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With a housing market that’s the most competitive it’s been in years, home buyers need every advantage they can get. And for buyers who will rely on a mortgage to finance a home purchase, an online lender could provide them with that advantage.
Technology-based (or fintech) lenders have quickly expanded their market share since the Great Recession, and along the way they have developed efficiencies that give them a major advantage over more traditional lenders, according to a new working paper from researchers at the Federal Reserve Bank of New York and New York University, distributed Monday by the National Bureau of Economic Research.
In short, these lenders are faster in processing loans, more adept at handling fluctuations in demand and tend to see fewer loans go into default.
The study classified a company as a “fintech” lender if a borrower could get a loan pre-approval based on a hard credit check online without interacting with a loan officer.
In 2010, these lenders originated just $34 billion in mortgages, representing 2% of the market. By December 2016, their market share had grown to 8%, or $161 billion in originations. Much of that growth came through Federal Housing Administration loans, which are generally given to borrowers with lower incomes who cannot afford large down payments, and refinances.
Here’s what the study found:
- Fintech lenders reduced the time it takes to process a loan by roughly 10 days as compared with the average processing time for mortgages. For refinances, they’re nearly 15 days faster than more traditional lenders.
- In instances where a lender is seeing greater demand for loans, tech-based lenders are better at handling the larger inflow of applications. Double the application volume raised the loan processing time only by 7.5 days for fintech lenders, versus 13.5 days for traditional ones. Moreover, the researchers found that tech-based lenders lower their denial rates when there’s a higher volume of applications.
- In parts of the country where fintech lenders have a greater presence, existing borrowers are more likely to refinance. But the efficiencies created through their platforms make it more likely that borrowers will see an optimal result from a refinancing, including getting the market interest rate.
- The default rate on Federal Housing Administration loans originated by fintech lenders is roughly 25% lower than traditional ones.
How online lenders could improve outcomes for mortgage applicants in the future
Fintech lenders are far from the only ones who are investing in online platforms and working to digitize the mortgage process. Consequently, the researchers predicted that fintech lenders’ success will predicate more advancement in this space.
“Technology will allow the origination process to be faster and to more easily accommodate changes in interest rates, leading to greater transmission of monetary policy to households via the mortgage market,” the researchers wrote. “Our findings also imply that technological diffusion may reduce inefficiencies in refinancing decisions, with significant benefits to U.S. households.”
But the extent to which consumers benefit from technological change in the mortgage industry might depend on the regulations lenders are subject to.
This is especially true for minority mortgage applicants. A recent report from the Center for Investigative Reporting found that lenders continue to deny black and Hispanic mortgage applicants at significantly higher rates than white applicants across the country — a situation that could worsen if financial regulations are loosened.
However, a recent study from researchers at the University of California, Berkeley, indicated that while fintech lenders still are more likely to deny loans to black and Hispanic consumers, they also tend to have lower denial rates relative to traditional lenders.
The researchers attributed this in large part to the underwriting standards imposed by Freddie Mac FMCC, +1.41% and Fannie Mae FNMA, +0.65% that guide the algorithms used to automate the mortgage process. And without these standards, the researchers reasoned that poorly constructed automated processes could “produce illegitimate statistical discrimination.”
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