Socure, the provider of Artificial Intelligence for digital identity verification, fraud prevention, and sanctions screening has launched Sigma Synthetic Fraud v4.
The product uses advanced machine learning and diverse, third-party and network feedback data “to uncover patterns linked to insidious synthetic identity fraud.”
The Deloitte Center for Financial Services “expects synthetic identity fraud to generate at least $23 billion in losses by 2030.”
Synthetic identity fraud is “a financial crime where a real person’s information is stolen and combined with other falsified personal information to create a fictitious identity, further used for fraudulent purposes.”
After a perpetrator opens an account “using the synthetic identity, they typically build up a positive credit score, open multiple accounts, and often appear to be good customers while going undetected until they decide to cash in, or “bust out” by using up all available credit lines and disappearing.”
Socure accurately detects and “stops synthetic fraud at onboarding before the fraudster can act nefariously in the financial ecosystem. According to a comprehensive study, Socure estimates that synthetics make up 1-3% of open accounts at U.S. financial institutions.”
Sigma Synthetic Fraud v4 draws “from diverse “Proof of Life” data sources including property records, driver’s licenses, and educational data adding a new dimension of accuracy so organizations can confidently verify younger and immigrant demographics with a limited digital footprint.”
Without these types of proof of life data sources, “these segments of the population may otherwise appear to be synthetic fraudsters and be shut out of the financial ecosystem.”
Yigit Yildirim, SVP, Fraud and Risk Products at Socure, said:
“Synthetic fraud cannot be accurately detected with rules-based systems or third-party fraud solutions.”
Synthetic identity fraud occurs “when criminals blend genuine and falsified information to create new, fictitious identities to fraudulently apply for loans, credit, government benefits, or move illicit funds.”
As fraudsters’ AI-supported schemes become “more sophisticated, differentiating malicious synthetic behavior from that of good consumers is more tangled than ever and has made it the fastest-growing form of financial crime in the United States.”
Per incident, synthetic fraud “can cost 10 times more than third-party identity fraud. The “profit” per synthetic fraud opportunity is much higher, such as with benefits fraud, P2P fraud scams, or romance swindling.”
Sigma Synthetic Fraud v4 enhancements include:
- Innovative Email Risk Enhancements: Email tumbling, or when people create “alias” email addresses by adding punctuation marks like periods between letters, often indicates ill intent. Sigma Synthetic Fraud v4 detects tumbling techniques that are commonly used to commit synthetic fraud, so customers can block the bad actors behind them.
- Consortium Data including Feedback: Bringing together a network (Socure Risk Insights Network) of 1,900+ of the world’s largest organizations that span diverse industries and government agencies allows Socure to identify multiple identity elements across the consortium and continually optimize machine learning algorithms to drive the highest accuracy in the market.
