Home » New Jersey-Based Fraud Ring Charged This Week: The Perfect Case for Social Network Analysis

New Jersey-Based Fraud Ring Charged This Week: The Perfect Case for Social Network Analysis

By Mike Betron, Infoglide VP of Marketing


As reported by MSN Money this week, eighteen members of a fraud ring have just been charged in what may be one of the largest international credit card scams in history. The New Jersey-based fraud ring is reported to have stolen at least $200 million, fooling credit card agencies by creating thousands of fake identities to create accounts.


What They Did


The FBI claims the members of the ring began their activity as early as 2007, and over time, used more than 7,000 fake identities to get more than 25,000 credit cards, using more than 1,800 addresses. Once they obtained credit cards, ring members started out by making small purchases and paying them off quickly to build up good credit scores. The next step was to send false reports to credit agencies to show that the account holders had paid off debts – and soon, their fake account holders had glowing credit ratings and high spending limits. Once the limits were raised, the fraudsters would “bust out,” taking out cash loans or maxing out the cards with no intention of paying them back.


But here’s the catch: The criminals in this case created synthetic identities with fake identity information (social security numbers, names, addresses, phone numbers, etc.). Addresses for the account holders were used multiple times on multiple accounts, and the members created at least 80 fake businesses which accepted credit card payments from the ring members.


This is exactly the kind of situation that would be caught by Social Network Analysis (SNA) software. Unfortunately, the credit card companies in this case didn’t have it.


How SNA Would Have Caught This Activity

This case is a typical example of how members of fraud rings recycle information when creating false identities and accounts. What SNA software does is identify and connect the links between the recycled identities, identifying potential fraud networks for the companies using the software.


In financial institutions (including credit card companies), the social links that SNA software identifies are made up of groups of accounts, customers, and/or employees that share some kind of relationship with each other. Attributes that can be shared and linked include personal identity information (such as names, addresses, phone numbers, etc.), account information, and other factors such as the size of a network or location.


Infoglide’s SNA detects shared relationships and links them together into networks. Once the entities are linked together, advanced analytics are used to assess risk and create a risk score for the institution. In this particular case, links that would have been identified include:


In the case of this fraud ring, SNA would have sent up red flags. SNA would have identified the connections between accounts and as a result, created an alert. For instance, the 80 false businesses that were accepting payments would have shown up in connection with multiple card accounts – and since the 1,800 fake addresses were used to get more than 25,000 cards, those addresses would have shown up in more than one credit card record, too.

Prosecutors note that the accused ring members created a number of fake utility bills and other documents to give credit card companies what appeared to be legitimate addresses. In fact, in one example in the case, the FBI says a member of the ring used the Social Security number of a 6-year-old boy to get a fake utility bill, which was then used to open credit card accounts. If those addresses (or the social security number) were used more than once with the same credit card company, SNA would have detected the fraud as it unfolded as opposed to six years later.


A number of the accused are family members – another likely link that could have identified a connection between accounts. Plus, even if members of the ring made slight changes to identity information such as making a slight number or spelling change in a name (a common practice among fraudsters), SNA would have still beenable to identify a problem. SNA’s algorithms are designed to connect near matches in names, street addresses, social security numbers and telephone numbers, via a process called identity resolution.


As it stands, fourteen defendants appeared before a federal judge on Tuesday, and the FBI continues to investigate the case. Right now, each defendant has been charged with one count of bank fraud and could face lengthy prison time and a $1 million fine if convicted – but that hardly covers the estimated $200 million in losses that the credit card companies (and the rest of us) are left to deal with.


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