ID Analytics Finds Problem of Synthetic Identities is on the Rise

Number of Applications Using New Social Security Numbers Has More Than Doubled since 2011; Synthetic Identities Developed by Fraudsters Are Likely Cause

SAN DIEGO--()--In a new whitepaper released today, ID Analytics LLC, a leader in consumer risk management, explores the rise in synthetic identity fraud including the new ways that fraudsters are creating synthetic identities. Since the randomization of social security numbers (SSNs) in 2011, ID Analytics has seen the number of new SSNs appearing on applications within its ID Network® more than double. This is likely caused by an increase in manufactured synthetic identities. A synthetic identity is a combination of fabricated credentials including SSNs that are combined to create an identity that is not associated with a real person.

“ID Analytics works with some of the country’s leading wireless, credit card and marketplace lenders, helping them to address the issue of synthetic identities, and we are committed to helping them solve the problem of manufactured synthetics, not just manage the symptoms.”

While the problem of synthetic identity fraud isn’t new, the spike in synthetic identities over the past several years is due in part to the Social Security Administration (SSA) deciding to randomize SSN issuance in 2011. Designed to protect the public, the randomization of SSNs also made it more difficult for fraud detection systems to identify fraudulent SSNs. When SSNs were assigned following the same format, institutions could more easily determine if a number was valid. If an SSN in the unissued range was provided by a consumer, it was a strong indicator that the application was a potential risk and should be flagged for additional review.

In the new era of synthetic identities, the randomization of SSNs has made it very difficult for institutions to distinguish between legitimate numbers and fraudulent identities. In the past, fraudsters used to create false identities composed of valid information stolen from several different consumers. Today’s synthetic identity fraudsters are using false identities composed of invalid information with no ties to a consumer, making the fraud less likely to be reported and even more difficult to address.

The demographics of manufactured synthetic identities appear to be very different from those of known third-party fraudsters. Demographics associated with suspected synthetic identities have characteristics similar to new-to-credit consumers. For example, third-party fraudsters are three times more likely to have a credit bureau record than suspected synthetic identities.

The whitepaper examines the three types of synthetic identity fraud, their risks and how institutions can combat them. The most common types include:

  • Traditional Synthetics: One of the earliest forms of synthetic fraud. Fraudsters create these synthetic identities using valid information taken from multiple real consumer victims – most importantly a real, stolen SSN – and combine the information to create a single fake identity. For example, the synthetic might have a real, “shippable” address and a valid SSN, but the SSN, name, and date of birth combination do not match with any one person.
  • Manipulated Synthetics: Synthetic identities based on the applicant’s real identity where only the SSN is changed. These are used by individuals to avoid their past history and gain access to credit. They are true consumers, rather than career criminals, but still pose a risk to lenders.
  • Manufactured Synthetics: A new form of synthetic fraud that remains unsolved. These are synthetic identities composed of invalid information including SSNs which fraudsters choose from the same range of numbers the SSA now uses to randomly issue SSNs, making them impossible to identify as invalid with current techniques. The personally identifiable information (PII) used to create the account does not belong to any known consumers. Fraudsters cultivate the identities, developing credit histories over time—initially appearing as new-to-credit consumers. They can operate for years undetected, before they max out their credit lines and disappear without a trace.

Institutions have been able to successfully address some of the threats of traditional and manipulated synthetics. Reviewing credit development timelines and usage of personal identifying information (PII) through scoring and fraud models can help detect some fraudulent applications, but the problem of manufactured synthetics is more challenging to address.

“The problem of synthetic behavior continues to grow in sophistication, intensity and frequency, and as it does, it has a huge impact on the financial harm it can do and how easily it can be detected,” said Ken Meiser, vice president of Identity Solutions at ID Analytics. “ID Analytics works with some of the country’s leading wireless, credit card and marketplace lenders, helping them to address the issue of synthetic identities, and we are committed to helping them solve the problem of manufactured synthetics, not just manage the symptoms.”

For over a decade, ID Analytics has led the charge in understanding and managing the threat of synthetic identities, and has produced an algorithm that can flag identities that appear to be synthetic. To identify a synthetic identity, the algorithm uses the more than one trillion data elements and 4.2 million confirmed frauds found in ID Analytics’ ID Network to compare PII, look for patterns, and recognize disparities in near real-time to reveal fake identities. The ID Analytics ID Network is one of the nation’s largest, continuously-updated networks of cross-industry consumer behavioral data.

More information on synthetic identities can be found in the ID Analytics white paper, “The Synthetic Epidemic: Understanding Identity Fraud after SSN Randomization.” Additionally, ID Analytics has an educational webinar on the topic available to play on demand at

About ID Analytics LLC

ID Analytics is a leader in consumer risk management with patented analytics, proven expertise, and near real-time insight into consumer behavior. By combining proprietary data from the ID Network®—one of the nation’s largest networks of cross-industry consumer behavioral data—with advanced science, ID Analytics provides in-depth visibility into identity risk and creditworthiness. Every day, many of the largest U.S. companies and critical government agencies rely on ID Analytics to make risk-based decisions that enhance revenue, reduce fraud, drive cost savings, and protect consumers. ID Analytics is a Symantec company. Visit to learn more.

ID Analytics and ID Network are registered trademarks of ID Analytics LLC. All other trademarks and registered trademarks are the property of their respective holders.


MSLGROUP for ID Analytics LLC
Mark McClennan/Jennifer Asaro

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