“Like any crime, you need a means — and now with AI and things of that nature, it’s a little easier to do that,” he said. “And then you need really the motivation. And it’s usually one of two things: the borrower wants to get into that dream house, or somebody on the inside, a mortgage insider, wants to make an extra commission. So similar to any crime, you have the contributing factors from that aspect.”
The category showing the largest year-over-year increase in Q2 was undisclosed real estate debt, which rose 2.6%. Cotality’s data shows these alerts are 2.5 times more likely to fire on an investment property than on an owner-occupied property, with investment applications showing 1 in 44 with fraud risk indicators and multi-family at 1 in 27, compared to the overall rate of 1 in 119.
Seguin said that while most fraud risk categories showed year-over-year declines, that should not be read as a signal to relax.
“Don’t become complacent,” he said. “The fraud is still out there, and we’re just reporting that the risk of that category is dropping a little. Having the data to know when a loan is potentially riskier than another and knowing what to pull off the conveyor belt — that’s the old work smarter, not harder kind of thing.”
The AI arms race
Seguin said AI is changing fraud on both sides of the equation. Lenders are deploying it to detect suspicious patterns, and fraudsters are using it to make fabrications harder to catch.
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