Synthetic identity fraud continues to cost the U.S. banking system billions of dollars. The Deloitte Center for Financial Services projects synthetic identity fraud to generate at least $23 billion in losses in the U.S. by 2030. According to a study Socure conducted, it’s estimated that synthetics make up 1-3% of open accounts at U.S. financial institutions.
As the problem of synthetic identity fraud grows, it’s worth looking at how these fake identities are manufactured in the first place. Scammers use a mix of stolen personal data and outright fabricated information to apply for various online services like rewards.
Once they’ve created an established fake identity, they can then use it to attack fintechs, banks, auto lenders, and government agencies. Using a synthetic identity, fraudsters can make a large purchase on a credit card or take out loans with no intention of paying it back. This creates huge losses for financial institutions.
How Credit Bureaus Contribute to the Synthetic Identity Problem
Though credit bureaus are often used in the identity verification process, their data ingestion practices may be part of the problem. As we heard in a recent Socure webinar with Meridian Link, credit bureaus have no effective way of verifying the data that’s coming into their system. If they see inquiries and transactions from a synthetic identity, there’s no check to make sure it’s a real account. This lends more credence to synthetic identities and helps criminals make more fake accounts.
Synthetic fraud also creates headaches for consumers when their information, such as a Social Security Number, is used in a fake identity. The file is then “split” and consumers must convince the credit bureau which identity is real. Since the credit bureaus can’t adjudicate this themselves, it creates a large waste of time and effort for American consumers.
We’ve even seen instances of “credit repair” companies preying on individuals with low-credit scores and then using their information in synthetic identities. Once again, the credit bureaus are unable to proactively stop synthetic fraud.
The Issue with Not Diversifying Data Sources
Most digital identity solutions will use credit bureau data of some kind. But surrounding that data with a number of sources is critical to stopping synthetic identities. Any company that solely uses credit bureau data to verify identity is adding to the problem by giving synthetic identities more space to operate. A credit bureau’s data is limited to what it can receive from the financial system; if there are synthetic identities that appear legitimate, there’s not much they can do to find them until it’s too late. Instead, solutions that rely on credit bureau data often employ a policy of blocking many “thin-file” identities, but this unnecessarily shuts out minority, Gen Z, and new-to-country demographics.
The solution is to augment identity verification with “Proof of Life” data sources like education information, property records, and email histories. This year, Socure eliminated over 200,000 synthetic identities through our Sigma Synthetic Fraud Solution and saved our partners more than $3 billion in fraud losses. Rooting out synthetic identities takes significant effort, but Socure uses these data sources and an industry-leading machine learning model to deliver optimal fraud prevention without compromising access.
We use hundreds of data sources and have unparalleled consortium data to optimize machine learning algorithms. By adding our Sigma Synthetic model and Social Security Number verification (eCBSV) capabilities at points throughout the identity verification process, we can determine what identities are synthetic fraud, distinguishing them from “thin-file” identities.
The issues with synthetic identities affect numerous industries beyond financial services, including government agencies, gaming companies, and insurance providers. To fully destroy synthetic identities, it’s time to look to the next generation digital identity verification.
Learn more about fighting synthetic identity fraud in our research report here.
Debra Geister
With more than two decades of experience in the banking compliance and anti-money laundering industries, Geister is a recognized leader in the financial crime detection field. She has worked with many of the largest financial institutions as well as technology and data companies, both global and domestic, to help eliminate and reduce money-laundering, fraud, and related financial risks.