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Prepayment Modeling: Today’s Housing Turnover Conundrum

Presenters

Alex Fishbein

Director, TD Securities

Divas Sanwal

Head of Modeling, RiskSpan

Raj Dosaj

Chief Revenue Officer, RiskSpan

Recorded: Thursday, June 22

Accurately modeling the lock-in effect on housing turnover presents some unique challenges.

Join TD’s Alex Fishbein and RiskSpan’s Divas Sanwal as they discuss various approaches available to modelers for tackling these challenges.



What Do 2023 Origination Trends Mean for MSRs?

When it comes to forecasting MSR performance and valuations, much is made of the interest rate environment, and rightly so. But other loan characteristics also play a role, particularly when it comes to predicting involuntary prepayments.

So let’s take a look at what 2023 mortgage originations might be telling us.

Average credit scores, which were markedly higher than normal during the pandemic years, have returned during the first part of 2023 to averages observed during the latter half of the 2010s.

The most credible explanation for this most recent reversion to the mean is the fact that the Covid years were accompanied by an historically strong refinance market. Refis traditionally have higher FICO scores than purchase mortgages, and this is apparent in the recent trend.

Purchase markets are also associated with higher average LTV ratios than are refi markets, which accounts for their sharp rise during the same period

Consequently, in 2023, with high home prices persisting despite extremely high interest rates, new first-time homebuyers with good credit continue to be approved for loans, but with higher LTV and DTI ratios.

Between rates and home prices,​​borrowers simply need to borrow more now than they would have just a few years ago to buy a comparable house. This is reflected not just in the average DTI and LTV, but also the average loan size (below) which, unsurprisingly, is trending higher as well.

Recent large increases to the conforming loan limit are clearly also contributing to the higher average loan size.

What, then, do these origination trends mean for the MSR market?

The very high rates associated with newer originations clearly translate to higher risk of prepayments. We have seen significant spikes in actual speeds when rates have taken a leg down — even though the loans are still very new. FICO/LTV/DTI trends also potentially portend higher delinquencies down the line, which would negatively impact MSR valuations.

Nevertheless, today’s MSR trading market remains healthy, and demand is starting to catch up with the high supply as more money is being raised and put to work by investors in this space. Supply remains high due to the need for mortgage originators to monetize the value of MSR to balance out the impact from declining originations.

However, the nature of the MSR trade has evolved from the investor’s perspective. When rates were at historic lows for an extended period, the MSR trade was relatively straightforward as there was a broader secular rate play in motion. Now, however, bidders are scrutinizing available deals more closely — evaluating how speeds may differ from historical trends or from what the models would typically forecast.

These more granular reviews are necessarily beginning to focus on how much lower today’s already very low turnover speeds can actually go and the extent of lock-in effects for out-of-the-money loans at differing levels of negative refi incentive. Investors’ differing views on prepays across various pools in the market will often be the determining factor on who wins the bid.

Investor preference may also be driven by the diversity of an investor’s other holdings. Some investors are looking for steady yield on low-WAC MSRs that have very small prepayment risk while other investors are seeking the higher negative convexity risk of higher-WAC MSRs — for example, if their broader portfolio has very limited negative convexity risk.

In sum, investors have remained patient and selective — seeking opportunities that best fit their needs and preferences.

So what else do MSR holders need to focus on that may may impact MSR valuations going forward? 

The impact from changes in HPI is one key area of focus.

While year-over-year HPI remains positive nationally, servicers and other investors really need to look at housing values region by region. The real risk comes in the tails of local home price moves that are often divorced from national trends. 

For example, HPIs in Phoenix, Austin, and Boise (to name three particularly volatile MSAs) behaved quite differently from the nation as a whole as HPIs in these three areas in particular first got a boost from mass in-migration during the pandemic and have since come down to earth.

Geographic concentrations within MSR books will be a key driver of credit events. To that end, we are seeing clients beginning to examine their portfolio concentration as granularly as zipcode level. 

Declining home values will impact most MSR valuation models in two offsetting ways: slower refi speeds will result in higher MSR values, while the increase in defaults will push MSRs back downward. Of these two factors, the slower speeds typically take precedence. In today’s environment of slow speeds driven primarily by turnover, however, lower home prices are going to blunt the impact of speeds, leaving MSR values more exposed to the impact of higher defaults.


Duration Risk: Daily Interest Rate Risk Management and Hedging Now Indispensable

The rapid decline of Silicon Valley Bank and Signature Bank affirms the strong need for daily interest rate risk measurement and hedging. All financial institutions should have well documented management and board limits on these exposures.

Measuring risk on complex mortgage-backed securities and loan portfolios that have embedded prepayment and credit risk is challenging. RiskSpan has a one-stop risk measurement solution for all mortgage-backed securities, structured product, loan and other related assets including data management, proprietary models and risk reporting.

Our bank clients enjoy the benefit of daily risk measurement to ensure they are well-hedged in this volatile market environment.

For a limited time, under full non-disclosure, RiskSpan will offer a one-time analysis on your securities portfolio.

Please reach out if we can help your institution more fully understand the market risk in your portfolios.

There are many lessons to learn through the SVB failure. While technology (the internet) enabled the fastest run on a bank in US history, technology can also be the solution. As we just saw US Government securities are risk-free for credit but not interest rate movements. When rates rose, security prices on the balance sheet of SVB declined in lock-step. All financial institutions (of all sizes) need to act now and deploy modern tech to manage modern risks – this means managing duration risk on a daily basis. It’s no longer acceptable for banks to review this risk monthly or weekly. Solutions exists that are practical, reliable and affordable.


Webinar Recording: An Investor’s Guide to America’s Housing Supply Crisis

Presenters

Amy Crews Cutts

President, AC Cutts and Associates and Chief Economist, NACM

Michael Neal

Equity Scholar and 
Principal Research Associate, Urban Institute

Janet Jozwik

Senior Managing Director and Head of Climate Analytics, RiskSpan

Divas Sanwal

Managing Director and Head of Modeling, RiskSpan

Recorded: Wednesday, March 29th

An informative webinar on the nation’s current “out-of-whack” housing supply and what it means for mortgage investors, homeowners, prospective homebuyers, and renters alike!

Housing economists Amy Crews Cutts and Michael Neal join RiskSpan credit and prepayment modelers Janet Jozwik and Divas Sanwal as they explore the factors that contribute to the current housing supply imbalance, including the cost of building, the impact of permits and zoning, and the emergence of the “missing middle.” They discuss how high interest rates and rental prices are incentivizing owners who relocate to hold old on to their old properties and become landlords. They also examine the impact of ADUs, zoning issues, and the availability of renovation financing.

Mortgage loan and security investors will learn about what housing supply means for prepay speeds. The panelists will consider the role of financing in addressing housing supply issues, including the market for low-balance loans and unconventional options like contracts for deed and lease-to-own arrangements.

The panel discusses the evolving housing needs of the population, including the desire to age in place, the challenges posed by multigenerational living arrangements, and the viability of several proposed solutions, including the potential for converting unused commercial properties into housing.



RiskSpan Incorporates Flexible Loan Segmentation into Edge Platform

ARLINGTON, Va., March 3, 2023 — RiskSpan, a leading technology company and the most comprehensive source for data management and analytics for residential mortgage and structured products, has announced the incorporation of Flexible Loan Segmentation functionality into its award-winning Edge Platform.

The new functionality makes Edge the only analytical platform offering users the option of alternating between the speed and convenience of rep-line-level analysis and the unmatched precision of loan-level analytics, depending on the purpose of their analysis.

For years, the cloud-native Edge Platform has stood alone in its ability to offer the computational scale necessary to perform loan-level analyses and fully consider each loan’s individual contribution to a mortgage or MSR portfolio’s cash flows. This level of granularity is of paramount importance when pricing new portfolios, taking property-level considerations into account, and managing tail risks from a credit/servicing cost perspective.

Not every analytical use case justifies the computational cost of a full loan-level analysis, however. For situations where speed requirements dictate the use of rep lines (such as for daily or intra-day hedging needs), the Edge Platform’s new Flexible Loan Segmentation affords users the option to perform valuation and risk analysis at the rep line level.

Analysts, traders and investors take advantage of Edge’s flexible calculation specification to run various rate and HPI scenarios, key rate durations, and other calculation-intensive metrics in an efficient and timely manner. Segment-level results run at both loan and rep line level can be easily compared to assess the impacts of each approach. Individual rep lines are easily rolled up to quickly view results on portfolio subcomponents and on the portfolio as a whole.

Comprehensive details of this and other new capabilities are available by requesting a no-obligation demo at riskspan.com.

This new functionality is the latest in a series of enhancements that further the Edge Platform’s objective of providing frictionless insight to Agency MBS traders and investors, knocking down barriers to efficient, clear and data-driven valuation and risk assessment.

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About RiskSpan, Inc. 

RiskSpan offers cloud-native SaaS analytics for on-demand market risk, credit risk, pricing and trading. With our data science experts and technologists, we are the leader in data as a service and end-to-end solutions for loan-level data management and analytics. Our mission is to be the most trusted and comprehensive source of data and analytics for loans and structured finance investments. Learn more at www.riskspan.com.


Takeaways from SFVegas 2023

The most highly attended conference in recent years brought together leaders from government, capital markets, and tech institutions to discuss the current state and future of the securitization markets.

SFVegas remains the optimal environment for fostering healthy dialogue aimed at making markets more efficient and transparent by creating innovative, new solutions.  RiskSpan is delighted to be engaged in this dialogue.  

Here are our key takeaways from the conference.

Loan Innovation

Sticky inflation and high interest rates are creating a macroeconomic environment that is particularly conducive to bringing new residential mortgage products to market. Market demand for HELOCs and other second-lien products is driving innovation around these offerings and accelerating their acceptance. ARM production is growing rapidly and is at some of the highest levels in over a decade.

Product Innovation is moving forward with both consumers and investors in mind. Consumers are in search of access to better financing while investors seek new ways to participate in these markets.

Technology-Accelerated (R)evolution

Data is driving the dialogue. New scoring tools (FICO10T and Vantage Score 4.0), new ESG-related data and better disclosures are creating a much more transparent investment process

Cloud-native applications continue to make analytics processing cheaper and differentiate how investors and their counterparties seek relative value. Efficiency in data management and analytics separates winner and losers.

Accelerated adoption of AI-driven solutions will drive market operational efficiency in the coming years. The adoption and use cases are just beginning to be uncovered. 

New Investors, New Ideas

New investors are bringing fresh capital to the market with new ideas on how to maximize risk-adjusted returns. Investors backed by private equity are seeking new returns in virtually every category of structured markets: MSRs, BPLs and CLOs. Interest in these classes will only grow in the coming years as more investors seek to maximize returns in private assets.

The international investor community remains strong as global asset allocation is shifting towards the U.S. and fewer opportunities exist in overseas markets


RiskSpan sits at the intersection of all of these trends by helping structured finance investors of every type to leverage technology and data solutions that uncover market opportunities, mitigate risks and deliver new products

Great conference! Get in touch with us to learn more about how RiskSpan help clients simplify, scale, and transform their structured finance analytics!


RiskSpan’s Snowflake Tutorial Series: Ep. 1

Learn how to create a new Snowflake database and upload large loan-level datasets

The first episode of RiskSpan’s Snowflake Tutorial Series has dropped!

This six-minute tutorial succinctly demonstrates how to:

  1. Set up a new Snowflake #database
  2. Use SnowSQL to load large datasets (28 million #mortgage loans in this example)
  3. Use internal staging (without a #cloud provider)

This is this first in what is expected to be a 10-part tutorial series demonstrating how RiskSpan’s Snowflake integration makes mortgage and structured finance analytics easier than ever before.

Future topics will include:

  • Executing complex queries using python functions in Snowflake’s SQL
  • External Tables (accessing data without a database)
  • OLAP vs OLTP and hybrid tables in Snowflake
  • Time Travel functionality, clone and data replication
  • Normalizing data and creating a single materialized view
  • Dynamic tables data concepts in Snowflake
  • Data share
  • Data masking
  • Snowpark: Data analysis (pandas) functionality in Snowflake

Agency Social Indices & Prepay Speeds

Do borrowers in “socially rich” pools respond to refinance incentives differently than other borrowers? 

The decision by Fannie and Freddie to release social index disclosure data in November 2022 makes it possible for investors to direct their capital in support of first-time homebuyers, historically underserved borrowers, and people who purchase homes in traditionally underserved areas. Because socially conscious investors likely also have interest in understanding how these social pools are likely to perform, we were curious to examine and learn whether mortgage pools with higher social ratings behaved differently than pools with lower social ratings (and if a difference existed, how significant it was). To the extent that pools rich in social factors perform better (i.e., prepay more slowly) than pools generally, we expect investors to put an even higher premium on them. This in turn should result in lower rates for the borrowers whose loans contribute to pools with higher social scores. 

The data is new and we are still learning things, but we are beginning to discern some differences in prepay speeds.

Definitions 

First, a quick refresher on Fannie’s and Freddie’s social index terminology: 

  • Social Criteria Share (SCS): The percentage of loans in a given pool that meet at least one of the “social” criteria. The criteria are low-income, minority, and first-time homebuyers; homes in low-income areas, minority tracts, high-needs rural areas; homes in designated disaster areas and manufactured housing. As of December 2022, 42.12 percent of loans in the average pool satisfy at least one of these criteria. 
  • Social Density Score (SDS): A measure of how many criteria the average loan in a given pool satisfies. For simplicity, the index consolidates the criteria into three categories – those pertaining to income, those pertaining to the borrower, and those pertaining to the property. A pool’s SDS can be zero, 1, 2, or 3 depending on the number of categories within which the loan satisfies at least one criterion. The average SDS as of December 2022 is 0.62 (out of 3). 

Do social index scores impact prepay speeds? 

While it remains too early to answer this question with a great deal of certainty, historical performance data appears to show that pools with below-average social index scores prepay faster than more “social” bonds. 

We first looked at a high-level, simplistic relationship between prepayments and Social Density Score. In Figure 1, below, pools with below-average Social Density Scores (blue line) prepay faster than both pools with above-average SDS (black line) and pools with the very highest SDS (green line) when they are incentivized by interest rates to do so. (Note that very little difference exists among the curves when borrowers are out of the money to refi.)  


Fig. 1: Speeds by Prepay Incentive and Social Density Score 

See how easy RiskSpan’s Edge Platform makes it for you to do these analyses yourself.

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We note a similar trend when it comes to Social Criteria Share (see Fig. 2, below).  


Fig. 2: Speeds by Prepay Incentive and Social Criteria Share 

Social Pool Performance Relative to Spec Pools 

Investors pay up for mortgage pools with specified characteristics. We thought it worthwhile to compare how certain types of spec pools perform relative to socially rich pools with no other specified characteristics. 

Figure 3, below, compares the performance of non-spec pools with above-average Social Criteria Share (orange line) vs. spec pools for low-FICO (blue line), high-LTV (black line) and max $250k (green line) loans. 

Note that, notwithstanding a lack of any other specific characteristics that investors pay up for, the high-SCS pools exhibit a somewhat better convexity profile than the max-700 FICO and min-95 LTV pools and slightly worse convexity (in most refi incentive buckets) than max-250k pools. 


Fig. 3: Speeds by Prepay Incentive and Social Criteria Share: Socially Rich (Non-Spec) Pools vs. Selected Spec Pools

We observe a similar effect when we compare non-spec pools with an above-average Social Density Score to the same spec pools (Fig. 4, below).   


Fig. 4: Speeds by Prepay Incentive and Social Density Score: Socially Rich (Non-Spec) Pools vs. Selected Spec Pools 

See how social index scores affect speeds relative to other spec pools.

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Edge Platform Adds Fannie and Freddie Social Index Data

ARLINGTON, Va., January 18, 2023 — RiskSpan, a leading technology company and the most comprehensive source for data management and analytics for residential mortgage and structured products, has announced the incorporation of Fannie Mae’s and Freddie Mac’s Single-Family Social Index data into its award-winning Edge Platform.

Fannie and Freddie rolled out their social index disclosures in November 2022. Consisting of two measures, the Social Criteria Score and the Social Density Score, the social index discloses the share of loans in a given pool that are made to low-income, minority, and first-time homebuyers, as well as mortgages on homes in low-income areas, minority tracts, high-needs rural areas, and designated disaster areas. Manufactured housing loans also contribute to the score.

Rather than classifying each individual bond as “social” or “not social,” the new Agency data available on the Edge Platform assigns every pool two fully transparent scores – one indicating the percentage of loans in a pool that satisfy any of the defined social criteria, the other reflecting how many criteria a pool’s average loan satisfies.

Taken together, these enable Agency traders and investors to view and understand each pool along a full continuum of the social index, as opposed to simply assigning a binary social designation. Because borrowers behave differently at various places along this continuum, traders and investors fine-tune their analytics in ways never before possible to isolate pools with potentially slower prepayment speeds in a way that transcends what has traditionally been available using so-called “spec. pool” stories alone.

Comprehensive details of this and other new capabilities are available by requesting a no-obligation live demo at riskspan.com.

This new functionality is the latest in a series of enhancements that further the Edge Platform’s objective of providing frictionless insight to Agency MBS traders and investors, knocking down barriers to efficient, clear and data-driven valuation and risk assessment.

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About RiskSpan, Inc. 

RiskSpan offers cloud-native SaaS analytics for on-demand market risk, credit risk, pricing and trading. With our data science experts and technologists, we are the leader in data as a service and end-to-end solutions for loan-level data management and analytics.

Our mission is to be the most trusted and comprehensive source of data and analytics for loans and structured finance investments.

Rethink loan and structured finance data. Rethink your analytics. Learn more at www.riskspan.com.

Get a Demo

About RiskSpan, Inc. 

RiskSpan offers cloud-native SaaS analytics for on-demand market risk, credit risk, pricing and trading. With our data science experts and technologists, we are the leader in data as a service and end-to-end solutions for loan-level data management and analytics. 

Our mission is to be the most trusted and comprehensive source of data and analytics for loans and structured finance investments. 

Rethink loan and structured finance data. Rethink your analytics. Learn more at www.riskspan.com. 

Media contact: Timothy Willis 


Webinar Recording: New Mobility Trends: The Impacts of Covid & Climate

Recorded: Wednesday, January 25th | 2:00 p.m. EST

As the Covid-19 pandemic began taking hold three years ago, very few people foresaw the dramatic impact it would have on household mobility. And yet within a year, millions of people had resettled – some temporarily, some permanently – to locations untethered to where their jobs were. Notwithstanding a gradual return to some offices, a tight labor market has enabled the increased mobility initially brought about by Covid to persist.

Will these mobility trends persist as other pandemic-era practices continue to recede? What role will climate change play in mobility as an increasing number of areas grapple with questions of insurability and other challenges tied to climate risk.

Housing economist Amy Crews Cutts, Freddie Mac chief economist and head of housing research Sam Khater, and RiskSpan head of modeling Divas Sanwal and head of climate analytics Janet Jozwik explore how these otherwise unrelated macro factors — Covid and climate – are combining to impact household mobility in the coming years.


Presenters

Amy Crews Cutts

President, AC Cutts and Associates and Chief Economist, NACM

Sam Khater

VP, Chief Economist, and Head of Freddie Mac’s Economic Housing and Research Division

Janet Jozwik

Senior Managing Director and Head of Climate Analytics, RiskSpan  

Divas Sanwal

Managing Director and Head of Modeling, RiskSpan


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