The competition for consumers to secure credit products has never been more intense. Applicants, who have more choices than ever before, place a high value on convenience and the speed of the application process in their decision making. As a result, the necessity for making quick approvals puts credit lending agencies into the unenviable position of having to strike a delicate balance between speed and security. Bad actors are increasingly exploiting the gaps in this system via synthetic identity fraud - a crime that combines the stolen personal information of real people with synthesized fictitious elements in order to generate new credit profiles. In their wake, these criminals leave significant losses to their creditors and ruin credit ratings for the victims of their identity theft.

The Rise of Synthetic Identity Theft 

In his RSA Conference 2022 Top Rated Session, Connecting the Dots: Identifying and Mitigating Synthetic Identity Fraud, Michael Timoney, VP Secure Payments, Federal Reserve Bank of Boston noted that in 2016-2017, synthetic identity fraud was the fastest growing crime in the United States. Last year, there was a staggering 20% increase in reported data breaches that led to the theft of social security numbers, birthdates, and various other elements of personally identifiable information (PII). These unique identifiers are combined with fictitious details to create what is known as a “Frankenstein ID” that is used to apply for credit products such as credit cards and personal loans. While some fraudsters may max out whatever credit they acquire immediately, many more will play the long game. This involves slowly building up their synthesized identity’s credit limits until they reach a significant payoff, at which time they max out all of their credit lines and abandon the identity in a process that has become known as “busting out.” The Deloitte Center for Financial Services estimates that this type of synthetic identity fraud will generate losses in excess of $23 billion dollars by 2030.

In her blog post for RSAC Conference, Synthetic Identity Fraud: What It Is and How to Recognize It, Isla Sibanda explained some of the methods for spotting synthetic identities. One of the most frequently occurring characteristics is the use of personal information belonging to a younger person, recent immigrant, or homeless person that will have what is known as a “thin” credit profile. These individuals are particularly susceptible because they often have no negative credit history, and they are unlikely to be monitoring their accounts for suspicious activity. However, the lack of information and variety in their credit checks should trigger greater scrutiny. According to Sibanda, “The bottom line is that if the credit report looks too ‘clean’ to be accurate, it likely is.”

The Role of Artificial intelligence in Synthetic Identity Fraud Detection 

The problem faced by credit lending agencies is that rigorous and accurate credit checks take time and can end up turning away customers who favor faster approvals with fewer obstacles. One solution is that companies need to adopt artificial intelligence (AI) and machine learning (ML) to vet credit applications more quickly and spot anomalies. However, the greater potential for AI and ML lies in their ability to rapidly analyze large pools of applications and spot emerging trends indicative of synthetic identity fraud that may not be obvious to someone looking at isolated incidents.

Blockchain, which is best known for its connection to cryptocurrency, can also be employed to prevent synthetic identity fraud. Blockchain uses a decentralized form of data storage that utilizes many different copies of data stored in separate nodes. In order for a change to be recorded in the blockchain, all of the nodes must agree. Any changes made to a blockchain are also permanently recorded to provide a clearer picture of activity and greater transparency for an account. These features, combined with the strong encryption inherent in blockchain make it a powerful tool in synthetic identity fraud prevention.

Cutting-Edge Biometric Technologies

Biometric identifiers are another emerging technology that can act as an additional layer of verification for personally identifiable information. These technologies can be used to identify individuals based upon unique physical characteristics such as fingerprints, face shape, and retinal scans. However, behavioral biometric identifiers use patterns such as the manner in which a person scrolls their phone, the way they type, or even the way they walk as more reliable indicators of identity and are more resistant to falsification.  Widespread adoption of behavioral biometric identification will add a significant impediment to criminals looking to commit identity theft.

Regulatory Landscape: Industry Partnerships and Information Sharing 

In order to effectively combat synthetic identity fraud, it is important that financial institutions work as a cohesive whole to share data and best practices. This cooperation should be cross-industry with banks, credit agencies, and e-commerce companies working symbiotically to strengthen the sector and prevent fraudulent parties from synthesizing new identities. With greater transparency between industries, patterns would become more readily obvious, and steps could be taken to combat synthetic identity fraud as it continues to evolve.