“Un-Retiring”: A New Employment Fraud Trend Raising Red Flags

Something unusual is happening in the lending world. We’re seeing a growing number of loan applicants claiming to be employed after previously stating they were retired. While you might think this reflects older Americans returning to work in a tough economy, our data reveals a more concerning pattern.

What’s Happening?

People who had previously claimed to be “retired” on a prior loan application are claiming to be actively employed on a current loan application less than 90 days later. While this might sound like a natural response to economic pressures on an aging population … there’s a catch.

This isn’t just happening with retirement-age borrowers trying to supplement their income. We’re seeing this pattern across all age groups, including applicants as young as 18 years old.

Why is this important? Because when we see this specific employment status switch, these loans are 2.5 times more likely to go into early payment default. That’s a significant red flag for lenders.

The Numbers Tell the Story

Looking at early payment default rates when we see this “un-retirement” pattern:

• Ages 18-24: 6.25%
• Ages 25-34: 11.7%
• Ages 35-44: 12.2%
• Ages 45-54: 10.7%
• Ages 55-64: 8.1%
• Ages 65+: 9.8%

These numbers reveal something striking: the highest default rates aren’t coming from older borrowers who might legitimately be returning to work. Instead, the peak risk appears in the 35-44 age group, suggesting this employment status switch isn’t about supplementing retirement income – it’s about manipulating stated income for loan approval.

Why Traditional Tools Miss This

Web-based tools to generate fake paystubs in a matter of minutes are easy to find.  The emergence of generative AI has made it even easier as fraudsters can use chatbots to provide employment “verification” services to support these fake paystubs.  Standard risk assessment tools and credit checks weren’t designed to catch this type of misrepresentation. They typically focus on credit history and current application data, missing these important shifts in stated employment status across applications over time.

Protecting Your Institution with Better Tools

Here’s how to guard against this emerging fraud trend:

1. Leverage Consortium Data
   • Discover how an applicant’s employment claims change across applications
   • Identify patterns of employment status switching that may indicate fraud

2. Strengthen Your Verification Process
   • Move beyond stated information on applications
   • Validate current employment status through reliable sources
   • Pay special attention to recent employment status changes
   • Look for logical inconsistencies in employment history

3. Implement Point Predictive’s IEValidate™
   • Get real-time validation of employment status
   • Verify income and occupation details instantly
   • Compare current employment claims against historical data
   • Make confident lending decisions based on validated information
   • Spot employment status inconsistencies before they become loans that might default

Looking Forward

This trend began emerging in early 2022, coinciding with significant economic shifts and the ongoing wave of Baby Boomer retirements. However, the presence of this pattern across all age groups, including young adults, suggests something more concerning than legitimate returns to the workforce.

The solution? Tools like IEValidate can help you instantly identify and verify employment, income, and occupation for a consumer. Instead of relying on stated information, you can access validated employment and income data in real-time. This helps you spot potential misrepresentation before it impacts your portfolio.

Remember: When an applicant claims to have gone from retired to employed, it’s worth a closer look – regardless of their age. The key is having reliable tools to effectively verify employment status and income sources.

Want to protect your institution from employment misrepresentation? Learn how IEValidate can help you validate employment claims and spot potential fraud.

Learn how IEValidate can help you validate employment claims and spot potential fraud.

Author: Justin Davis