verify your SSN, it typically it looks for bad credit history tied to that name and number. If an individual presents a name and SSN that are linked to late payments and delinquent accounts, they may be denied credit. But if the number is invented, or is linked to someone else who has no credit history, it won’t raise any red flags. That is one reason fraudsters often try to get the Social Security numbers of young children: there’s no negative credit record associated with that SSN so far, and any bad information tied to that number likely won’t be discovered for years, until the child is old enough to apply for credit.

In the Greensboro case, ID Analytics detected 196 applications for wireless and other services that were filed by people connected to this ring over a seven-year period. This gradual approach is typical of a patient fraudster: Rather than committing massive thefts and then hiding for a while, these people run an ongoing trickle of fake transactions over a long period of time, creating a steady second income that might provide a few hundred or a few thousand extra dollars per month for quite a while, until the transactions create a detectable pattern.

If the fraudster is careful and steady, they can generate an ongoing income stream. By producing a small number of applications every month, they can generate a little money on the side. It’s when the fraudsters get greedy, or move too quickly that their actions alert suspicion and get caught. Read the Long Con: An Analysis of Synthetic Identities white paper to learn more about synthetic identities.


Dr. Stephen Coggeshall is Chief Analytics and Science Officer at ID Analytics


1. Trundy, Sean. FraudFighter. (14 August 2013)  Identity Theft: The Fastest Growing Crime in America retrieved April 08, 2015 from