ID:A Labs White Papers
This white paper explores the definition of synthetic fraudsters and the algorithm used to identify them, the estimated size of the synthetic fraud issue, and possible solutions for reducing synthetic fraud.
According to a new study by ID Analytics’ ID:A Labs there are more than 10,000 identity fraud rings in the U.S. This study is the first to systematically find many thousands of identity fraud rings, which was accomplished by developing an algorithm capable of automating the process of examining the interconnections between identity fraudsters to uncover rings of organized activity.
Minors’ identities are particularly appealing targets for fraudsters because their personal data is untainted, legitimate, less likely to be monitored for misuse, and few tools are available to protect children against attack. To provide greater insight into the scope of child identity fraud, ID Analytics conducted a study of more than 172,523 children enrolled in ID Analytics’ Consumer Notification Service at some point during the 12-month period.
Requesting a change of address on an account is a common tactic used by fraudsters to gain access to an account’s assets. Once the fraudulent address is in the system, the fraudster can then place orders for replacement credit cards, checks, passwords/PINs or new cell phones which will be mailed to the fraudulent address. Frauds linked to address changes are costing companies millions of dollars each year.
Direct marketing and many other consumer analytics frequently rely on name/dates-of-birth (DOB) combinations for personal identification. We will demonstrate that empirically, names/DOB combinations are woefully inadequate as a precise tool for personal identifiers; this is true for common, especially for cyclical and trendy names appended by a DOB.
Despite the absence of apparent associations between individuals seeking credit, we find that the credit application process reveals a socio-economical network of credit customers. In the complex heterogeneous data captured by ID Analytics, we observe networks of people connected by their names, dates of birth, SSNs, phones and addresses.