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Higher Rates, Smarter Models, and Fresher Credit Insights: August Models & Markets Recap

Register here for next month’s call: Thursday, September 18th, 2025, 1 p.m. ET. 

Each month, we host a Models & Markets call to offer our insights into recent model performance, emerging credit risks, and broader economic indicators. This month’s call was a wide-ranging update on new model developments, consumer credit insights, and macroeconomic trends shaping structured finance. 

Here’s a quick recap in case you missed it. 

(Click here to listen to the entire 30-minute recording or continue reading for a summary.)  

Market Outlook: August 2025

Stable employment and inflation notwithstanding, the macro backdrop remains dominated by persistent headwinds: 

  • Mortgage Rates: Still above 6.5% and expected to stay above 6% for the next several years. 
  • Home Prices: Case-Shiller data shows relative stability, with modest month-over-month declines and low year-over-year growth. 
  • Labor & Inflation: Both unemployment and PCE inflation are holding steady. 
  • Fed Policy: The Fed Funds Rate remains in the 4.25%–4.50% range, with the first cut expected in September 2025. Markets anticipate a year-end rate of 3.75%–4.00%, but long-term rates remain elevated. 
  • 10Yr rates unlikely to see a significant decline over next few years, leading to a high mortgage rate environment (>~ 6%) for next 3-5 years. 

New Equifax Data Integration 

We introduced our latest research leveraging the Equifax Analytic Dataset (ADS), a borrower-level anonymized sample representing 10% of the U.S. active credit population. Using tradeline-level detail (credit scores, balances, payments, etc.), we have constructed aging curves for auto loans and personal loans segmented by credit score bands. 

Some key takeaways: 

  • Auto Loan Defaults: Clear segmentation appears across credit score bands, with default curves validated against Federal Reserve data. 

  • Personal Loan Defaults: Similar segmentation trends, with early results indicating significant variation across risk tiers. 
  • Credit card and student loan performance curves: Coming soon. 

The final versions of these datasets will be accessible directly within the RiskSpan platform, allowing clients to benchmark their portfolios against robust national trends. 

Model Updates 

Prepayment Models (Versions 3.2 & 3.7) 

Our prepayment models continue to perform strongly against observed market behavior. The latest back-testing of agency cohorts (Fannie Mae and Freddie Mac 2021/2022 vintages across 1.5%–6.5% coupons) shows that speeds remain broadly consistent with expectations. However, higher coupon pools have recently exhibited slower-than-expected speeds, reflecting both tighter refinancing conditions and borrower credit constraints. 

1.5 to 3.5 Coupons 

6.5 Coupons 

Credit Model 7.0 

Our much-anticipated Credit Model v7 is now available in production on the RiskSpan Platform. Key features include: 

  • Delinquency Transition Matrix – A granular 3-D framework tracking monthly movement of loans through delinquency buckets (30D, 60D, 90D, 120D, 150D, 180D+, Foreclosure, REO). 
  • Severity & Liquidation Enhancements – Expanded severity vectors and a liquidation timeline module allow for more nuanced control of loss projections. 
  • Integration with MSR Engine – Provides detailed P&I and T&I cash flow accounting that captures probabilistic delinquency transitions. 

These enhancements equip investors and risk managers with deeper tools for analyzing loss dynamics across mortgage, GSE, FHA, and VA loan cohorts. 

Contact us to learn more.

Navigating Headwinds with Data and AI: July Models & Markets Recap

Register here for next month’s call: Thursday, August 21st, 2025, 1 p.m.

Each month, we host a Models & Markets call to offer our insights into recent model performance, emerging credit risks, and broader economic indicators. This month, as interest rates remain elevated and economic uncertainty persists, we addressed how both conventional and AI-based modeling techniques are shaping decision-making processes across agency, non-QM, and ARM products.

Here’s a quick recap in case you missed it.

(Click here to listen to the entire 30-minute recording, or continue reading for a summary.)

Model Performance: Prepayment Dynamics in Focus

RiskSpan’s prepayment model continues to perform well based on benchmarking against actuals across coupon stacks. The team noted:

  • Speeds in higher coupons have slowed relative to expectations, in line with broader refinancing trends as mortgage rates remain high.
  • RiskSpan’s Non-QM Prepayment Model (v3.11) shows strong back-testing performance. While most vintages perform as expected, the 2022 vintage diverged, potentially due to ambiguous underwriting guidelines in QM loans that may have led to adverse selection in the Non-QM space. One possible reason is that this reflects borrower composition differences not captured by traditional metrics.

New ARM Model Launch

An enhanced ARM Prepayment Model (v3.8) is now live in production. It exhibits refined sensitivity to rate shocks and aims to provide improved accuracy for adjustable-rate portfolios in today’s volatile environment.

Claude the Research Assistant: AI in Action

One of the highlights of the call was a deep dive into how we are testing Claude (Anthropic’s well-known LLM) as a mortgage research assistant.

Using a dataset from RiskSpan’s Snowflake instance, Claude orchestrated an end-to-end analytical workflow, including:

  • Retrieving and aggregating partially pre-aggregated loan-level data
  • Generating Python code for analysis and visualization
  • Annotating charts and analyzing prepayment trends

Key Insights from Claude’s Analysis

Claude surfaced several noteworthy trends:

  • FICO Score Sensitivity: Higher credit score bands (>750) showed dramatically higher prepayment rates than lower bands (<650), highlighting the refinancing advantage for more creditworthy borrowers.
  • Loan Size Effect: A positive correlation (0.22) between loan size and prepayment rates suggests that larger loan holders are more motivated to refinance.
  • Mortgage Vintage: Newer vintages (especially 2015–2016) demonstrated greater prepayment sensitivity, likely due to looser underwriting and seasoning effects.
  • Interest Rate Sensitivity: Claude captured the sharp inverse relationship between rates and prepayment, particularly the COVID-era spike and the post-2022 slowdown.

Claude correctly reasoned with the provided data but could not identify some features (like “Spread at Origination”). This raises interesting questions about LLMs’ capacity to reason beyond their training corpus.

Market Outlook: Economic Signals Turning Cautionary

The macro backdrop continues to weigh on securitization and borrower behavior. Highlights from July’s indicators:

  • Mortgage Rates: Remain above 6.5%, with little sign of easing before the Fed’s expected first rate cut in September.
  • Fed Funds Rate: Currently 4.25–4.50%, with year-end projections settling around 3.75–4.00%.
  • Home Prices: Showing stability with little YoY movement in the Case-Shiller Index.
  • Labor and Inflation: Both unemployment and PCE inflation measures remain steady, but signs of economic headwinds are beginning to appear.

On the Horizon

  • RiskSpan’s new credit model (v7), which includes a new delinquency transition matrix, is on track for release by the end of the month.
  • Continued enhancements are being made to the Platform, including new prepayment and performance visualizations for private credit and agency MBS sectors.

Contact us to learn more.

June 2025 Models & Markets Update – Predictive Power Amid Economic Uncertainty

Register here for next month’s call: Thursday, July 17th, 2025, 1 p.m.

Each month, we host a Models & Markets call to offer our insights into recent model performance, emerging credit risks, and broader economic indicators. This month, we showcased our responsiveness to shifting macroeconomic dynamics and introduced new transparency elements (i.e., back-testing tools) to our prepayment and credit modeling.

Click here to listen to the entire 23-minute recording, or continue reading for a summary.

Agency Prepay Model: Back-testing and Enhanced Control

We are launching a new loan-level prepayment back-testing tool using nearly all agency loans (FN/FH/GN) aged 10 years or less. The tool runs every month through our models with historical home prices and interest rates. Based on this data, we have an interactive dashboard that will allow users to drill down into model performance with far more granularity than currently possible.

Key Enhancements to Prepay Model v. 3.8

A soon to be released version of the prepay model will include:

  • User-defined slope multipliers for both Out-of-the-Money (OTM) and In-the-Money (ITM) performance, offering finer control over refinance sensitivity and turnover behavior.
  • Independent knob control across CONV 30, CONV 15, FHA, and VA loan types.

A redesigned ARM prepayment framework, derived from the fixed-rate model. The new ARM component includes:

  • A realistic payment shock element that aligns prepayment spikes with rate reset events.
  • Improved seasonality and aging ramp that reflects empirical loan behavior

These updates give users the ability to more precisely tune model responses under a variety of macroeconomic and borrower scenarios.

Credit Model: V7 and Delinquency Transitions

The delinquency transition matrix incorporated into our new Credit Model V7 provides users a more nuanced credit risk assessment. This model works in conjunction with the enhanced prepayment model to better simulate the joint dynamics of default and prepay behavior across economic cycles.

Macroeconomic Context: Rates and Risk in a Holding Pattern

We remain cautious in our outlook for the remainder of 2025 and into 2026:

The Fed Funds Rate is expected to remain elevated—currently in the 4.25–4.50% range—with the first rate cut likely in September. By year-end 2025, the market expects it to settle around 3.75–4.00%.

Mortgage rates remain stubbornly high, hovering above 6.5%, putting pressure on origination volumes and reinforcing the value of accurate prepayment modeling.

Home prices and broader macro indicators like unemployment and PCE inflation remain stable, suggesting a “wait-and-see” mode for both consumers and investors.

What’s Next: More Models, More Tools, More Insights

We continue to expand our Platform with new analytics, model documentation, and client-facing tools. Users can soon access the new back-testing report directly within the Platform, alongside these updated prepayment and credit models. These developments reflect our commitment to model transparency, data-driven innovation, and practical tools for real-time market adaptation.

Contact us to learn more.

Preparing For Impact: How Will Non-QM Prepay Speeds React to Lower Rates?

In a recent post, we addressed some of the less obvious ways in which a lower interest rate environment is likely to impact an agency universe with such a large volume of loans that are still out-of-the-money to refinance. In this post, we turn our attention to non-QM loans, whose unique characteristics mean they will likely feel the coming rate cuts differently.

Understanding the Distinctive Prepayment Dynamics of Non-QM Loans

Non-QM loans cater to borrowers who do not meet the stringent criteria of traditional agency loans, often due to factors like non-standard income documentation, credit issues, or investment property financing. Non-QM loans generally carry higher interest rates, and, unlike their agency counterparts, many have prepayment penalties designed to protect lenders from early payoff risk. Non-QM loans are also more likely than agency loans to involve investment properties – and thus, the underlying mortgages are not subject to the same “ability to repay” constraints that apply to agency/QM loans.

All these factors play a role in forecasting prepay speeds.

As rates decline, the incentive for some non-QM borrowers to refinance should increase, but several unique factors will shape the extent to which borrowers respond to this incentive:

  1. Prepayment Penalties: Many non-QM loans, especially those structured as Debt Service Coverage Ratio (DSCR) loans for investment properties, include prepayment penalties that can deter refinancing despite a favorable rate environment. These penalties vary widely, from a fixed percentage over a set period to declining penalties over time. The economic calculus for borrowers will hinge on whether the potential savings from refinancing outweigh these penalties
  2. Diverse Loan Structures: The non-QM market includes a variety of loan products, such as 40-year terms, hybrid ARMs and loans with interest-only periods, reminiscent of the pre-2008 lending landscape. This diversity means that not all non-QM loans will see the same incentive to refinance and the slope of the mortgage curve will matter. For example, loans with higher rates are likely to exhibit a stronger refinance response, particularly as the shape of the mortgage rate curve plays a significant role, with hybrid ARMs resetting off short-term rates and 30-year fixed-rate mortgages being influenced by movements in the 10-year Treasury yield
  3. Interest Rate Spread Compression: Historically, the spread between non-QM and agency mortgage rates has varied significantly, ranging from 100 to 300 basis points. A narrowing of this spread, driven by falling rates, could heighten the refinance incentive for non-QM borrowers, leading to faster prepayment speeds. However, the extent of this spread compression is uncertain and will depend on broader market dynamics. Souring economic conditions, for example, would likely contribute to a widening of spreads.

Key Factors Influencing Non-QM Prepayment Speeds

Loan Characteristics and Documentation Types

Non-QM loans can vary significantly by documentation type, such as full documentation, bank statements, or DSCR. Historically, as illustrated in the following chart, full documentation loans have shown faster prepayment speeds, because these borrowers are closer to qualifying for agency refinancing options as rates drop.

S-Curves by Doc Type (Full vs. Alt. vs. Bank Statement vs. DSCR)

Unlike agency mortgages, which include a substantial volume of loans originated at much lower rates, the non-QM market predominantly consists of loans originated in the past few years when rates were already elevated. As a result, a larger portion of non-QM loans is closer to being “in the money” for refinancing. This distinction suggests that the non-QM sector may see a more pronounced increase in prepayment activity compared to agency loans, where the lock-in effect remains stronger.

S-Curve (line) vs UPB (bars) by Refi Incentive

Economic Sensitivity to Rate Moves

For many non-QM borrowers, the primary barrier to agency loan qualification—whether credit score, income documentation, or property type—remains static despite lower rates. Thus, while a rate cut could improve the appeal of refinancing into another non-QM product, it might not significantly shift these borrowers towards agency loans. However, as noted, those closer to the threshold of agency eligibility could still be enticed to refinance if the rate spread and penalty structures align favorably.

Conclusion

The coming interest rate cuts are poised to influence the non-QM market in unique ways, with prepayment speeds likely to increase as borrowers seek to capitalize on lower rates. However, the interplay of rate spreads, prepayment penalties, and diverse loan structures will create a complex landscape where not all non-QM loans will behave uniformly. For lenders and investors, understanding these nuances is crucial to accurately forecasting prepayment risk and managing portfolios in a changing rate environment.

As the market evolves, ongoing analysis and model updates will be essential to capturing the shifting dynamics within the non-QM space, ensuring that investors and traders are well-prepared for the impacts of the anticipated rate cuts. Contact us to learn how RiskSpan’s Edge Platform is helping a growing number of non-QM investors get loan-level insights like never before.

Is Your Prepay Analysis Ready for the Rate Cut?

The forthcoming Federal Reserve interest rate cuts loom large in minds of mortgage traders and originators. The only remaining question is by how much rates will be cut. As the economy cools and unemployment rises, recent remarks by the Fed Chair have made the expectation of rate cuts essentially universal, with the market quickly repricing to a 50bp ease in September. This anticipated move by the Fed is already influencing mortgage rates, which have already experienced a notable decline.

Understanding the Lock-in Effect

One of the key factors influencing prepayments in the current environment is the lock-in effect, where borrowers are deterred from selling their current home due to the large difference between their current mortgage rate and prevailing market rates (which they would incur when purchasing their next home). As rates decrease, the gap narrows, reducing the lock-in effect and freeing more borrowers to sell and move.

As Chart 1 illustrates, a significant share of borrowers continues to hold mortgages between 2 and 3 percent. These borrowers clearly still have no incentive to refinance. But historical data suggests that the sizeable lock-in effect, which is currently depressing turnover, diminishes as the magnitude of their out-of-the-moneyness comes down. In other words, even a 100-basis point reduction can significantly increase housing turnover, as borrowers who were previously 300 basis points out of the money move to 200 basis points, making selling their old home and buying a new one, despite the higher interest rate, more palatable.

CHART 1: Distribution of Note Rates for 30-Year Conventional Mortgages: July 2024

Current Market Dynamics

Recent data from Mortgage News Daily indicates that mortgage rates have dropped over the past four weeks from around 6.8% to nearly 6.4%. This decrease is expected to continue, potentially bringing rates below 6% by the end of the year. This will likely have a profound impact on mortgage prepayments, particularly in the Agency MBS market.

Most outstanding mortgages, particularly those in Fannie and Freddie securities, currently have low prepayment speeds, with many loans sitting at 2% to 3% coupons. While a drop in mortgage rates to 6% (or lower) will still leave most of these mortgages out of the money for traditional rate-and-term refinances, it may bring a growing number of them into play for cash-out refinances, given significant home price appreciation and equity buildup over last 4 years. It will also loosen the grip of the lock-in effect for a growing number of homeowners currently paying below-market interest rates.

Implications for Prepayment Speeds

Factoring in the potential increase in turnover and cash-out refis, the impact of rate cuts on prepayment speeds could be substantial. For instance, with a 100-bp drop in rates, loans that are deeply out of the money could see their prepayment speeds increase by 1 to 2 CPR based on the turnover effect alone. Loans that are just at the money or slightly out of the money will see a more pronounced effect, with prepayment speeds potentially doubling. Chart 2, below, illustrates both the huge volume of loans deep out of the money to refinance as well as the small (but significant) uptick in CPR that a 100-bp shift in interest rates can have on CPR even for loans as much as 300 bps out of the money.

CHART 2: CPR by Refinance Incentive (dotted line reflects UPB of each bucket)

Historical data suggests that if mortgage rates move to 6.4%, the volume of loans moving into the money to refinance could increase up to eightfold — from $39 billion to $247 billion (see chart 3, below.) This surge in refinance activity will significantly influence prepays — impacting both turnover and refi volumes.

CHART 3: Volume and CPR by Coupon (dotted line reflects UPB of each bucket)

The Broader Housing Market

Beyond prepayments, the broader housing market may also feel the effects of rate cuts, but perhaps in a nuanced way. A reduction in rates generally improves affordability, potentially sustaining or even increasing home prices despite the increased supply from unlocked homes. However, this dynamic is complex. While lower rates make homes more affordable, the release of previously locked-in homes could counterintuitively depress home prices due to increased supply. With housing affordability at multi-decade lows, an uptick in housing supply could swamp any effect of somewhat lower rates.

While a modest rate cut may primarily boost turnover, a more significant cut could trigger a wave of refinancing. Additionally, cash-out refinances may become more attractive, offering a cheaper alternative to HELOCs and other more expensive options.

Conclusion

The forthcoming Fed interest rate cuts are poised to have a significant impact on mortgage prepayments. As rates decline, the lock-in effect will ease, encouraging more refinancing and increasing prepayment speeds. The broader housing market will also feel the effects, with potential implications for home prices and overall market dynamics. Monitoring these trends closely will be crucial for market participants, particularly those in the agency MBS market, as they navigate the changing landscape.

Contact us to staying informed and prepared and learn more about how RiskSpan can help you make strategic decisions that align with evolving market conditions.

What Do 2024 Origination Trends Mean for MSRs?

While mortgage rates remain stubbornly high by recent historical standards, accurately forecasting MSR performance and valuations requires a thoughtful evaluation of loan characteristics that go beyond the standard “refi incentive” measure.

As we pointed out in 2023, these characteristics are particularly important when it comes to predicting involuntary prepayments.

This post updates our mortgage origination trends for the first quarter of 2024 and takes a look at what they could be telling us.

Average credit scores, which were markedly higher than normal during the pandemic years, have returned and stayed near the 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.

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Consequently, in 2023 and 2024, 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, continues to trend 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.

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GenAI Applications for Loans and Mapping Data

RiskSpan is actively furthering the advancement of several GenAI applications aimed at transforming how mortgage loan and private credit investors work and maximizing their efficiency and performance. They include:

1. Tape-Cracking 3.0: Making RiskSpan’s Smart Mapper Even Smarter

RiskSpan’s Edge Platform currently uses machine learning techniques as part of its Smart Mapper ETL Tool. When a new portfolio is loaded in a new format, the fuzzy logic that powers the Platform’s recommended mappings gets continually refined based on user activity.

In the coming months, the Platform’s existing ML-driven ETL process will be further refined to leverage the latest GenAI technology.

GenAI lends additional context to the automated mapping process by incorporating an understanding not only of the data in an individual column, but also of surrounding data as well as learned characteristics of the asset class in question. The resulting evolution from simply trying to ensure the headers match up a more holistic understanding of what the data actually is and the meaning it seeks to convey will be a game changer for downstream analysts seeking to make reliable data-driven investment decisions.

RiskSpan made several updates in 2023 to help users automate the end-to-end workflow for loan valuation and surveillance. AI-based data loading combined with the Platform’s loan risk assumptions and flexible data model will enable users to obtain valuation and risk metrics simply by dragging and dropping a loan file into the application.

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2. Modeling Private Credit Transactions

Many financial institutions and legal advisors still spend an extraordinary amount of time reading and extracting relevant information from legal documents that accompany structured private credit transactions.

RiskSpan has partnered with clients to develop a solution to extract key terms from private credit and funding transactions. Trained multimodal AI models are further extended to generate executable code valuations. This code will be fully integrated into RiskSpan’s risk and pricing platform.

The application solves a heretofore intractable problem in which the information necessary to generate accurate cash flows for private credit transactions is spread across multiple documents (a frequent occurrence when terms for individual classes can only be obtained from deal amendments).

Execution code for cash flow generation and valuation utilizes RiskSpan’s validated analytics routines, such as day count handling, payment calculations, discounting, etc.

3. “Insight Support”

Tech support is one of today’s most widely known (and widely experienced) GenAI use cases. Seemingly all-knowing chatbots immediately answer users’ questions, sparing them the inconvenience of having to wait for the next available human agent. Like every other company, RiskSpan is enhancing its traditional tech support processes with GenAI to answer questions faster and and embed user-facing AI help within the Platform itself. But RiskSpan is taking things a step further by also exploring how GenAI can upend and augment its clients’ workflows.

RiskSpan refers to this workflow augmentation as “Insight Support.”

With Insight Support, GenAI evaluates an individual user’s data, dynamically serves up key insights, and automatically completes routine analysis steps without prompting. The resulting application can understand an individual user’s data and recognize what is most important to identify and highlight as part of a loan data analysis workflow.

Insight Support, for example, can leverage insights obtained by the AI-driven “Smarter Mapping” process to identify what specific type of collateral reporting is necessary. It can produce reports that highlight outliers, recognize the typical analytical/valuation run settings a user would want to apply, and then execute the analytical run and summarize the results in management-ready reporting. All in the name of shortening the analysis time needed to evaluate new investment opportunities.

Conclusion

Considered collectively, these three applications are building toward having RiskSpan’s SaaS platform function as a “virtual junior analyst” capable of handling much of the tedious work involved in analyzing loan and structured product investments and freeing up human analysts for higher-order tasks and decision making.

GenAI is the future of data and analytics and is therefore the future of RiskSpan’s Edge Platform. By revolutionizing the way data is analyzed, AI-created and -validated models, dashboards, and sorted data are already allowing experts to redirect their attention away from time-consuming data wrangling tasks and toward more strategic critical thinking. The more complete adoption of fully optimized AI solutions throughout the industry, made possible by a rising generation of “AI-native” data scientists will only accelerate this phenomenon.

RiskSpan’s commitment to pushing the boundaries of innovation in the Loan and Structured Product Space is underscored by its strategic approach to GenAI. While acknowledging the challenges posed by GenAI, RiskSpan remains poised for the future, leveraging its expertise to navigate the evolving landscape. As the industry anticipates the promised benefits of GenAI, RiskSpan’s vision and applications stand as a testament to its role as a thought leader in shaping the future of data analytics.

Stay tuned for more updates on RiskSpan’s innovative solutions, as we continue to lead the way in harnessing the power of GenAI for the benefit of our clients and the industry at large.

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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.

FICO

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

LTV

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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.

DTI

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.

WOLS

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.

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Edge: Zombie Banks

At the market highs, banks gorged themselves on assets, lending and loading their balance sheets in an era of cheap money and robust valuations. As asset prices drop, these same companies find their balance sheets functionally impaired and in some cases insolvent. They are able to stay alive with substantial help from the central bank but require ongoing support. This support and an unhealthy balance sheet preclude them from fulfilling their role in the economy.

We are describing, of course, the situation in Japan in the late 1980s and early 1990s, when banks lent freely, and companies purchased both real estate and equity at the market highs. When the central bank tightened monetary policy and the stock market tanked, many firms became distressed and had to rely on support from the central bank to stay afloat. But with sclerotic balance sheets, they were unable to thrive, leading to the “lost decade” (or two or three) of anemic growth.

While there are substantial parallels between the U.S. today and Japan of three decades ago, there are differences as well. Firstly, the U.S. has a dynamic non-bank sector that can fill typical roles of lending and financial intermediation. And second, much of the bank impairment comes from Agency MBS, which slowly, but surely, will prepay and relieve pressure on their HTM assets.

Chart
Source: The Wall Street Journal

How fast will these passthroughs pay off? It will vary greatly from bank to bank and depends on their mix of passthroughs and their loan rates relative to current market rates, what MBS traders call “refi incentive” or “moniness.” It is helpful to remember that incentive also matters to housing turnover, which is a form of mortgage prepayment. For example, a borrower with a note rate that is 100bp below prevailing rates is much more likely to move to a new house than a borrower with a note rate that is 200bp out of the money, a trait that mortgage practitioners call “lock-in”.

Chart
Source: RiskSpan’s Edge Platform

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As a proxy for the aggregate bank’s balance sheet, we look at the universe of conventional and GNMA passthroughs and remove the MBS held by the Federal Reserve.

1

The Fed’s most substantial purchases flowed from their balance sheet expansion during COVID, when mortgage rates were at all-time lows. Consequently, the Fed owns a skew of the MBS market. Two-thirds of the Fed’s position of 30yr MBS have a note rate of 3.25% or lower. In contrast, the market ex Fed has just under 50% of the same note rates.

Chart
Source: RiskSpan’s Edge Platform

From here, we can estimate prepayments on the remaining universe. Prepay estimates from dealers and analytics providers like RiskSpan vary, but generally fall in the 4 to 6 CPR range for out-of-the-money coupons. This, coupled with scheduled principal amortization of roughly 2-3% per annum means that for this level in rates, runoff in HTM MBS should occur around 8% per annum — slow, but not zero. After five years, approximately 1/3 of the MBS should pay off. Naturally, the pace of runoff can change as both mortgage rates and home sales change.

While the current crisis contains echoes of the Japanese zombie bank crisis of the 1990s, there are notable differences. U.S. banks may be hamstrung over the next few years, with reduced capacity to make new loans as MBS in their HTM balance sheets run off over the next few years. But they will run off — slowly but surely.

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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.

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

AssetLiabilityRpt

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.

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