Agency MBS Archives

Edge: PIW and Prepayments

Inspection waivers have been available on agency-backed mortgages since 2017, but in this era of social distancing, the convenience of forgoing an inspection looks set to become an important feature in mortgage origination. In this post, we compare prepayments on loans with and without inspections.

Broadly, FNMA allows inspection waivers on purchase single-family mortgages up to 80% LTV, and no cash-out refi with up to 90% LTV (75% if the refi is an investment property). Inspection waivers are available on cash-out refis for primary residences with LTV up to 70%, and investment properties with LTV up to 60%.

Inspection waivers were first introduced in mid-2017. In 2018, the proportion of loans with inspection waivers held steady around 6% but started a steady uptick in the middle of 2019, long before the pandemic made social distancing a must.[1]

Cumulative Proportion of Loans with Waivers

In the current environment, market participants should expect a further uptick in loans with waivers as refis increase and as the GSEs consider relaxing restrictions around qualifying loans. In short, PIW will start to become a key factor in loan origination. Given this, we examine the different behavior between loans with waivers and loans with inspections.

In the chart below, we show prepayment speeds on 30yr borrowers with “generic” mortgages,[2] with and without waivers. When 100bp in the money, “generic” loans with a waiver paid a full 15 CPR faster than loans with an inspection appraisal. Additionally, the waiver S-curve is steeper. Waiver loans that are 50-75bp in the money outpaced appraised houses by 20 CPR.

Next, we look at PIW by origination channel. For retail origination, loans with waivers paid only 10-15 CPR faster than loans with inspections (first graph). In contrast, correspondent loans with a waiver paid 15-20 CPR faster versus loans with an inspection (second graph).

We also looked at loan purpose. Purchase loans with a waiver paid only 10 CPR faster than comparable loans purchase loans with an inspection (first graph), whereas refi loans paid 25 CPR faster when 50-75bp in the money.

We also examined servicer-specific behavior for PIW. We saw both a difference in the proportional volume of waivers, with some originators producing a heavy concentration of waivers, as well as a difference in speeds. The details are lengthy, please contact us on how to run this query in the Edge platform.

In summary, loans with inspection waivers pay faster than loans without waivers, but the differentials vary greatly by channel and loan purpose. With property inspection waivers rising as a percentage of overall origination, these differences will begin to play a larger role in forming overall prepayment expectations.

If you interested in seeing variations on this theme, contact us. Using RS Edge, we can examine any loan characteristic and generate a S-curve, aging curve, or time series.

[1] Refi loans almost entirely drove this uptick in waivers, see RiskSpan for a breakdown of refi loans with waivers.

[2] For this query, we searched for loans delivered to 30yr deliverable pools with loan balance greater than $225k, FICO greater than 700, and LTV below 80%.

What The FHFA’s Forbearance Announcement Means for Agency Prepayments

On Tuesday, the market received a modicum of clarity around Agency prepayments amid the uncertainty of COVID-19, when the FHFA released new guidelines for mortgage borrowers currently in forbearance or on repayment plans who wish to refinance or buy a new home.

Borrowers that use forbearance will most likely opt for a forbearance deferment, which delays the missed P&I until the loan matures. The FHFA announcement temporarily declares that borrowers are eligible to refinance three months after their forbearance ends and they have made three consecutive payments under their repayment plan, payment deferral option, or loan modification.”

With the share of mortgage loans in forbearance accelerating to over 8 percent, according to the MBA, and retail mortgage interest rates remaining at historically low levels, the FHFA’s announcement potentially expands the universe of mortgages in Agency securities eligible for refi. However, mortgage rates must be sufficiently low as to make economic sense to refinance both the unpaid principal balance of the loan and the deferred payments, which accrue at 0%. We estimate that a 6-month forbearance means that rates must be an additional 25bp lower to match the same payment savings as a borrower who doesn’t need to refinance the deferred payments. In turn, this will slow refinancing on loans with a forbearance deferment versus loans without forbearance, when faced with the same refinancing incentive. This attenuated refi activity is on top of the three-payment delay after forbearance is over, which pushes the exercise of the call option out three months and lowers the probability of exercise. In total, loans in forbearance will both be slower and have better convexity than loans not in forbearance.

Today’s FHFA release also extends Fannie’s and Freddie’s ability to purchase single-family mortgages currently in forbearance until at least August 31, 2020.

RiskSpan VQI: Current Underwriting Standards – March 2020

The RiskSpan Vintage Quality Index (“VQI”) indicates that we are entering the current economic downturn with a cohort of mortgages that were far more conservatively originated than the mortgages in the years leading up to the 2008 crisis. The VQI dropped three points for mortgages originated during March to finish the first quarter of 2020 at 87.77. This reflects generally tight underwriting standards leading into the COVID-19 crisis, though not nearly as tight as what was witnessed in the years immediately following the housing finance crisis.

The VQI climbed slightly during the first two months of the year—evidencing a mild loosening in underwriting standards—peaking at just over 90 in February, before dropping to its current level in March. The following chart illustrates the historical trend of risk layering that contributes to the VQI and how that layering has evolved over time. Mortgages with one borrower—now accounting for more than 50 percent of originations—remain a consistent and important driver of the index and continued to climb during Q1. High-DTI loans, which edged higher in Q1, continue to drive the index today but not nearly to the degree they did in the years leading up to the 2008 crisis.

RiskSpan introduced the VQI in 2015 as a way of quantifying the underwriting environment of a particular vintage of mortgage originations. The idea is to provide credit modelers a way of controlling for a particular vintage’s underwriting standards, which tend to shift over time. The VQI is a function of the average number of risk layers associated with a loan originated during a given month. It is computed using:

The loan-level historical data released by the GSEs in support of Credit Risk Transfer initiatives (CRT data) for months prior to December 2005, and
Loan-level disclosure data supporting MBS issuances through today.

The value is then normalized to assign January 1, 2003 an index value of 100. The peak of the index, a value of 139 in December 2007, indicates that loans issued in that month had an average risk layer factor 39% greater (i.e., loans issued that month were 39% riskier) than loans originated during 2003. In other words, lower VQI values indicate tighter underwriting standards (and vice-versa).

Build-Up of VQI

The following chart illustrates how each of the following risk layers contributes to the overall VQI:

Loans with low credit scores (FICO scores below 660)
Loans with high loan-to-value ratios (over 80 percent)
Loans with subordinate liens
Loans with only one borrower
Cash-out refinance loans
Loans secured by multi-unit properties
Loans secured by investment properties
Loans with high debt-to-income ratios (over 45%)
Loans underwritten based on reduced documentation
Adjustable rate loans

Modeling Delinquency Deluge

RiskSpan’s CEO Bernadette Kogler recently spoke with Simon Boughey of Structured Credit Investor (SCI) to discuss COVIDー19’s impact on the mortgage market & securitizations of mortgage assets. Simon’s article has been republished here with their permission.

Wednesday 8 April 2020 17:45 London/ 12.45 New York/ 01.45 (+ 1 day) Tokyo

Mortgage market advisers and consultants are struggling to find any models that work for the current crisis, but they are telling clients that they should prepare for a worst case scenario in mortgage market and securitizations of mortgage assets.

“Our clients are modeling a range of scenarios but are preparing themselves for the worst case including sustained levels of unemployment. Hopefully it won’t be that bad, but they need to prepare themselves,” says Bernadette Kogler, Chief Executive Officer of RiskSpan, a Washington, DC-based analytics and modeling firm which has particular expertise in mortgage markets.

RiskSpan clients include firms prominent in the mortgage securitization industry, such as lenders and servicers like Wells Fargo and Flagstar, as well as Fannie Mae and Freddie Mac. It also has clients on the buy-side, such as Barings, Northern Trust and Fidelity.

Both buy-side and sell-side clients are struggling to assess what the economic devastation of the last two weeks, with more to come, will mean for the MBS markets.

The “worst case” could be very bleak indeed. Economists at the Federal Reserve Bank of St Louis have predicted that the dislocation elicited by COVID-19 could cause 47M job losses in the US. This translates to an unemployment rate of 32% – comfortably worse than the rate of 25% recorded in the Great Depression of 1930-33.

Other economists are not quite so pessimistic, but Kogler agrees and she is advising clients to prepare for an unemployment rate of 30% in the worst affected regions of the USA. Las Vegas, Nevada, for example, is particularly exposed to the collapse of the hospitality industry, while Texas has been hit with a double whammy of a Coronavirus lockdown and a precipitous decline of oil and gas prices.

Metropolitan Las Vegas has a population of over 2.5M while the state of Texas is home to over 12.5M people.

An unemployment rate of 30% could lead to a mortgage delinquency rate of around 30%. Data provided by the Bureau of Labor shows that the correlation between unemployment and mortgage delinquency is very high – virtually 1:1. So, for example, both unemployment and mortgage delinquency peaked at around 10% in the Great Recession.

mortgage delinquency rate and unemployment rare

At the moment, a delinquency rate of 10% looks a lot better than what might be seen in a few months from now. Of course, foreclosure rates will be substantially lower than delinquencies, but if delinquencies do hit 30% foreclosures might be as high as 30%. The effect on the MBS market, both agency and non-agency, of delinquency rates of this magnitude is hard to over-estimate.

Kogler suggests that around 1M Federal Housing Authority (FHA) loans could be affected by unemployment levels like that.

The GSEs, of course, offer largely guaranteed debt to capital markets investors in the TBA market, so their position could become particularly painful.

On January 23, when COVID-19 was still something to be not too bothered about, Federal Housing Finance Authority (FHFA) director Mark Calabria gave a speech to National Association of Homebuilders and reminded his audience that Fannie Mae and Freddie Mac had a leverage ratio of 300 to 1.

“Given their risks and financial position, even in a modest downturn, Fannie and Freddie will fail,” he said.

Part of the problem in modeling for a disaster of this proportion is that there are still many unknowns. Though the Federal Reserve has intervened with a stimulus package, but no-one knows how much it will continue to do, or can do, as the crisis persists.

Certain areas of the mortgage industry are still without any Federal aid. Mortgage originators and servicers hope to receive some backing, but nothing has been divulged as yet.

Models based on natural disasters provide no firm clue about this crisis will unfold. In disasters of that kind, insurance companies intervene at some juncture, distorting the appropriateness of disaster-based models for the COVID-19 world.

“No models are sufficient. Predictive models are based on historical data, and to the extent that we have not seen anything like this before they are not going to work,” says Kogler.

Simon Boughey

08/04/2020 17:45:18

This article was published in Structured Credit Investor on 08 April 2020.

RS Edge: Loan-level Delinquencies in GNMA Pools

With the rapid rise of social distancing and a looming recession, investor thoughts are turning towards mortgage delinquencies and defaults. In GNMAs, loans that are 90+ days delinquent may be bought out of the pool by the servicer. When a servicer does this, the repurchase shows up as an involuntary prepay for the investor. GNMA servicers may buy the loan out a pool when it turns 90 days delinquent or more but must do so using their own capital. Given this, we may start to see a separation in buyout behavior between well-capitalized bank servicers and more thinly capitalized non-bank servicers, with longer liquidation timelines for some entities over others.¹

The GNMA loan–level data shows each loan’s delinquency status, listed from current to 180+ days delinquent.² In Edge, users can run either a single pool or a portfolio and separate the loans into buckets by individual servicer. Users can simultaneously overlay other filters such as loan guarantor, geography, mark-to-market LTV, and other. Doing this at portfolio level can help quantify a portfolio’s exposure to various bank and non-bank servicers segregated by different loan characteristics.

It is difficult to predict the exact repurchase differential we will see between bank and non-bank servicers, but for MBS investors, it will certainly be important to quantify the exposure at both pool and portfolio level as a first step. Most market participants expect a substantial uptick in the number of involuntary prepayments in the GNMA space. Edge lets users rapidly assess delinquency exposure across many different loan characteristics for an entire portfolio, which may matter more now than it ever has in recent history.

RS EDGE: Loan-level Delinquencies in GNMA Pools

Loan-level delinquency by servicer for 2019-vintage GN Multi-lender pools, broken out by FHA/VA. This search is simple to execute in the Edge platform. Contact us for details.

¹ In 2011-12, the market saw significant differences in buyout behavior, for example Bank of America was slow to buy out delinquent loans.

² On Bloomberg, the delinquency states 90 days onward are compressed into a single 90+ state.

RS Edge: S-curves Over Different Refi Cycles

Over the last six months, TBA speeds have progressively accelerated and are poised to print even faster given the recent lows in primary rates and near doubling in the Refi Index. But how do these speeds compare against previous refi cycles? In this short piece, we compare today’s S-curve against the 2012-13 cycle and the massive refi wave in 2002-03.

First, we start by running an S-curve on loans in recently issued Majors¹, filtering for loans that were 2019 vintage and at least 6 months seasoned. Below, we plot prepay speeds against refi incentive². In aggregate, fully in-the-money mortgages pay around 55 CPR, with actual speeds varying from pool to pool.

Next, we overlay a TBA S-curve during the 2012-13 refi wave, covering the period both pre– and post–QE3 (September 2012). Traders during that time will remember top speeds in the mid to upper 30s. Clearly the 2019-20 prepay experience has exceeded these speeds for similar refi incentive.

Finally, we compare the current refi environment against the 2002-03 environment—the gold standard for refinancing waves. Traders active during that period will remember this as a time of high cash-out refis, which drove both in– and out-of-the money prepayments higher. Out-of-the-money mortgages paid in the mid-teens as homeowners tapped their homes like an ATM, while in-the-money mortgages paid in the high 60s to low 70s in aggregate, with some sectors paying in the 80s for several months.

The 2002-03 refi wave also featured a surge driven by the “media effect.” With nearly the entire mortgage market in–the–money, a combination of aggressive advertising plus frequent news reporting reminded homeowners at every turn that they could save hundreds of dollars per month if they refinanced their loans. In early 2003, 95% of the mortgage market was 50bp or more in the money, compared with 80% today.

We conclude that with Fed easing and recession fears, 2020 could see a renewed media effect, which may help drive prepayments higher at every point on the S-curve.

If you are interested in seeing variations on this theme, contact us. Using RS Edge, we can examine any loan characteristic and generate a S-curve, aging curve, or time series.

¹ We did a similar analysis on multi-lender Giants. Please contact us for details.

² To be included, the loan had to be at least 6 months old, higher than $225k balance, LTV < 80, and FICO > 700.

RiskSpan VQI: Current Underwriting Standards – February 2020

The RiskSpan Vintage Quality Index (“VQI”) edged higher for mortgages originated during February despite remaining low (90.41) by historical, pre-crisis standards. Low-FICO and high-LTV loans continued to trend downward, while high-DTI loans, investment properties, and cash-out refinances continued to rebound after declining through much of 2019.

As the historical trend of risk layering (see below) shows, mortgages with one borrower—now accounting for more than 50 percent of originations—remain a consistent and important driver of the index. High-DTI loans today drive the index more than they did during the years immediately after the 2008 crisis but not nearly so much as they did during the years leading up to it. High-LTV loans continue to be originated in abundance, while adjustable-rate mortgages and loans with subordinate financing, in contrast, have practically vanished.

The loan-level historical data released by the GSEs in support of Credit Risk Transfer initiatives (CRT data) for months prior to December 2005, and
Loan-level disclosure data supporting MBS issuances through today.

Build-Up of VQI

The following chart illustrates how each of the following risk layers contributes to the overall VQI:

Loans with low credit scores (FICO scores below 660)
Loans with high loan-to-value ratios (over 80 percent)
Loans with subordinate liens
Loans with only one borrower
Cash-out refinance loans
Loans secured by multi-unit properties
Loans secured by investment properties
Loans with high debt-to-income ratios (over 45%)
Loans underwritten based on reduced documentation
Adjustable rate loans

FHFA Prepayment Monitoring Reports are Powered by RS Edge

[vc_row][vc_column][vc_column_text]To help enforce prepayment alignment across Fannie’s and Freddie’s Uniform MBS, the Federal Housing Finance Agency publishes a quarterly monitoring report comparing the prepayment speeds of UMBS issued by the two Agencies. This report helps ensure that prepayment performance remains consistent—so that market expectations of a Fannie-issued UMBS are fundamentally indistinguishable from those of a Freddie-issued UMBS and the two Agencies UMBS are both deliverable into passthrough “TBA” trades.

Last week, the FHFA released the most recent version of this report containing performance data from the fourth quarter of 2019. The charts in the FHFA’s publication, which are generated using RiskSpan’s Edge Platform, compare Fannie and Freddie UMBS prepayment rates (1-month and 3-month CPRs) across a variety of coupons and vintages.

Relying on RiskSpan’s Edge Platform for this sort of analysis is fitting in that it is precisely the type of comparative analysis for which Edge was developed.

Edge allows traders, portfolio managers, and analysts to compare performance across a virtually unlimited number of loan subgroups. Users can cohort on multiple loan characteristics, including servicer, vintage, loan size, geography, LTV, FICO, channel, or any other borrower characteristic.

Edge’s easy-to-navigate user interface makes it accessible to traders and PMs who want to be able to set up queries and tweak constraints on the fly without having to write SQL code. Edge also offers an API for users that want programmatic access to the data, useful for generating customized reporting and systematic analysis of loan sectors.

Comparing Fannie’s and Freddie’s prepay speeds only scratches the surface of Edge’s analytical capabilities. Schedule a demo to see what this tool can really do.[/vc_column_text][/vc_column][/vc_row]

RS Edge: WALA Ramps for Non-Bank Servicers

In 2019, the non-bank servicing sector continued to grow faster than traditional bank-servicers. As a group, non-bank servicers now represent nearly half of the agency MBS market, with outsized representation in newer-production mortgages. Their aggressive refinancing has driven speeds on in-the-money mortgages to post-crisis highs, and we believe this behavior will continue into 2020.

But within the non-bank sector, prepayment behavior varies widely. In this short post, we measure the fastest non-bank servicers against their cohorts and against the wider market.

We used the Edge platform to generate WALA ramps for the top 25 non-bank servicers for 30yr “generic” mortgages.¹ In the first graph, we show WALA ramps for bank-serviced and non-bank–serviced loans that were 75-125bp in the money over the last calendar year. At the peak, non-bank servicers outstripped bank servicers by roughly 8 CPR.

Graph

In the next chart, we break out performance for the two fastest non-bank servicers: United Shore and Provident Funding.² United Shore clocked in at a blazing 83 CPR for the 7-8 WALA bucket with Provident printing in the high 70s.

Switching to SMM—the right way to examine such fast speeds—we see that loans serviced by United Shore paid at 13.7 SMM, more than twice the unscheduled principal per month than the cohort of non-bank servicers in months 7 and 8.

In closing, we note that newer vintage Freddie Mac Supers consistently contain more United Shore and Provident product than similarly aged Fannie Mae Majors. Together, United Shore and Provident account for 14-18% of newer–production Freddie Supers, such as FR SD8016, SD8005, SD8001, and SD8006, but only 4-6% of Fannie Majors, such as FN MA3774 or MA3745. Most of the fast-payer Freddie Supers are 3s and 3.5s and may not show fast speeds at current rates, but in a 25-50bp rally we may see separation between Fannie and Freddie TBA speeds. As a consequence, Freddie Supers may have worse convexity than similar vintage Fannie Majors.

If you are interested in seeing variations on this theme, contact us. Using RS Edge, we can examine any loan characteristic and generate a S-curve, WALA curve, or time series. [/vc_column_text][/vc_column][/vc_row][vc_row][vc_column][vc_empty_space][vc_empty_space][startapp_separator border_width=”1″ opacity=”25″ animation=””][/vc_column][/vc_row][vc_row][vc_column][vc_column_text]¹For a loan to be included, it had to be securitized into a deliverable 30yr Fannie or Freddie pool and have a loan balance greater than $225,000, FICO > 700, LTV <= 80, and not in NY state. All analysis was done at loan level.

²New Residential and Home Point Financial receive an honorable mention for fast speeds. Their speeds showed more response for loans 50-100bp in the money but started to converge to average non-bank speeds when 75-125bp in the money. See RiskSpan for details.

FHFA 3Q2019 Prepayment Monitoring Report

FHFA’s 2014 Strategic Plan for the Conservatorships of Fannie Mae and Freddie Mac includes the goal of improving the overall liquidity of Fannie Mae’s and Freddie Mac’s (the Enterprises) securities through the development of a common mortgage-backed security. This report provides insight into how FHFA monitors the consistency of prepayment rates across cohorts of the Enterprises’ TBA-eligible MBS.

Download Report

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Edge: PIW and Prepayments

What The FHFA’s Forbearance Announcement Means for Agency Prepayments

RiskSpan VQI: Current Underwriting Standards – March 2020

Build-Up of VQI

Modeling Delinquency Deluge

RS Edge: Loan-level Delinquencies in GNMA Pools

RS Edge: S-curves Over Different Refi Cycles

RiskSpan VQI: Current Underwriting Standards – February 2020

Build-Up of VQI

FHFA Prepayment Monitoring Reports are Powered by RS Edge

RS Edge: WALA Ramps for Non-Bank Servicers

FHFA 3Q2019 Prepayment Monitoring Report

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