A new report from Deloitte shows that synthetic identity fraud is the fastest growing financial crime in the U.S. and could trigger need for more sophisticated biometric security systems.
Synthetic identity fraud involves fraudsters creating fabricated identities by using both fake and real information. They can then use these identities to open bank accounts, access lines of credit, apply for credit accounts and take out loans. Fraudsters can also combine real Social Security numbers with other data to establish a credit record. By making purchases and quickly paying them off, criminals can build a solid credit score to secure bigger loans and credit lines.
By the time fraud detection systems become aware, culprits have moved on and abandoned their synthetic identities.
Developing technology such as artificial intelligence has made it easier for cybercriminals to create these more believable scams. Creating false written or audio messages to bypass various security measures and access banking or account information.
The new data largely consists of novel types and forms of data such as satellite images, social media posts, geolocation data, credit card transactions and mobile application data that are starkly different from the traditionally structured financial data.
To combat these seemingly undetectable attacks, businesses require a multi-layer defense mechanism, with artificial intelligence (AI) and machine learning (ML) playing a crucial role in detecting illicit activities. AI not only enhances fraud detection but also reduces the costs associated with manual checks, human error and operational inefficiencies. It is particularly relevant for businesses with regulatory requirements such as know your customer (KYC), where identity verification is essential.