Mortgage Fraud Risk on the Rise as Market Pressures Mount

A new report from analytics firm Cotality reveals that mortgage fraud risk is creeping upward, with the company’s National Mortgage Application Fraud Risk Index climbing 7.3% year-over-year in Q1 2025. The index now stands at 133, slightly down from Q4 2024 but still significantly higher than the 124 level recorded a year ago.

One key area of concern is “transaction risk” fraud involving misrepresented or incomplete details about the home purchase itself. This type of risk surged 4.6% over the past year and includes deceptive tactics like inflated home values, fake down payments, and undisclosed relationships between buyers and sellers.

Market Strains Fuel Fraud Potential

Matt Seguin, Senior Principal of Fraud Solutions at Cotality, warns that while mortgage delinquencies remain low for now, the overall economic landscape marked by high interest rates, rising insurance costs, and sluggish home sales has created fertile ground for fraud.

“As affordability continues to erode, we’re seeing more signs of stress in applications,” Seguin said. “That’s often when questionable activity starts to rise people are getting creative just to qualify.”

The report notes that although overall mortgage applications have held steady, purchase loans now make up 67% of volume, and the share of government-backed loans increased to 26%, up from 24% in Q4 2024. These trends suggest more first-time or low-to-moderate income borrowers are entering the market, which could be contributing to rising risk levels.

What’s Driving the Fraud Indicators?

Cotality’s analysis flagged several patterns that signal higher fraud potential:

• Income discrepancies: Borrowers reporting unusually high earnings for their location or tenure.
• Occupancy misrepresentation: Buyers claiming primary residence status on homes they may not occupy.
• Suspicious transactions: Rapid flips or properties being relisted for rent shortly after being purchased.
• Property valuation red flags: Listings priced significantly above neighborhood norms.

One particularly alarming trend: a 50% jump in the number of supposed owner-occupied homes listed for rent within six months potentially signaling occupancy fraud.

Geographically, New York state saw the sharpest regional increase, with Albany and Poughkeepsie posting the highest quarter-over-quarter fraud risk gains.

Fannie Mae Turns to AI to Fight Back

In response to the uptick in suspicious activity, Fannie Mae is stepping up its game. The government-sponsored enterprise has launched a new fraud detection initiative in partnership with Palantir, a tech firm known for its advanced AI capabilities. The new Crime Detection Unit will monitor millions of mortgage-related data points in real time to identify hidden patterns and inconsistencies.

“With this technology, we’re entering a new era of fraud prevention,” said Fannie Mae CEO Priscilla Almodovar. “We’ll be able to catch anomalies before they snowball into major financial risks for the market.”

Regulatory Focus Shifts Toward Real Consumer Harm

Meanwhile, the Consumer Financial Protection Bureau (CFPB) is restructuring its priorities. In a recent memo from its Chief Legal Officer, the agency announced that it would concentrate more resources on direct threats to consumers particularly fraud that causes tangible financial damage.

The memo named mortgage fraud as the agency’s top enforcement priority, followed by data reporting violations, misleading debt collection practices, and unlawful fees. The CFPB also signaled that state regulators will take over some of the lower-priority enforcement work moving forward.

As affordability challenges persist and more borrowers stretch their finances, the housing industry may face a wave of risk unlike any seen since the last major downturn. But with new technology, a more targeted regulatory approach, and heightened vigilance from lenders, the hope is to catch fraud early before it spreads. For direct financing consultations or mortgage options for you visit 👉 Nadlan Capital Group.