A fraudster combines real and create a fake identity, a fabricated identity, or a synthetic persona, that’s difficult for traditional fraud detection systems to identify. This type of fraud, referred to as synthetic identity fraud (SIF), leads to significant financial losses for enterprises.

SIF typically starts with a legitimate Social Security number – stolen from children, homeless individuals or the deceased – and builds a fake identity around it by adding bogus addresses, phone numbers, employment details and social media profiles to legitimize the fake persona. This Frankenstein identity then allows fraudsters to open credit accounts or secure loans with fraudulent intent.

Manipulated Synthetics

Individuals may also use fictitious identities to conceal their past history, and they’re difficult for detection technologies to detect because they don’t fit into patterns of typical fraud behavior. Unlike true synthetics, manipulated synthetics only change some elements like the date of birth and name and often pass validity checks.

Fraudsters’ ability to make high-quality, realistic fake IDs has increased as AI tools become easier to access. They take advantage of something the public gives away freely: photos from billions of social media profiles. These pictures are the building blocks of a fake ID, and scammers look for clear, front-facing selfies that have neutral expressions. They then input the selfie into an AI tool and, within minutes, get back an authentic-looking government ID that can fool Know Your Customer (KYC) systems. This opens the door to fraudsters to commit crimes such as opening multiple credit accounts, obtaining disaster relief programs and securing loans they have no intention of repaying, leading to substantial financial losses for businesses.