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The idea for Copperlane started with a phone call to Athan Zhang’s mother.
She had spent her career in the secondary mortgage market, on the risk side, and Zhang, then a computer science student at Princeton, was struck by something she described: by the time a loan reaches investors, it has been flattened into a spreadsheet of numbers, and a lot gets lost along the way. To Zhang, that sounded less like a paperwork problem than a data problem.
That observation is now a company. This month, Copperlane announced $4.1 million in seed funding led by TQ Ventures, with participation from Y Combinator, US News Digital Ventures, Eight Capital and angel investors from Mercor and others. Zhang, 21, is chief executive; his co-founder, Brianna Lin, also 21, is chief operating officer. The two met through Y Combinator and bonded over a shared inheritance: both grew up in what they call “mortgage families,” with parents whose careers spanned Freddie Mac, Fannie Mae and the Federal Housing Finance Agency.
A business built for a brutal stretch in lending
Their timing is pointed. Originating a mortgage has become punishingly expensive, and, for a long stretch, unprofitable. Independent mortgage banks lost an average of $1,056 on every loan they originated in 2023, their worst showing in years, according to the Mortgage Bankers Association. The industry clawed back to a thin average profit of $443 per loan in 2024, the MBA reported, but the rebound was uneven: smaller lenders stayed in the red for a third consecutive year, and the fourth quarter slipped back into a loss. Production costs alone ran north of $11,000 per loan.
Copperlane’s wager is that a meaningful share of that cost is waste: hours spent chasing documents, re-reading bank statements and clarifying the same discrepancies on loan after loan, across the millions of mortgages Americans take out every year.
What ‘Penny’ actually does
At the center of the platform is Penny, which the company describes as an AI mortgage loan officer. Rather than the rigid, rule-based software lenders are accustomed to, Copperlane says Penny uses a general-purpose AI model to read a borrower’s file the way a junior loan officer might. At the application stage, the company says, it can scan bank statements, flag a large deposit that doesn’t square with a borrower’s income, ask the borrower about it and draft a compliant letter of explanation. This all happens before the file lands on an underwriter’s desk.
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