Over the past couple of years, we’ve witnessed some volatility with regards to FHFA’s approach to mortgages on second homes and investor properties (sometimes referred to non-owner occupied housing or NOO). In January 2021, FHFA announced that caps would be imposed to limit the acquisitions of loans backed by second homes and investment properties to 7% of the total on a rolling 52-week basis. These caps were then suspended in September of that year.
Then, on January 5, 2022, FHFA announced targeted fee hikes on second home mortgages and jumbo mortgages on loans delivered to Fannie Mae and Freddie Mac, to be implemented on April 1, 2022. These up-front fees are tiered by LTV and for second home mortgages range from 1.125% and 3.875% and for high balance loans range from 0.25% and 0.75%. Borrowers in special affordability programs are excluded from these fees, as are first-time homebuyers in high-cost areas whose incomes fall below 100% of the area median income.
To see what if any impact these fee hikes have had on the targeted market segments, we look first at the share of conventional loans broken into second homes, investment homes and others, as measured by loan count.
We’ve noticed that the prevalence of appraisal waivers for purchase mortgages within the eligible population peaked in Q4 last year, and recently has gone into steep decline. Our working thesis as to what is behind this trend is that lenders are getting concerned about the rapid pace of home price increases and want the additional security associated with an on-site appraisal. If this is indeed the case, we should see a greater decline in this share for larger mortgages than for smaller ones. So we break up the universe by GSE, and by loans above and below 2021’s conforming loan limit of $548,250:
As mortgage rates have moved up recently, we have observed some changing trends in underwriting characteristics associated with GSE new issuance. According to Freddie Mac, the US weekly average 30-year fixed mortgage rate stood at 3.89% as of Feb 24, 2022, which is about a 1.3% increase since the record low level of 2.65% was reached on Jan 7, 2021.
As mortgage rates decline, originators become capacity constrained and allocate credit to the highest-quality borrowers. Similarly, to keep lending pipelines full, originators are likely to loosen up their underwriting standards when rates rise. After declining in recent years when interest rates were low, GSE new issuance purchase loans with DTI over 45 started to increase again in the second half of 2021, especially for Fannie Mae, as mortgage rates began to rise. Nonbanks have historically been more active in lending to higher DTI borrowers, but recently the gap between banks and nonbanks has narrowed.
We have observed similar trends in credit scores. After the decline in the shares of low credit score borrowers in 2019 and 2020, sellers have recently been delivering an increasing share of loans with credit score less than 680 to the GSEs.
We observe these trends by tracking our monthly data reports. If you are interested in the outlook for mortgage market developments, reach out to email@example.com and subscribe to Recursion Reports!
Mortgage market analysis in 2022 is setting up to be very much focused on the impact of expiring forbearance programs. In this post, we look at the FHA program from this perspective. With the onset of the pandemic, FHA began to apply “Partial Claim”s, a seldom-used loss mitigation method to help its mortgage borrowers cope with financial difficulties stemming from the pandemic. A Partial Claim is a no-interest junior claim consisting of missed P&I payments secured by the property that comes due when the first lien is extinguished. Ginnie Mae created a new pool type, the RG pool, mainly to take delivery of the loans received via a partial claim, after they successfully made six6 consecutive payments. Another FHA innovation is the availability of an automatic modification that allows borrowers exiting forbearance to have access to a program that reduces monthly payments by up to 25% without impacting their credit.
The result has been a sharp change in the composition of FHA loans delivered to Ginnie Mae program over the past year.
This changing composition will likely have a measurable impact on pool performance. In this regard, it’s interesting to look at the credit scores of borrowers across loan types.
Original Credit scores for RG loans look very much like those in the overall pool. And while credit scores for modified loans remain below those overall, the gap has narrowed since the new waterfall was made available. As a result, we are once again in the situation where we can’t confidently extrapolate historical trends about the relationship of loan performance and economic factors like interest rates and unemployment as a basis for decision-making. Instead, it is the details in the policy changes designed to keep borrowers in their homes that provide the clearest view on market performance.
As we have noted many times, one of the best features of loan-level analysis is the ability to segment the mortgage market into components that allow for a deepening of understanding of the behavior of the various market players. In this note we look at two groups: borrowers who get an appraisal and those who are eligible to get one but do not.
In previous posts we pointed out that analysis of the performance characteristics of mortgages with and without appraisal waivers cannot be accomplished by looking at loans with waives vs those without as many loans without waives are ineligible to obtain them. A robust analysis can only be conducted by looking at loans with waivers against loans that are qualified to get one. The qualification characteristics can be complex, but the main factor is LTV, which differs by loan purpose.
The question that naturally arises is why do some eligible borrowers not obtain a waiver when doing so would save money on the transaction? To address this issue, we look at the distribution of loan sizes for purchase loans with waivers vs those without them that are eligible. Here is the pattern of loans delivered to the GSEs YTD October 2021 by Agency:
In a recent post we looked at the evolution of the FHA purchase mortgage market share broken down between areas with a high percentage of Low-Moderate Income (LMI) households and those without. While the overall FHA share has generally declined since the onset of the pandemic, its share has held up in areas with a preponderance of LMI households. There are many factors behind these trends, but a natural consideration is underwriting standards.
To examine this factor, we use the Recursion Matched Dataset, where we create a large sample of loans with characteristics from both HMDA and the Agency disclosure data. A very high share of mortgages can be matched using our proprietary algorithm over the years 2018-2020. The coverage ratio from the Matched Dataset is provided in a previous post.
We proceed by looking at three major underwriting characteristics for LMI and non-LMI areas for FHA and the GSE’s: Credit Score (CS), Loan-to-Value (LTV) and Debt-to-Income (DTI),
Most interesting is Credit Scores:
The new FHFA Acting Director Sandra Thompson has lost no time in implementing new policies designed to support homeownership with the aim of creating greater wealth equality. This is the basis of the New Housing Policy we described in a recent post. At first, this involved extending foreclosure moratoriums for distressed families until the end of the year. Then recently, the GSE regulator announced a change in its modification policy to broaden the eligibility for rate mods to any qualifying household that were previously only available to those with a mortgage greater than or equal to 80% of the current home valuation (Current LTV>=80). This program is designed to allow as many credit-worthy borrowers to stay in their homes as possible.
The LTV limit is significant because the surge in house prices we have witnessed over the past year has meant that a relatively small share of loans should have Current LTVs greater than or equal to 80. Our loan-level data set allows us to examine this question by looking at over 25 million GSE loans. Below finds a snapshot of the total combined June books of the GSEs broken down in this manner:
We received the first loan-level performance data for the GSE’s a few months ago, so it’s about time to see what tentative observations can be drawn from this new data set. As a popular theme for this blog is the bank/nonbank share this seems a good place to start. In general, we have noticed that nonbank DQ’s tend to be higher than those for banks, and that this distinction is correlated with the relatively more generous credit terms available in the nonbank sector. Below find a table that demonstrates this for 2018 and 2019 vintage mortgages:
This can be summarized: