Fighting fire with fire

Zest AI
August 15, 2024

Why credit unions need to aggressively combat fraud now more than ever

Has #fraud become trendy?

Earlier this year, Fast Company reported on a series of TikToks that went viral from an account called Business Women University advising users on how to max out a credit card to purchase an Airbnb. Taking a quick look through the hashtags #wealth, #financialfreedom, #money, #taxes, etc., you’ll find a slew of misleading financial advice, or worse, how-to guides on committing fraud under the guise of “gaining financial freedom.” When people follow this bad financial advice, it can lead them down a dangerous path of racking up debt, letting loans default, and ignoring collections.

It’s no wonder that people are searching for a way out: credit card debt is at an all-time highdelinquencies are on the rise, and consumers are feeling the economic stress. Couple this with endless, misleading financial “advice” content on the internet and increasingly available AI tools, and we find ourselves with an unfortunate end result — fraud rises too.

Fraud empties credit unions’ pockets 

In 2023, Alloy reported that 79 percent of credit unions and community banks lost more than $500,000 due to fraud — higher than any other type of financial institution. Credit unions’ member and community-first structure lends itself to first-party, identify fraud, and social engineering scams.

In addition to economic stress weighing on consumers, credit unions’ current fraud prevention tactics are lacking. Heavy reliance on manual verification (such as reviewing paystubs, filling out paperwork, showing ID, or asking for references) is no longer effective, simply because these documents and references are too easy to fake. Generative AI tools are growing in popularity, and as they become more widespread, so will their sophistication.

The different types of fraud

Application fraud comes in many flavors:

  • First-party: A borrower takes out a loan with no intention to pay the loan back.
  • Third-party: One person’s identity has been stolen, or a new identity is synthetically created and used to apply for a loan. American consumers lost $43 billion to third-party fraud scams in 2023.
  • Misreported income: An applicant or auto dealer enters an incorrect income amount on the application.

Using AI to fight AI

It’s critical for credit unions to seek out tools that can implement the latest technology to combat AI-generated fraud at the same breakneck pace that fraud is evolving. Machine learning algorithms can detect thousands of data points that the human eye may not be able to catch, from quirks on a falsified document to subtle income verification mismatches. It can even detect anomalies in behavior to capture early delinquency — capturing someone who might, say, max out their credit card and never pay it back. It may seem like fighting fire with fire, but the only way to truly combat fraud, especially AI-generated fraud is with better, faster, stronger, AI technology.

When looking at fraud prevention solutions, ask:

  1. What types of fraud are being detected, and how will it address the evolving landscape?
  2. How much visibility and confidence are you able to get into the fraud being detected?
  3. How much does the solution affect your automation efforts?
  4. How will it affect your customer experience? Will it have a positive impact (no need to provide extra documentation) or a negative one (longer wait times)?

It’s time to take action

Fraud is vastly underreported, meaning that your credit union might be funding even more fraud than you’re aware of. Credit unions need a powerful solution that can efficiently flag fraud indicators accurately, doesn’t generate huge false positive rates, and truly provides insight into where and how to stop fraud. Luckily, as AI tools become more widespread for fraudsters, they also become more accessible for financial institutions. It’s time for credit unions to take their technological power back and face fraud head-on.

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