FinTech Disrupting The Mortgage Industry

photo by www.cafecredit.com

photo by www.cafecredit.com

Researchers at the NY Fed have posted The Role of Technology in Mortgage Lending. There is no doubt that tech can disrupt the mortgage lending business much as it has done with others. The abstract reads,

Technology-based (“FinTech”) lenders increased their market share of U.S. mortgage lending from 2 percent to 8 percent from 2010 to 2016. Using market-wide, loan-level data on U.S. mortgage applications and originations, we show that FinTech lenders process mortgage applications about 20 percent faster than other lenders, even when controlling for detailed loan, borrower, and geographic observables. Faster processing does not come at the cost of higher defaults. FinTech lenders adjust supply more elastically than other lenders in response to exogenous mortgage demand shocks, thereby alleviating capacity constraints associated with traditional mortgage lending. In areas with more FinTech lending, borrowers refinance more, especially when it is in their interest to do so. We find no evidence that FinTech lenders target marginal borrowers. Our results suggest that technological innovation has improved the efficiency of financial intermediation in the U.S. mortgage market.

The report documents the significant extent to which FinTech firms have already disrupted the primary mortgage market. They also predict a whole lot more disruption coming down the pike:

Going forward, we expect that other lenders will seek to replicate the “FinTech model” characterized by electronic application processes with centralized, semi-automated underwriting operations. However, it is unclear whether traditional lenders or small institutions will all be able to adopt these practices as these innovations require significant reorganization and sizable investments. The end result could be a more concentrated mortgage market dominated by those firms that can afford to innovate. From a consumer perspective, we believe our results shed light on how mortgage credit supply is likely to evolve in the future. Specifically, 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. Our findings also imply that technological diffusion may reduce inefficiencies in refinancing decisions, with significant benefits to U.S. households.

Our results have to be considered in the prevailing institutional context of the U.S. mortgage market. Specifically, at the time of our study FinTech lenders are non-banks that securitize their mortgages and do not take deposits. It remains to be seen whether we find the same benefits of FinTech lending as the model spreads to deposit-taking banks and their borrowers. Changes in banking regulation or the housing finance system may affect FinTech lenders going forward. Also, the benefits we document stem from innovations that rely on hard information; as these innovations spread, they may affect access to credit for those borrowers with applications that require soft information or borrowers that require direct communication with a loan officer. (37-38)

I think that the author’s predictions are right on target.

 

Borrowing Constraints and The Homeownership Rate

photo by Victor

Arthur Acolin, Jess Bricker, Paul Calem and Susan Wachter have posted a short paper on Borrowing Constraints and Homeownership to SSRN. The abstract reads,

This paper identifies the impact of borrowing constraints on home ownership in the U.S. in the aftermath of the 2008 financial crisis. The existence of credit rationing in the U.S. mortgage market means that some households for whom it would be optimal to choose to be homeowners may not be able to do so. Borrowers with certain wealth, income and credit characteristics are unable to obtain a loan even if they are willing to pay a higher cost of credit (Linneman and Wachter 1989). The Stiglitz and Weiss (1981) canonical model sets up the rationale for this credit rationing. Using data from the 2001, 2004-2007 and 2010-2013 Surveys of Consumer Finance (SCF), this paper measures the impact of changes in the income, wealth and credit constraints on the probability of home ownership. Credit supply eased and then became considerably more restricted in the wake of the Great Recession. The loosening of borrowing constraints was accompanied by an increase in home ownership from the late 1990s until the start of the housing crisis. In this paper we estimate the role the tightening of credit has had on the probability of individual households to become homeowners and the decline in the aggregate home ownership rate following the crisis. The home ownership rate in 2010-2013 is predicted to be 5.2 percentage points lower than it would be if the constraints were at the 2004-2007 level and 2.3 percentage points lower than if the constraints were set at the 2001 level.

This paper builds on some of the other work of the authors (see here for instance) on the homeownership rate. The paper makes a valuable contribution by estimating the impact of credit rationing on the homeownership rate. To the extent we can identify an optimal amount of credit supply, it should help us to determine a target homeownership rate to guide policymakers.

Friday’s Government Reports Round-Up

Wednesday’s Academic Roundup