Banks need to shift their mindset to fight synthetic ID fraud
Economic growth is making credit more widely available for consumers to purchase cars and homes, as well as to invest in their future. It is also providing fraudsters a broader opportunity to implement innovative schemes, such as synthetic identity fraud.
With an eye toward acquiring young borrowers with limited credit histories, yet potential for significant lifetime value to the lender, banks and other financial institutions may use more relaxed verification processes or rely on outdated policies and checks. The thought process is that, with enough “good” borrowers, lenders could offset potential fraud losses. But fraudsters are also aware of the lax standards and have executed thousands of synthetic identity fraud attacks with potentially millions of synthetic identities in play, and billions of dollars at risk.
Given the time it takes for fraudsters to cultivate synthetic identities – approximately 12-18 months – we can expect to see a surge in synthetic identity attacks as fraudsters work fast to take advantage of current conditions. One factor is the prospect of an economic downturn – recessionary periods tend to produce tighter credit and more stringent verification standards.
In addition, the pilot program for the Social Security Administration’s new electronic Consent Based Social Security Number Verification (eCBSV) service is on the horizon. This program will hinder fraudsters’ ability to monetize their synthetic identity inventory.
According to Experian’s 2020 Global Identity & Fraud Report, 57 percent of businesses are seeing higher losses associated with account opening and account takeover fraud.
Which lenders need to be most aware?
The lenders that tend to be the most at risk are large banks and other institutions focused on emerging consumers – the latter group includes fintech firms. Most of them tend to covet young borrowers with the hopes of maximizing the lifetime value of these consumers. The earlier large banks can convert prospective borrowers into customers, the more likely these lenders can establish lifetime loyalty. The appeal is mutual: Large banks have numerous options attractive to these young borrowers, including credit cards, rewards programs, auto loans and more.
The product diversity that attracts young borrowers also attracts fraudsters, who have more options to illegally expand the borrowers’ available credit and thus more opportunity to steal significant amounts of money.
To counteract the synthetic identity threat, banks tend to tighten credit criteria or explore traditional identity-verification solutions. However, stricter credit standards are not the most effective solution – synthetic identities are engineered to outmaneuver credit-based controls. Experian research shows that lenders that tighten credit criteria continue to book the same percentage of potentially synthetic identities, and that the losses on these accounts continue to increase. Additionally, the more stringent criteria negatively impact the number of “good” borrowers,” which can diminish a bank’s bottom line.
Advanced data and analytics are the answer
Rather than rely solely on traditional credit-based identity controls, banks and other lending institutions need to leverage advanced data, analytics and technology. This includes machine learning, device intelligence and digital tokenization. Experian’s Global Identity & Fraud Report shows that only slightly more than half of businesses consider advanced analytics, such as machine learning, to be important for identifying customers.
An analysis of identity characteristics that extend beyond credit and basic demographic information can help accurately detect synthetic identity fraud. For example, a long-term view of an identity’s evolution, and the manner in which the identity connects to a network of other consumers through shared accounts, can help lenders assess historical credit behavior and relationships. If the identity is connected to individuals that exhibit fraudulent characteristics or includes a Social Security number that has been associated with dozens of addresses, lenders should investigate the identity further. A lender that requests additional documentation typically deters further fraudulent behavior.
While we can expect to see a surge in synthetic identity fraud attacks, banks and other lending institutions can protect themselves by shifting their mindset. Minimizing the overreliance on traditional, credit-based authentication measures by leveraging advanced data and analytics can better position them to detect fraud attacks before reaching the point of significant pain. It also opens the door for banks to continue to acquire “good” borrowers and provide a positive customer experience.
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