Synthetic Identity Fraud is Attacking Credit Unions

Synthetic identity fraud involves manufacturing an identity using a mix of both real and fake information in order to obtain fraudulent loans and accounts. Over the last couple of years, synthetic identity fraud has become a risk for US credit unions. Exposure to this risk could amount to billions of dollars. And credit unions are losing perhaps hundreds of millions of dollars per year to this type of fraud.

At Point Predictive, we don’t see the risk of synthetic identity fraud decreasing anytime soon. But technology innovations are reaching credit unions and giving them a powerful tool in the fight against this challenging type of fraud.

One new tool is offered by the Social Security Administrations. It’s called “Electronic Consent-Based Social Security Number Verification“, or eCBSV. It’s off to a great start. However, the rollout has been slow and its effectiveness against synthetic identity fraud is limited for two reasons.

• Synthetic identity fraud doesn’t affect every lender equally. Fraudsters target the most vulnerable lenders. And they prefer schemes that require the least amount of effort.
• Synthetic identities look legitimate. This makes fraud detection more difficult.

Why are Credit Unions Vulnerable to Synthetic ID Fraud?

It is common to believe that credit unions have an advantage in the fight against loan fraud because they are member-based organizations. So why are credit unions vulnerable?

Trust is More Difficult to Assess

A credit union is a cooperative financial institution that is owned and controlled by its members. Accordingly, it operate on the principle of “people helping people”. As a not-for-profit business, credit unions can offer lower interest rates. They can also focus on serving the underserved.

These attributes allow credit unions to lend to people within their communities who may not be able to bank elsewhere. This increases risk of synthetic identity fraud. For credit unions, lending decisions aren’t based solely on ability to repay. These institutions also consider the willingness to repay. We call this assessment “currency and character”.

The service that credit unions offer to communities is impactful. But in today’s lending landscape, it puts underwriting at risk. It hasn’t always been this way, though. For example, when credit unions were first formed, it was easier to manage risk for two major reasons.

• Stricter Membership Requirements. The field of membership is the means by which a person can become a member. In the past, membership could be dependent on living within a certain community, working for a certain employer, or being a part of a particular organization. However, in pursuit of growth, credit unions have widened these fields of membership.
• Pre-Digital Revolution. Before the era of widespread online banking, credit unions got to know their members and truly understand their banking needs through in-person interactions. It was far easier to determine who was trustworthy. The assessment of “currency and character” was tangible.

Today, broader fields of membership digital interactions increase fraud risk for credit unions.

Automated Underwriting Practices Have Emerged

It should surprise no one that the almighty credit score has been a key element of a lending decision.

Over time, the banking industry begun to use innovative new data sources to complement credit scoring technology.

Unfortunately, credit unions have been late to the party. Only recently are they adapting their underwriting practices. To fully mature, credit unions must unlearn old habits while adopting new ones.

Borrowers with a good story should not be treated as an exception to the rule. And decisions that put the credit union at risk while benefitting the member should be more tightly controlled.

Synthetics look perfect to a loan analyst. They look like a safe bet. Loan review analysts are often fooled by synthetic identities. They often appear as a prime borrower, but those identities are typically in the middle of accumulating open credit for a future “bust out”. Therefore, credit unions who rely too heavily on credit scores will almost certainly approve loans for some synthetic identities.

Only cross-industry datasets provide the clues that connect the dots between synthetic identities and the default losses that identify the application as risky.

Technology Investments Have Not Kept Up with Synthetic Identity Fraud

We all know that technology can help fight fraud. But technology also enables fraud. Perpetrators of fraud are successfully using technology to forge documentation. Anyone who has internet access can find ways to produce fake paystubs or falsely verify employment.

But human fraud prevention analysts have a limit. They are constrained by time and mental capacity. The machines can work faster, more consistently, and are getting better at learning and assessing risk.

Of course, there are still many things that a human fraud analyst can do that a machine cannot. Fraud is a people-perpetrated crime; people know people best.

Fraudsters know all of this already. That could be a reason why credit unions are such good targets for them. Many credit unions have stretched humans and not enough machines to fight back against fraud.

Naturally, most credit unions strive to provide superior service. Being aggressive managers of risk adds friction to a customer interaction.

How does a credit union keep its game elevated while protecting against unforeseen losses that can come from anywhere? The answer: fresh new approaches to data collaboration and some killer artificial intelligence.

Why You Need to Work with Point Predictive on Synthetic Identity

Powered by data from over 94 million applications, Point Predictive’s unique approach to detecting synthetic identity fraud delivers a high confidence of identifying true frauds while removing unnecessary alerts that may drive increased friction in the member onboarding process.

Synthetic ID Alert leverages Point Predictive’s patented Artificial + Natural Intelligence™ technology to continuously assess the risk of default and loss by coming through these millions of applications. So, Synthetic ID Alert will instantly let a lender know that the risk of synthetic identity fraud is present. Coupled with the expertise of seasoned fraud fighters, any institution’s fraud operation can find more fraud, reduce false positives, and accelerate throughput of a loan origination operation.

Fraudsters may be targeting credit unions. But Point Predictive is changing that. Synthetic ID Alert gives credit unions the opportunity to maintain high levels of service while protecting the institution from these changing risks.