What Is Synthetic Identity Fraud? A Glossary Definition

Synthetic identity fraud is a financial crime where perpetrators combine real and fabricated information to create a new, fictitious identity. Learn how these identities are constructed and why digital footprints are key to detection.

Synthetic identity fraud is a sophisticated form of financial crime where perpetrators combine real and fabricated information to create a new, fictitious identity. Unlike traditional identity theft, which targets an existing person, synthetic fraud involves building a 'Frankenstein' identity to open accounts or secure credit. This type of fraud is often detected by analyzing inconsistencies in digital footprints, such as phone and email history, which help teams review the legitimacy of an application.

Defining Synthetic Identity Fraud

Synthetic identity fraud involves merging real and fake data to create an entirely new identity. Instead of taking over an existing user's account, perpetrators build a fictitious profile from the ground up. This method relies on the creation of a new identity rather than the takeover of an existing one, making it a distinct challenge for risk and compliance teams. By blending genuine data points—such as a stolen Social Security number—with fabricated details, the resulting profile is designed for financial gain.

How Synthetic Identities Are Constructed

The assembly process of these identities relies on a careful mix of stolen identifiers and fabricated details. Perpetrators construct a 'Frankenstein' identity by pairing a legitimate piece of information with a fake name, date of birth, or address. Because the genuine data point may not immediately flag as stolen, the newly built profile often appears legitimate to automated systems. Over time, the fictitious identity is nurtured to build a seemingly normal history, allowing it to bypass basic checks and eventually be used to open accounts or secure credit.

The Role of Digital Footprints in Detection

Because synthetic identities are fabricated, they typically lack the natural, long-term digital history of a real person. Digital footprints, such as the age and activity history of a phone number or email address, serve as key signals for businesses to assess the legitimacy of an identity. When an application is submitted, risk workflows analyze these footprints for inconsistencies. A newly created email address or a phone number with no history of legitimate usage adds a risk signal that supports review.

FAQ

Why is it difficult to detect synthetic identities?

Synthetic identities are difficult to detect because they often use a mix of genuine and fabricated data points that appear legitimate to automated systems. Since there is no specific 'victim' reporting a stolen account, the fraud can go unnoticed until the fictitious identity is used for financial gain.