Synthetic identity theft is the fastest growing financial crime in the United States, and it poses serious risks for financial institutions (FIs) that are looking to streamline their customer onboarding in an effort to scale customer acquisition. Example industries include neo-banks, BNPL providers, and non-bank FIs with credit card products. Criminals can create “synthetic” identities to avoid detection by combining legitimate information, fabricated data, and online activity.

Traditional identity theft is a race against time for the criminals — they try to steal as much as possible before their theft is discovered by FIs or government agencies. Synthetic identity fraud is more commonly stopped by the criminals themselves, disappearing after they have built up enough of a credit profile to “borrow” large amounts of money that will never be repaid.  

Payments systems around the world face an increasing threat from synthetic fraud, and data breaches have released large amounts of personally identifying information that provide a valid basis for fraudulent profiles. These synthetic profiles may not immediately be able to apply for credit, but sustained effort over months or years can establish enough legitimacy to do real damage.  

Synthetic identities have been used to apply for government benefits and launder money, and more sophisticated methods are being used to create them. The most recent efforts have involved fake faces created with artificial intelligence to circumvent biometric verification systems. These risks mean that fraud prevention, credit decisioning, and anti-money-laundering processes will need more effective ways of managing rising compliance costs. 

External Data to Combat Synthetic Fraud

Hundreds of existing data products can enhance the capabilities of FIs, allowing them to verify addresses and perform basic checks to prevent fraud. Data tends to be lower cost than large-scale technology improvements, which means that data-driven solutions can serve as a vital tool to plug holes and facilitate rapid growth. Demyst’s upstream data providers, such as Ekata, Telesign, Neutrino, and Seon, offer fraud detection scores and identity verification flags across name, address, phone, and email. Other Demyst data partners offer synthetic ID alerts through the Demyst Platform that apply advanced matching logic to evaluate suspicious patterns and check external data to identify potentially fraudulent behavior.

Understanding how to leverage external data and dynamic machine learning will be an important advantage for FIs in the battle against fraud. Create your free account on the Demyst platform and learn more about fighting synthetic fraud.