On March 24, the CFPB released HMDA data for 2021[1], with results obtained from 4,316 reporters, little changed from 4,472 reporters in 2020, but well below the 5,505 respondents reached in 2019[2]. There are yet more companies are expected to report to 2021 HMDA. However, our experience from previous year indicates little change in big picture when reporting is finalized. The drop reported in the number of reporters in 2020 vs 2019 is largely due to a reduction in the number of loans that a bank needed to underwrite, requiring a report to be filed starting in 2020.
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This data is used for market sizing by regulators and market participants, but it also represents a treasure trove of information regarding lender and consumer behavior across a wide variety of economic and market regimes. 2021 was notable for being the second year of the Covid-19 pandemic, which is associated with expansive monetary and fiscal policies and surging house prices.

This report will briefly assess trends across a variety of topics.
 
Market Activity
After surging by 47% in 2020 to 24.8 million from 2019, the number of loan activities reported in 2021 HMDA ticked up by just 2% to 25.2 million, almost 40% below the record high 41.5 million attained in 2003. Similarly, the number of loans originated reported in 2020 jumped by 57% from the prior year to 14.2 million, while in 2021 the figure rose by only 3% to 14.6 million, down by about one-third from the 2003 peak of 21.4 million.

​New York, NY Nov.3rd 2021 --- New York based FinTech company Recursion is teaming up with Fordham University’s Center for Research in Contemporary Finance to work on ESG aspects of mortgage market.
 
The group will utilize Recursion’s cutting edge big data tool, HMDA analyzer, that is based on HMDA data released by CFPB and FFIEC from 1990 to 2020 consisting of more than 600mm mortgage applications, originations, and purchases that is widely used to evaluable affordable housing policies in the US.  Recursion also recently introduced FHFA’s newly released fair lending dataset, such as low-income areas, minority tracts, disaster areas and rural areas to HMDA analyzer.

Recursion is teaming up with Lincoln Institute of Land Policy and Rice University to work on the Underserved Mortgage Markets Coalition project and the Social Policy Analysis Capstone Course (“SOPA”). 

With affordable housing for Low-Moderate Income (LMI) households at the top of the policy agenda, we take a look at loan data for manufactured housing (MH). In a recent report, the CFPB provided a comprehensive survey of this market based on enhancements to the HMDA data first made available in 2018[1]. These include data on
Secured property type:

1. Mortgage: the loan supports a manufactured home and the land on which it sits
2. Personal Property Loan: the loan is secured by the home but not the land

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In their survey, the CFPB looked deeply into the data for 2019. In this note, we update some of their work with 2020 HMDA data. This is important because of the onset of Covid-19 that year. The site-built market performed strongly, but this cannot necessarily be presumed to carry over to MH as Covid is a supply shock, impacting labor markets and supply chains.

Another innovation in this note is that rather than looking at this market by state the way the CFPB does, as a policy guide we look at it bifurcated between rural and nonrural MSAs.

Below finds a chart of the progression of single-family manufactured housing origination volumes for personal loans (securitized by chattel) and mortgages (securitized by real property) from 2018-2020, along with the share of all single-family manufactured housing loans (personal loans plus mortgages) of the total single-family mortgages including those for site-built homes.

In a recent post[1], we looked at the declining FHA share of the purchase mortgage market relative to the GSE’s across a variety of price points. Another way to look at this question is by a geographic breakdown focusing on those census tracts with a Low-Moderate Income (no greater than 80% of area median income) population greater than 51% (we will call these LMI areas)[2].
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To address this issue, we utilize the HMDA dataset, and then apply the LMI information to compute shares of originated purchase loans delivered to FHA vs GSE. This is done on both a loan count and loan balance basis.

Credit provision is one of the great areas of concern addressed by the New Housing Policy. In a previous post[1], we mentioned that we have integrated HUD LMI Neighborhood information with our tools. We can view aggregate credit creation through Cohort Analyzer, and its composition through HMDA Analyzer.
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2020 marked an unprecedented year for mortgage production as the pandemic sparked aggressive moves by the Federal Reserve driving mortgage rates to record lows, coupled with a flight of households away from density towards more sparsely populated areas. Trends in the major programs by loan count can be seen here:

As we accumulate more data at a fine local level, the opportunities to evaluate policies derived from insights into lender, borrower and supervisor behavior grow massively. Our recent post looking at the potential impact of FHFA’s new rate mod policy[1] is our most recent example of the application of digital tools in the policy space, but as noted previously[2], the new policy framework is designed to focus on wealth creation and housing sustainability at the local level.

To look at this issue, we need to have data at hand that tells us which local areas have a preponderance of low-income borrowers on which we can overlay the HMDA data set, which reports census tract level indicators related to the policy issue at hand.

It turns out that the income data can be found in the American Community Survey (ACS)[3]. A key facet of this survey is information regarding the share of every census tract where low and moderate income (LMI) people comprise less than or equal to 51% of the total population. This data is available through the HUD Exchange[4].

With that, we now have a robust tool for analysis. An immediate challenge in this regard is to come up with specific queries out of the myriad of possibilities that demonstrate their power. Below finds a chart that provides a big-picture view of lender behavior in LMI neighborhoods broken down between banks and nonbanks[5]. Specifically, we look at the trend in purchases from third-party originators of both FHA and conventional loans:

Last August we reported that we had downloaded 2019 HMDA and detailed queries were accessible to our clients via HMDA Analyzer[1]. Recently, the CFPB provided a preliminary release of 2020 data, with information from smaller reporters coming a bit later in the year. Nevertheless, the new data is available on HMDA Analyzer and several insights can already be gained.
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​    1. Total Origination loan count grew to its highest level since the runup to the Global Financial Crisis,          driven by a surge in refinancings:

    2. Nonbanks Rule – Covid 19 accelerated the long-term trend increase in nonbank lending share:

    3. The held on book share collapsed, as banks preferred to hold mortgage risk in the form of MBS to            avoid the potential for credit losses:

​Much more can be found through with just a few clicks of the button.