To advance mortgage lending, trust must take backseat to truth
Once upon a time, loans were made on a handshake. That’s not just a platitude; before the Civil War, most Americans were self-employed, there was no federal income tax and banking was decentralized, making it practically impossible to verify a borrower’s employment, income and assets. The earliest iteration of the FICO score was still decades away, and information about borrowers’ past debts was scant and subjective.
When a person needed a loan to buy property or raise a new barn, unless he owned something valuable enough to offer as collateral, the loan was secured by little more than his good word and the threat of foreclosure. In other words, loans were predicated on trust, making them risky and hard to obtain, and homeownership was the exception rather than the rule.
As the American financial system grew more sophisticated, so did our ability to document an individual’s financial history and capacity — but it still wasn’t possible for a creditor to access and review this information in real time.
So mortgage lending morphed from a trust-based system to what could be called a “trust, but verify” model, to coin a favorite Russian proverb of Reagan’s. Lenders would use a borrower’s self-reported ability to pay (ATP) as the starting point for a loan application, but then they’d verify that information over the course of the origination process by calling employers, requesting tax transcripts and collecting bank statements.
The problem with the “trust, but verify” model, which is still used by many lending institutions today, is that it’s time-consuming and expensive. Lenders may engage three separate vendors to verify a borrower’s stated employment, income and assets, creating three sets of actions for borrowers and processors to complete and contributing significantly to the 48 days and $8,243 it takes to produce the average loan.
And since (whether by accident or design) loan applicants don’t always provide an accurate accounting of their ATP, the verification process has the potential to derail an entire deal. The later in the loan process this happens, the higher the sunk production costs that are squandered — costs that are ultimately passed on to borrowers in the form of higher interest rates and lender fees.
It’s time we removed trust from the picture entirely. Instead of asking borrowers about their finances and then initiating a weeks-long paper chase to determine if the information provided is trustworthy, lenders should go straight to the source financial institution or other recordkeeper to learn the truth about a borrower’s employment, income and assets.
Immutable source data eliminates the opportunity for fraud or error, saves processors precious time and speeds up the underwriting process to get loans closed faster. And in the event the borrower does not qualify for a loan, source data lets the lender know immediately, so lenders can coach borrowers down the path to homeownership.
Lenders that aren’t yet taking this approach likely don’t realize the speed and ease with which source ATP data can be retrieved today. Instead of ordering verification services from three different vendors and making borrowers upload a bunch of documents to a portal, lenders can use a single service like FormFree’s AccountChek 3n1 or Passport to digitally verify employment, income and assets in seconds.
With AccountChek, consumers authorize instant access to their data through direct connections with more than 16,000 financial institutions and 45 payroll providers, sparing all parties from the hassle of manual verification and eliminating the need for lenders to stack costs from multiple verification vendors.
It’s important to note that taking trust out of the lending equation does not mean dehumanizing the mortgage experience. On the contrary, having a clear, unbiased understanding of a borrower’s financial DNA allows lenders to extend credit with greater confidence and make more inclusive lending decisions. Take, for example, the new positive rent payment history feature in Fannie Mae’s Desktop Underwriter (DU).
The idea is to unlock more homeownership opportunities for first-time homebuyers by factoring in their history of consistent rent payments. In a perfect world, a lender could just ask a loan applicant, “how much do you pay in rent, and how many of the last 12 months did you pay on time?” and take their responses at face value. Realistically, however, such trust-based systems expose lenders to unnecessary risk and hurt borrowers by introducing personal bias into the credit decisioning process.
The “trust, but verify” approach would be to ask the loan applicant the same questions, then spend two weeks trying to get in touch with the landlord to verify the rental payment history with cancelled checks or some sort of affidavit.
But the added frustration, time and expense — not to mention fraud risk — involved in such a process would no doubt discourage lenders from taking rental payment history into account in the first place.
What lenders need to do, then, is to get to the truth of an applicant’s rental payment history, and that truth resides in the applicant’s asset data.
Using direct-source asset data from authorized report suppliers like FormFree, DU can automatically identify recurring rent payments and take them into consideration when assessing credit eligibility for certain, qualified first-time buyers, potentially expanding homeownership opportunities to historically marginalized borrowers who have been overlooked by the traditional mortgage and baking system due to limited credit history.
This example underscores the central role of source data in advancing mortgage lending to the benefit of borrowers and lenders alike. Now is the time for trust to take a backseat and for lenders to embrace truth as the fairer and smarter foundation on which to grow their businesses.
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