Tapping into the Self-Employed Market: A Multi-Trillion-Dollar Lending Opportunity Revolutionized by AI
Paul Gigliotti is Head of Growth and Partnerships for Prudent AI
For decades, the mortgage industry has been stuck in an outdated model — built for W-2 borrowers with predictable pay stubs, steady jobs, and the kind of financial stability that made sense in, say, the 1950s. But let’s be real—Ward and June Cleaver aren’t applying for loans anymore. Today’s workforce is different, and so are their financial profiles.
The self-employed and gig economy market isn’t just growing — it’s booming. About 10.1% of the U.S. workforce (16.2 million people) is self-employed, and 36% of the workforce (57 million people) works in the gig economy. And here’s a fun fact: self-employed folks tend to be wealthier, with a median net worth of $380,000 — four times that of traditionally employed families. Yet, the mortgage industry still struggles to serve them.
The Lender’s Missed Opportunity
Despite their strong earning potential, self-employed borrowers face frustrating hurdles when trying to secure a mortgage. Why? Because traditional underwriting models weren’t designed with them in mind. Fluctuating income, complex tax returns, and a lack of conventional employment history make it tough to fit into the neat little boxes lenders prefer. As a result, this massive market remains underserved, and lenders are leaving money on the table.
But here’s the good news: The industry doesn’t need to reinvent the wheel — it just needs a smarter way to evaluate borrowers. And that’s where AI-driven lending solutions come in.
AI: The Game-Changer for Non-QM Lending
Especially in the non-QM market, AI is revolutionizing how lenders assess self-employed borrowers. By automating traditionally manual processes, AI-powered platforms can:
Instantly verify income from bank statements, tax returns, and credit reports—eliminating hours (or days) of human review.
Accurately calculate earnings, even when borrowers have multiple revenue streams or fluctuating income.
Automate eligibility checks, ensuring borrowers are matched with the right loan products without unnecessary delays.
Detect fraud, safeguarding lenders against risky loans.
Lenders Already Winning with AI
For lenders, this means less paperwork, faster approvals, and happier borrowers. For self-employed applicants, it means finally being treated like the financially responsible individuals they are — rather than feeling like they’re trying to explain their job to a confused bank underwriter who’s still stuck on, “Wait… you drive for Uber and sell vintage sneakers online?”
The best lenders aren’t waiting around for change — they’re leading it. Take LendSure Mortgage Group, for example. This San Diego-based lender specializes in non-QM loans and recently modernized its document processing with AI. The result? A 4.5x increase in productivity, loan processing times cut from hours to minutes, and an overall boost in employee (and borrower) happiness. Because let’s face it — no one enjoys manually reviewing stacks of bank statements.
The Future: AI-Powered Pre-Qualification
The real revolution? Moving pre-qualification to the top of the funnel. Imagine a world where self-employed borrowers know their mortgage options upfront—without endless back-and-forth document requests. AI makes this possible by providing real-time insights into a borrower’s financial standing, ensuring only qualified applicants move forward. That’s a win-win for lenders and consumers alike.
The Bottom Line
The self-employed market is a multi-trillion-dollar opportunity, and AI is the key to unlocking it. The lenders who embrace this shift will tap into a massive pool of qualified borrowers while streamlining their operations. The ones who don’t? Well, they’ll be left wondering why their competitors are thriving while they’re still stuck in the past, trying to make 1950s underwriting rules work for a 2025 economy.
It’s time to flip the script. The self-employed deserve better, and AI is how we get there. The real question, will the agencies want to jump on the wagon and expand guides?
(Views expressed in this article do not necessarily reflect policies of the Mortgage Bankers Association, nor do they connote an MBA endorsement of a specific company, product or service. MBA NewsLink welcomes submissions from member firms. Inquiries can be sent to Editor Michael Tucker or Editorial Manager Anneliese Mahoney.)
