In a recent post we looked at the differences in bank underwriting characteristics between those conforming loans held on book compared to those delivered to the GSEs using data pulled from Recursion HMDA Analyzer. We now extend this into another dimension via the addition of LTV.
Below find the difference in share of such deliveries between sold loans and those held on book:
With the release of 2019 HMDA data, we now have two years of loan-level information that contains both demographic and credit characteristics. Demographic information in HMDA includes income, race, and geography down to the census tract level, while credit characteristics include DTI. Our agency loan level databases contain a richer set of information regarding lending characteristics, but limited data on geography and demographics. For institutions looking to benchmark their performance in affordable and minority lending for regulatory purposes, 2019 HMDA, with data on thousands of lenders, is an invaluable tool. If you are interested in finding out more, please reach out.
There are of course policy uses for this data as well. A significant difference between HMDA and the agency pool loan-level data is that HMDA contains data for loans held on book, the so-called “Unsold” category. This allows a comparison of loans that banks originate and keep and those they deliver. We can break this down in any number of ways, but let’s look at it for conforming loans broken down by DTI.
In the table above, we can readily observe that banks tend to keep higher-quality loans (as measured by DTI<=43) compared to those they deliver to the Enterprises. Of course, this is not a complete picture of this issue; there are many other ways to slice the data (credit score, LTV, loan size, geography). Moreover, as there is a correlation between low LTV and desirable loan characteristics for regulatory purposes (minority status, low income), we cannot simply conclude that it’s a matter of keeping the best for themselves.
A second interesting question is: did behavior in this regard change between 2018 and 2019? Below you can find a chart of the change in the distribution between unsold and delivered loans between these two years.
It appears that banks kept more of the loans associated with very low levels of indebtedness (DTI<35) in 2019 compared to 2018, while they distributed a small share of higher-risk loans across the spectrum of DTIs above that level.
Explanations for such behavior are the subject of future research.
2019 HMDA data has been released and is loaded into Recursion’s HMDA Analyzer so clients can perform consistent queries back to 1990. As always, a vast wealth of information is available. Below are several high-level observations.
First, total originations rose by over $700 billion compared to 2018, a 13-year high. The bank share fell for the eighth consecutive year, reaching a record low of 37%. This was down 1 percentage point from 2018, the smallest decline posted for 8 years. Nonetheless, banks have suffered a remarkable 30-point drop in market share since 2008.
With the onset of the Covid-19 crisis, the role of the banking sector has once again risen to the forefront of concern. As noted in an earlier post, the sharp spike in unemployment is certain to lead to a surge in delinquencies. Banks play a significant role in the mortgage pipeline as originator, servicer and investor. In our previous post, we noted that the onset of the crisis has triggered a flood of cash flowing into bank deposits as households and others shed risky assets. As such, banks have more assets to invest, including in the mortgage market.
Banks like mortgages as an investment, spurred by solid fundamentals related to firm labor markets and rising, but not overly stretched home prices. Banks are protected from credit and default risk by owning agency MBS instead of mortgage whole loans and enjoy favorable treatment from the capital rules set by the regulators. According to Federal Reserve data, in Q4 2019 banks held about 25% of the $9.6 trillion agency MBS market. To understand the behavior of banks in this market it is important to probe its underlying structure.
With the onset of the Covid-19 crisis, the role of the banking sector has once again risen to the forefront of concern. As noted in an earlier post the sharp spike in unemployment is certain to lead to a surge in delinquencies. Substantial purchases by the Federal Reserve of Mortgage Backed Securities (MBS) have had a limited impact on rates facing borrowers due in part to uncertainty around the magnitude of the losses and who will bear the costs. Policies regarding forbearance and liquidity provision to mortgage servicers are having an impact on lending standards and the availability of credit.
Banks play a significant role in the mortgage pipeline as originator, servicer and investor. Most of the current focus is on the first two, but the importance of their role as investor is also crucial. According to Home Mortgage Disclosure Act (HMDA) data Recursion uploaded to the cloud, 3.1 million individual single family loans with a balance of $739.4 billion were originated in 2018 by the banks, of which 60.4% were held on their balance sheet. Each loan file in the data set contains many characteristics, including originator information. As banks originated about 43% of all mortgages that year, the implication is that about one quarter or all residential mortgage production was kept by the banks.
On April 7, 2020 our CEO Li Chang was invited to speak as an industry expert at a graduate-level finance class at the Gabelli School of Business at Fordham University. Students were also given free access to the Recursion Analyzers to help them monitor the current mortgage market trend using big data tools.
Students were introduced to the problem of understanding the role of new mortgage fintech lending based on the use of loan-level data on U.S. mortgage applications and originations reported to their regulators according to the Home Mortgage Disclosure Act (HMDA).
In February 2019, BB&T announced its acquisition of SunTrust Bank for about $28 billion in stock. In December that year, the nation’s 6th biggest bank, Truist, was created. There are, of course, a multitude of reasons why financial institutions merge. A classic explanation is that they wish to obtain economies of scale by combining overlapping operations in particular markets. As regional commercial banks with a heavy consumer focus, both these institutions faced earnings pressure from developing headwinds in the mortgage market as interest rates climbed in 2018. (Table 1).