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Articles Tagged with: ESG

Striking a Proper Balance: ESG for Structured Finance

The securitization market continues to wrestle with the myriad of approaches and lack of standards in identifying and reporting ESG factors in transactions and asset classes. But much needed guidance is on the way as industry leaders work toward a consensus on the best way to report ESG for structured finance.  

RiskSpan gathered with other key industry players tackling these challenges at this month’s third annual Structured Finance Association ESG symposium in New York City. The event identified a number of significant strides taken toward shaping an industry-standard ESG framework and guidelines.  

Robust and engaging discussions across a variety of topics illustrated the critical need for a thoughtful approach to framework development. We observed a broad consensus around the notion that market acceptance would require any solution to be data supported and fully transparent. 

Much of the discussion revolved around three recurring themes: Finding a workable balance between the institutional desire for portfolio-specific measures based on raw data and the market need for a standardized scoring mechanism that everybody understands, maintaining data privacy, and assessing tradeoffs between the societal benefits of ESG investing and the added risk it can pose to a portfolio. 

Striking the Right Balance: Institution-Specific Measures vs. Industry-Standard Asset Scoring 

When it comes to disclosure and reporting, one point on a spectrum does not fit all. Investors and asset managers vary in their ultimate reporting needs and approach to assessing ESG and impact investing. On the one hand, having raw data to apply their own analysis or specific standards can be more worthwhile to individual institutions. On the other, having well defined standards or third-party ESG scoring systems for assets provides greater certainty and understanding to the market as a whole.  

Both approaches have value.

Everyone wants access to data and control over how they view the assets in their portfolio. But the need for guidance on what ESG impacts are material and relevant to structured finance remains prominent. Scores, labels, methodologies, and standards can give investors assurance a security contributes to meeting their ESG goals. Investors want to know where their money is going and if it is meaningful.

Methodologies also have to be explainable. Though there was agreement that labeled transactions are not always necessary (or achievable), integration of ESG factors in the decision process is. Reporting systems will need to link underlying collateral to external data sources to calculate key metrics required by a framework while giving users the ability to drill down to meet specific and granular analytical needs.    

Data Privacy

Detailed analysis of underlying asset data, however, highlights a second key issue: the tradeoff between transparency and privacy, particularly for consumer-related assets. Fiduciary and regulatory responsibility to protect disclosure of non-public personally identifiable information limits investor ability to access loan-level data.

While property addresses provide the greatest insight to climate risk and other environmental factors, concerns persist over methods that allow data providers to triangulate and match data from various sources to identify addresses. This in turn makes it possible to link sensitive credit information to specific borrowers.

The responsibility to summarize and disclose metrics required by the framework falls to issuers. The largest residential issuers already appreciate this burden. These issuers have expressed a desire to solve these issues and are actively looking at what they can do to help the market without sacrificing privacy. Data providers, reporting systems, and users will all need to consider the guardrails needed to adhere to source data terms of use.   

Assessing Impact versus Risk

Another theme arising in nearly all discussions centered on assessing ESG investment decisions from the two sometimes competing dimensions of impact and risk and considering whether tradeoffs are needed to meet a wide variety of investment goals. Knowing the impact the investment is making—such as funding affordable housing or the reduction of greenhouse gas emissions—is fundamental to asset selection or understanding the overall ESG position.

But what risks/costs does the investment create for the portfolio? What is the likely influence on performance?

The credit aspect of a deal is distinct from its ESG impact. For example, a CMBS may be socially positive but rent regulation can create thin margins. Ideally, all would like to maximize positive impact but not at the cost of performance, a strategy that may be contributing now to an erosion in greeniums. Disclosures and reporting capabilities should be able to support investment analyses on these dimensions.  

A disclosure framework vetted and aligned by industry stakeholders, combined with robust reporting and analytics and access to as much underlying data as possible, will give investors and asset managers certainty as well as flexibility to meet their ESG goals.   

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Why Climate Risk Matters for Mortgage Loan & MSR Investors 

The time has come for mortgage investors to start paying attention to climate risk.

Until recently, mortgage loan and MSR investors felt that they were largely insulated from climate risk. Notwithstanding the inherent risk natural hazard events pose to housing and the anticipated increased frequency of these events due to climate change, it seemed safe to assume that property insurers and other parties in higher loss position were bearing those risks. 

In reality, these risks are often underinsured. And even in cases where property insurance is adequate, the fallout has the potential to hit investor cash flows in a variety of ways. Acute climate events like hurricanes create short-term delinquency and prepayment spikes in affected areas. Chronic risks such as sea level rise and increased wildfire risk can depress housing values in areas most susceptible to these events. Potential impacts to property insurance costs, utility costs (water and electricity in areas prone to excessive heat and drought, for example) and property taxes used to fund climate-mitigating infrastructure projects all contribute to uncertainty in loan and MSR modeling. 

Moreover, dismissing climate risk “because we are in fourth loss position” should be antithetical to any investor claiming to espouse ESG principles. After all, consider who is almost always in the first loan position – the borrower. Any mortgage investment strategy purporting to be ESG friendly must necessarily take borrower welfare into account. Dismissing climate risk because borrowers will bear most of the impact is hardly a socially responsible mindset. This is particularly true when a disproportionate number of borrowers prone to natural hazard risk are disadvantaged to begin with. 

Hazard and flood insurers typically occupy the loss positions between borrowers and investors. Few tears are shed when insurers absorb losses. But society at large ultimately pays the price when losses invariably lead to higher premiums for everybody.    

Evaluating Climate Exposure

For these and other reasons, natural hazards pose a systemic risk to the entire housing system. For mortgage loan and MSR investors, it raises a host of questions. Among them: 

  1. What percentage of the loans in my portfolio are susceptible to flood risk but uninsured because flood maps are out of date? 
  2. How geographically concentrated is my portfolio? What percentage of my portfolio is at risk of being adversely impacted by just one or two extreme events? 
  3. What would the true valuation of my servicing portfolio be if climate risk were factored into the modeling?  
  4. What will the regulatory landscape look like in coming years? To what extent will I be required to disclose the extent to which my portfolio is exposed to climate risk? Will I even know how to compute it, and if so, what will it mean for my balance sheet? 

 

Incorporating Climate Data into Investment Decision Making

Forward-thinking mortgage servicers are at the forefront of efforts to get their arms around the necessary data and analytics. Once servicers have acquired a portfolio, they assess and triage their loans to identify which properties are at greatest risk. Servicers also contemplate how to work with borrowers to mitigate their risk.  

For investors seeking to purchase MSR portfolios, climate assessment is making its way into the due diligence process. This helps would-be investors ensure that they are not falling victim to adverse selection. As investors increasingly do this, climate assessment will eventually make its way further upstream, into appraisal and underwriting processes. 

Reliably modeling climate risk first requires getting a handle on how frequently natural hazard events are likely to occur and how severe they are likely to be. 

In a recent virtual industrial roundtable co-hosted by RiskSpan and Housing Finance Strategies, representatives of Freddie Mac, Mr. Cooper, and Verisk Analytics (a leading data and analytics firm that models a wide range of natural and man-made perils) gathered to discuss why understanding climate risk should be top of mind for mortgage investors and introduced a framework for approaching it. 

WATCH THE ENTIRE ROUNDTABLE

Building the Framework

The framework begins by identifying the specific hazards relevant to individual properties, building simulated catalogs of thousands of years worth of simulated events, computing likely events simulating damage based on property construction and calculating likely losses. These forecasted property losses are then factored into mortgage performance scenarios and used to model default risk, prepayment speeds and home price impacts. 

 

Responsibility to Borrowers

One member of the panel, Kurt Johnson, CRO of mega-servicer Mr. Cooper, spoke specifically of the operational complexities presented by climate risk. He cited as one example the need to speak daily with borrowers as catastrophic events are increasingly impacting borrowers in ways for which they were not adequately prepared. He also referred to the increasing number of borrowers incurring flood damage in areas that do not require flood insurance and spoke to how critical it is for servicers to know how many of their borrowers are in a similar position.

Johnson likened the concept of credit risk layering to climate risk exposure. The risk of one event happening on the heels of another event can cause the second event to be more devastating than it would have been had it occurred in a vacuum. As an example, he mentioned how the spike in delinquencies at the beginning of the covid pandemic was twice as large among borrowers who had just recovered from Hurricane Harvey 15 months earlier than it was among borrowers who had not been affected by the storm. He spoke of the responsibility he feels as a servicer to educate borrowers about what they can do to protect their properties in adverse scenarios.


Webinar Recording: How Much Will That MSR Portfolio Really Cost You?

Recorded: June 8th | 1:00 p.m. ET

Accurately valuing a mortgage servicing rights portfolio requires accurately projecting MSR cash flows. And accurately projecting MSR cash flows requires a reliable forecast of servicing costs. Trouble is, servicing costs vary extensively from loan to loan. While the marginal cost of servicing a loan that always pays on time is next to nothing, seriously delinquent loans can easily cost hundreds, if not thousands, of dollars per year.

The best way to account for this is to forecast and assign servicing costs at the loan level – a once infeasible concept that cloud-native technology has now brought within reach. Our panelists present a novel, granular approach to servicing cost analytics and how to get to a truly loan-by-loan MSR valuation (without resorting to rep lines).

 

 

 

Featured Speakers

Venkat Mullur

SVP, Capital Markets, Ocwen

Paul Gross

Senior Quantitative Analyst, New Residential Investment Corp.

Dan Fleishman

Managing Director, RiskSpan

Joe Makepeace

Director, RiskSpan


Industry Virtual Roundtable: The Intersection of Climate Risk Management with Mortgage Loan & MSR Investing

April 14th | 2:00-3:15 p.m. ET

With both the public and private sectors increasingly making climate risk management a priority, attention in our industry is turning to what it means for mortgage loan and MSR investors.

Industry experts join RiskSpan and Housing Finance Strategies for a roundtable event where they engage in a discussion on the latest approaches and technology for mitigating climate risk management in mortgage portfolios.

The loan-level cash flows discussed in this webinar were generated using RiskSpan’s Edge Platform.

 

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Agenda (all times Eastern)

2:00-2:05 pm | WELCOME AND PROGRAM OVERVIEW 

Faith Schwartz, Founder & CEO, Housing Finance Strategies

2:05-2:20 pm | CLIMATE RISK’S IMPACT ON MORTGAGE FINANCE AND TOOLS TO MANAGE RISK

Janet Jozwik, Senior Managing Director and Head of Climate Risk, RiskSpan
Dan Raizman, Global Resilience Manager, Verisk Analytics

2:20-3:00 pm | PANEL DISCUSSION: CLIMATE RISK IN HOUSING FINANCE—RISK MANAGEMENT AND REGULATORY PERSPECTIVES

Faith Schwartz, Moderator
Mark Hanson, SVP, Freddie Mac
Kurt Johnson, CRO, Mr. Cooper
Sean Becketti, former Freddie Mac
Bernadette Kogler, CEO, RiskSpan

3:00-3:15 pm | QUESTIONS AND DISCUSSION OF POLLING RESULTS


Incorporating Climate Risk into ERM: A Mortgage Risk Manager’s Guide

Climate risk is becoming impossible to ignore in the mortgage space.

President Biden’s May 2021 Executive Order makes clear that quantifying and mitigating climate risk will be a priority for the federal government’s housing finance agencies (HUD, FHFA, FHA, VA). It’s just a matter of time before the increased emphasis on this risk makes its way to others in the eco-system (Government-Sponsored Enterprises, Servicers, Lenders, Investors). The SEC will be coming out with climate-related requirements for the securities markets. In early 2021, a proposed rule amendment “to enhance registrant disclosures regarding issuers’ climate-related risks and opportunities” was added to their regulatory agenda with an expected release in 2022. Other agencies, including the OCC, are issuing draft guidance, or requesting feedback on climate-related risks.  Boards are taking notice, and, if you haven’t heard from yours on the topic, you will soon.

But where can you start?

Bear in mind there are a couple of critical questions you need to think about regarding your organizational response to climate risk. Most executives and boards are now familiar with the concepts of physical and transition risks of climate change, but how will these risks manifest in your organization through business, asset, regulatory, legal, and reputation risk? How will these risks impact residential housing prices, attractiveness of communities, building codes, insurance costs, and zoning laws, and the valuation of mortgages and other financial instruments that are a derivative value of residential properties and the economic strength of communities? What will be the response from homeowners, insurers, builders, investors, and public policy of local, state, and federal governments that could impact asset valuation? It’s not an easy problem to solve!

A growing body of academic literature has developed around home price dynamics, mortgage performance, and the general perception of climate risk as a market influencer. Published findings focus primarily on the effect of physical risks on mortgage performance and home prices. A recurring theme in the literature is that while individual climate events can be highly disruptive on local real estate and mortgage markets, values tend to rebound quickly (Bin and Landry, 2013) with the specter of another such event not appearing to weigh down prices significantly. On top of that, short-run effects of supply issues and competitive effects, such as attractive housing features and locations, complicate housing price dynamics. People still want to live on coasts and rivers, in hot and dry desert locations, and in earthquake- and wildfire-exposed areas that are prone to natural catastrophes and increasing impacts from climate change. So attractive are these areas, the marginal effect of a home being in an area that is projected to be underwater may actually increase home prices, without controlling for distance to the shore. This may be a consequence of the premium value associated with waterfront views (Baldauf et al., 2020). But just because impacts so far have been minimal, does not mean future impacts will follow the same trend.

While prices have rebounded quickly after events in the past and housing prices still command a premium for waterfront views, there is evidence that buyers are starting to discount values for coastal properties exposed to sea level rise (Bernstein et al. 2018).  In the future, where there is increasing chances that climate change will cause permanent change to usable land due to any number of hazards without effective resilience improvements, there may be a smaller or no rebound in prices leaving the holders of exposed real and financial assets with a loss. Or, conversely, the value of waterfront homes may even begin to experience a rapid decline if mortgage holders begin to suspect that the value (and usability) of their properties could decline substantially over the life of their mortgages.

Further discussion of the academic literature and a bibliography can be found in the note at the end of this article.

Significant uncertainty exists about how climate change will occur, over what timeframe these changes will occur, how all levels of government will intervene or react to chronic risks like sea level rise, and how households, companies, and financial markets will respond to various signals that will create movements in prices, demographics, and economic activity even before climate risk manifests. What is known is that global temperatures will continue to warm over the next 50 years regardless of the actions people and governments take, and the impacts of that warming will accumulate and become more severe and frequent over time, requiring a definitive action plan for dealing with this issue.


Little differentiation in scenarios in 20 years. Risks will manifest differently over different timeframes.


 

The standards by which organizations will be expected to deal with climate risk will evolve as the climate continues to change and more capabilities are developed to address these issues. An important first step is the need to contextualize these risks with respect to other risks to your business. One immediate need is to address near-term board and regulatory reporting requirements, as well as voluntary public disclosure, as pressure by stakeholders to understand what actions are being taken by companies to address climate change builds.

There is no easy answer, but we offer a way to bring the issue into focus and plan for a thoughtful response as the risks and standards evolve. We are tackling the problem by understanding the risks the organization faces and evaluate those through scenarios and sensitivity analysis. We recommend against over-engineering a solution; instead, design a framework that allows you to monitor and track risk over time. We propose a practical approach, one that’s incrementally phased and integrates risk management through time, enabling pause, adjustment, assessment, and changes in course as needed.


Suggested Approach for Incorporating Climate Risk into ERM


We present five key components to consider when incorporating a climate and natural hazard risk dimension into an existing ERM framework.

Evaluate the Risk Landscape

As a starting point, evaluating the risk landscape entails identifying which climate-related risks have the potential to affect investment return. Climate-related financial risks can be categorized into physical and transition risks.

Physical risks can be acute or chronic. Acute physical risks include extreme events like hurricane, floods, and wildfire. Chronic physical risks refer to a property’s exposure to sea level rise, excessive heat, or drought, for example. Investors who understand these terms and scenarios – including how uncertainty is modeled, emphasizing the directional relationship and order of magnitude of changes rather than exact quantification — are at a competitive advantage.

Transition risks and the secondary effects of physical risks can arise from changes in policy, legal, technology, or market actions that come about from a movement to reduce carbon emissions.

Some important and guiding questions for both physical and transition risk include:

What are the acute and chronic physical hazard types that pose a financial risk?

How will these risks manifest as potential financial loss to mortgage investments?

How material are the possible losses?

How might these risks evolve over time?

Note that climate science continues to evolve, especially as it relates to longer-term impacts, and there is limited historical data to understand how the effects of climate change will trickle into the housing market. Risk assessments must be based on a range of scenarios and include plausible narratives that are not bound by historical observations. The scenario approach applies to studying both acute and chronic physical risks, and the scenarios used in assessing acute or chronic risks may be conceptualized differently.

Select Climate-Related Risks that Impact Mortgage Finance

Visualizing the exposure of various mortgage stakeholders to different forms of climate risk can be accomplished using a table like the following.


Figure


Establish Risk Measurement Approach

Quantifying the financial impact of physical and transition risk is critical to evaluating a portfolio’s potential exposure. From a mortgage loan perspective, loan-level and portfolio-level analyses provide both standalone and marginal views of risk.

Translating hazard risk into a view of financial loss on a mortgage instrument can be accomplished within traditional mortgage model estimations using 1) a combination of property-specific damage estimates from natural hazard and climate risk models, and 2) formulated macroeconomic scenarios guided by academic research and regulatory impacts. And because chronic effects can affect how acute risks manifest, a more nuanced view of how acute risks and chronic risks relate to one another is necessary to answer questions about financial risk.

Mortgage investors can better understand natural hazard risk measures by taking a page from how property insurers account for it. For example, the worst-case “tail loss” potential of a given portfolio is often put in context of the type of events that are at the tail of risk for the industry as a whole – in other words, a 1-in-100-year loss to the portfolio versus a loss to portfolio for a 1-in-100-year industry event. Extending this view to mortgages entails considering the type of events that could occur over the average life of a loan.

To address chronic and transition risk, selecting appropriate macroeconomic scenarios also provides a financial view of the possible impact on a mortgage portfolio. These scenarios may be grounded in published climate projections, asset-specific data collection, or different scenario narratives outlining how these risks could manifest locally.

Defining a Risk Appetite Framework

Inventorying the complete range of potential climate-related risks provides structure and organization around which risks have the largest or most severe impact and creates a framework for ranking them by appropriate criteria. A risk appetite and limit framework defines the type and quantity of natural catastrophe and climate change risk that an enterprise is willing to hold in relation to equity, assets, and other financial exposure measures at a selected probability of occurrence.  The operational usefulness of these frameworks are enhanced when defining the appetite and limits in reference to the risk measures the company selects in addition to straight notional values.

The loss exposure for a particular risk will drive operations differently across business lines based on risk preferences. From the viewpoint of mortgage activities, these operations include origination, servicing, structuring, and pricing. For instance, it may be undesirable to have more than $100 million of asset valuation at risk across the enterprise and apportion that limit to business units based upon the return of the asset in relation to the risk generated from business activity. In this way, the organization has a quantitative way for balancing business goals with risk management goals.

The framework can also target appropriate remediation and hedging strategies in light of the risk priorities. Selecting a remediation strategy requires risk reporting and monitoring across different lines of business and a knowledge of the cost and benefits attributed to physical and transition risks.

Incorporate Findings into Risk Governance

Entities can adapt policies, processes, and responsibilities in the existing ERM framework based on their quantified, prioritized, and articulated risk. This could come in the form of changes to stakeholder reporting from internal management committees, board, and board committees to external financial, investor, public, and regulatory reporting.

Because regulatory requirements and industry best practices are still being formed, it is important to continuously monitor these and ensure that policies align with evolving guidance.

Monitor and Manage Risk Within Risk Appetite and Limits

Implementation of an ERM framework with considerations for natural catastrophe and climate risk may appear different across different lines of businesses and risk management processes. For this reason, it is important that dashboards, reporting frameworks, and exposure control processes be designed to fit in with current reporting within individual lines of businesses.

A practical first step is to establish monitoring specifically to detect adverse selections issues—i.e., ensuring that you are not acquiring a book of business with disproportionately high levels of climate risk or one that adds risk to areas of existing exposure within your portfolio. The object is to manage the portfolio, so risk remains within the agreed appetite and limit framework.  This type of monitoring will become increasingly critical as other market participants start to incorporate climate risk into their own asset screening and pricing decisions. Firms that fail to monitor for climate risk will ultimately be the firms that bear it.

All of this ultimately comes down to identifying natural catastrophe and climate risks, quantifying them through property and loan-specific modeling and scenarios, ranking the risks along different criteria, and tailoring reporting to different operations in the enterprise with an eye for changing regulatory requirements and risk governance policies. An enterprise view is needed given climate risks correlate across multiple asset classes, and where it is determined that differences in risk tolerance are desired, the framework described provides a coherent and quantitative basis for differences.  Successfully negotiating these elements is more easily described than actually carried out, particularly in large financial institutions consisting of businesses with widely divergent risk tolerances.  But we appear to be reaching a point where further deferral is no longer an option. The time to begin planning and implementing these frameworks is now.

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Note on academic research and works referenced

Some empirical research has been conducted examining outcomes following natural hazard events, specifically their impact on mortgage loan performance. Kousky et al. (2020) show evidence that property damage from an extreme event increases short-term mortgage delinquencies and forbearance rates. This effect is mitigated by the presence of flood insurance, which enables borrowers to use insurance proceeds to pay off loans or sell damaged homes once they’ve received compensation and move away from the impacted area. A rebound effect, observed in home prices, occurs in loan performance as well. Delinquencies, while elevated just after the disaster, tend to quickly revert to pre-disaster levels (Fannie Mae, 2017). Extending beyond single-event analysis, delinquencies in hurricane-prone areas have been shown to be higher than delinquency rates in other areas, controlling for other risk factors (Rossi, 2020). The projected rise in hurricane intensity and incidence can therefore lead to higher default risk, which in turn leads to higher losses to investors in mortgage credit risk.

Studies on chronic risks like sea level rise reveal the risk to have a moderate effect on housing prices, stratified by climate “denier” and climate “believer” borrowers (Baldauf et al., 2020). All else equal, areas with owners who perceive a climate threat to their properties may demand a discount on prices. Similarly, Bernstein et al. (2018) show housing price discounts of up to 7% for counties more worried about sea level rise than unworried counties. Risk perception for climate change is subject to a number of biases (Kousky et al., 2020). As such, distortion created by these biases can contribute to inaccurate home pricing. Evidence suggests that regulatory floodplain properties are overvalued, but pricing is inconsistent. Borrowers who are well-informed and sophisticated may fully reflect flood risk information in their pricing (Hino and Burke, 2021). These effects can vary by consumer disclosure requirements as well, which lead to discussion about information gaps on climate risk.

Yet, there is notable research on the salience of events, where house prices following the occurrence of an extreme event have been shown to have persistent effects on home prices. Ortega and Taspinar (2018) show a permanent price decline in the 5 years following Hurricane Sandy for properties in flood zones, regardless of the damage experienced. While properties damaged by the hurricane showed a rebound in home prices right after the event, all properties affected by the storm converged to the same home price penalty. Eichholtz et al. (2019) primarily study commercial real estate properties in New York, with corroborating studies in Boston and Chicago, and find negative price effects from flood-risk exposure post-Hurricane Sandy due to sophisticated investors adjusting their valuations downward. Increased attention to climate change from the occurrence of extreme events may cause long-term price effects as communities begin evaluating the possible risks they face after weathering a catastrophic event.


For further reading, see:

Markus Baldauf, Lorenzo Garlappi, Constantine Yannelis, Does Climate Change Affect Real Estate Prices? Only If You Believe In It, The Review of Financial Studies, Volume 33, Issue 3, March 2020, Pages 1256–1295, https://doi.org/10.1093/rfs/hhz073

Eichholtz, Piet M. A.; Steiner, Eva; Yönder, Erkan “Where, When, and How Do Sophisticated Investors Respond to Flood Risk?,” June 2019. PDF

Bernstein, Asaf and Gustafson, Matthew and Lewis, Ryan, Disaster on the Horizon: The Price Effect of Sea Level Rise (May 4, 2018). Journal of Financial Economics (JFE), Forthcoming, Available at SSRN: https://ssrn.com/abstract=3073842 

Bin, O., & Landry, C. E. (2013). Changes in implicit flood risk premiums: Empirical evidence from the housing market. Journal of Environmental Economics and Management, 65(3), 361–376. HYPERLINK “https://protect-us.mimecast.com/s/SL58C5ylW5F05NOpXUzgQhi?domain=doi.org

Hinoa and Burke, The effect of information about climate risk on
property values (March 18, 2021). PDF

Ortega, Francesc and Taspinar, Suleyman, Rising Sea Levels and Sinking Property Values: The Effects of Hurricane Sandy on New York’s Housing Market (March 29, 2018). Available at SSRN: https://ssrn.com/abstract=3074762 or http://dx.doi.org/10.2139/ssrn.3074762

Clifford Rossi. “Assessing the impact of hurricane frequency and intensity on mortgage default risk,” June 2020. PDF

Markus Baldauf, Lorenzo Garlappi, Constantine Yannelis, Does Climate Change Affect Real Estate Prices? Only If You Believe In It, The Review of Financial Studies, Volume 33, Issue 3, March 2020, Pages 1256–1295, https://doi.org/10.1093/rfs/hhz073

Carolyn Kousky, Howard Kunreuther, Michael LaCour-Little & Susan Wachter (2020) Flood Risk and the U.S. Housing Market, Journal of Housing Research, 29:sup1, S3-S24, DOI: 10.1080/10527001.2020.1836915

Carolyn Kousky, Mark Palim & Ying Pan (2020) Flood Damage and Mortgage Credit Risk: A Case Study of Hurricane Harvey, Journal of Housing Research, 29:sup1, S86-S120, DOI: 10.1080/10527001.2020.1840131

Verisk 2021: How Current Market Conditions Could Impact U.S. Hurricane Season 2021

RiskSpan 2018: Houston Strong: Communities Recover from Hurricanes. Do Mortgages?


RiskSpan Chosen “Best Company for Diversity and Inclusion” Category Winner in WatersTechnology’s Women In Technology & Data Awards 2022 Rankings

RiskSpan Chosen “Best Company for Diversity and Inclusion” by WatersTechnology Women In Technology & Data Awards 2022


Learn More about riskspan's Dei initiatives

The award reflects RiskSpan’s major commitment to making DEI a priority and empowering employees from every background and at every level of the company to contribute to our mutual success.

Recent initiatives have included:

  • A broad expansion and formalization of a mentorship program pairing every non-management employee with a senior company leader.
  • Regular anonymous surveys designed to gauge employee perceptions of inclusion and identify opportunities for improvement.
  • Establishment of a Women’s Employee Resource Group featuring forums, dinners, and other social events.
  • Active participation in industry DEI committees and events.
  • Development of training frameworks open to all employees seeking help obtaining certifications and customized training programs.

These and related efforts all aim to create a close-knit organization by maximizing opportunities for communication among staff across the organization and creating more opportunities to get to know one another in smaller groups outside of assigned projects and teams.


Webinar: Geocoding Mortgage Data for ESG and Climate Risk Analysis

Recorded: February 16th | 1:00 p.m. ET

Geocoding remains a particularly vexing challenge for the mortgage industry. Lenders, servicers, and loan/MSR investors know the addresses of the properties securing their mortgage assets. But most data pertaining to climate and other ESG considerations is available only by matching to a census tract or latitude/longitude.

And if you have ever tried mapping addresses, you know this exercise can be a lot harder than it looks. Fortunately, a growing body of geocoding tools and techniques is emerging to make the process more manageable than ever, even with less than perfect address data.

Our panel presents a how-to guide on geocoding logic and its specific application to the mortgage space. You will learn a useful waterfall approach for linking census-tract-level, geo-specific data for climate risk and ESG to the property addresses in your portfolio.

 

Featured Speakers

Suhrud Dagli

Chief Innovation Officer, RiskSpan

Jason Huang

Manager, RiskSpan

Jason Lee

Software Engineer, RiskSpan


How Has the First “Social” RMBS Performed – And What’s So Social About It?

Now that six months have passed since Angel Oak issued AOMT 2021-2 – hailed as the first U.S. non-Agency RMBS to qualify as a social bond [1] – we can compare preliminary collateral performance to other deals. Angel Oak’s 2021-1, from the same shelf and vintage – but without the social bond distinction – provides an apt control group. To set the stage for this performance comparison, we’ll first reexamine the compositional differences – and significant overlap – between the two collateral pools. What we will show:

  • The pool compositions are highly overlapping, with marginally greater risk concentrations of self-employment and alternative documentation in the social securitization, and the same WA (weighted average) coupon
  • The social collateral has outperformed the benchmark credit-wise in the early going
  • The social deal has exhibited some lock-in, i.e., slower refinancing, providing some very preliminary evidence that the borrowers are indeed underserved, and that investors may be rewarded if the social collateral’s credit performance holds
  • However, the credit mix of the social collateral has drifted riskier – more so than the benchmark – meaning the strong early credit performance of the social deal could reverse, and ongoing surveillance is warranted

New Loans or New Label?


The Social AOMT 2021-2 Is Similar to AOMT 2021-1

Figure 1 shows AOMT 2021-1 vs. 2021-2 in the Collateral Comparison screen of Edge, RiskSpan’s data and analytics platform. Clearly, the two pools were similar at origination, with highly overlapping distributions of FICO, LTV, and DTI and many other similar metrics.

So What’s Different – And How Different Is It?

The distinguishing principle of a social bond under Angel Oak’s framework is that it provides affordable home mortgages to those who often can’t get them because they don’t qualify under the automated underwriting processes of traditional lenders because of the exceptional nature of their sources of income. [2]

Angel Oak says the specific characteristic hindering the borrowers in the AOMT 2021-2 deal is self-employment. [3] Self-employed borrowers make up 94.4% of the pool (with a median annual income of $227,803) [4], up marginally from 86.5% in the 2021-1 deal [5]. As Figure 1 shows, the proportion of low documentation by balance was up from 87.5% in 2021-1 to 97.5% in 2021-2.

Also, Figure 1 shows that 2021-2’s FICOs and LTVs are slightly worse on average with slightly more tail risk, and the cash-out proportion is slightly riskier.

Compensating marginally for 2021-2 are slightly lower ARM proportions (0 vs. 0.8% for 2021-1), lower WA. DTI, and a higher proportion of owner-occupied (90% vs. 85%), which many view as credit-positive.

In summary, RiskSpan calculates 1.83 average risk layers per loan for the social 2021-2, slightly higher than 1.78 for 2021-1.

Notably the WA coupons for the two pools are the same.


Figure 1: Edge’s Collateral Comparison Screen Showing AOMT 2021-1 (aka AOAK 2101) vs. 2021-2 (aka AOAK 2102) at OriginationSource: CoreLogic, RiskSpan


Would you like to see the tool we used to perform this analysis?

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In summary, it seems that most – though perhaps not all – of the loans that qualified for AOMT 2021-2 would have qualified for AOMT 2021-1 and other non-QM deals.

Kroll’s new issue report seems to acknowledge that what is new about 2021-2 is mostly the formal emphasis on the social benefits of the loans made, and less a change in the kinds of loans made: “While many of [Angel Oak’s] lending programs overlap meaningfully with other non-QM lender’s offerings, the actions taken by AOCA generally indicate management’s attention to ESG related matters. Specifically, AOCA’s SBF puts focus on the impact that credit availability for underserved borrowers can have.” [4]

A skeptical interpretation of the overlap between 2021-1 and the social 2021-2 collateral would be that the social claim is largely hollow. Another way of looking at it is that a financial market participant is finally taking credit for good work it has been largely doing all along. Angel Oak itself seems to take this latter view, saying, “Since 2011, AOCA has been implementing ESG principles within its non-qualified mortgage (non-QM) origination and securitization program to provide access to residential credit for underserved borrowers.” [2]

Either way, logical hypotheses would be that collateral performance will be similar between 2021-2 and 2021-1, with -2 showing (a) slightly more credit trouble and (b) slightly less able to refinance. Regarding the second hypothesis, logically it should challenge the premise that the deal serves underserved borrowers if its borrowers can refinance just as readily as others.

Early Performance of the Social Bonds


Let’s see how AOMT’s social 2021-2 has performed as benchmarked to 2021-1 during the first six and seven months, respectively, of available data.

Better Delinquency Trend Than the Benchmark

As Figure 2 shows, delinquencies opened higher for the social 2021-2 but have mostly cured. By contrast, delinquencies have trended up for 2021-1. So far, Angel Oak’s social origination is outperforming its non-social contemporary from a credit standpoint.


Figure 2: AOMT 2021-2 Delinquencies Began Higher, Have Mostly Cured; AOMT 2021-1’s Delinquencies Have Trended Up 60 day-plus delinquency share over time, AOMT 2021-2 vs AOMT 2021-1 Source: CoreLogic, RiskSpan


Significantly Better Credit Performance by the Social DSCR Investor Loans

A small slice of the deals driving outsized delinquencies in 2021-1 are the DSCR-based investor loans (Figure 3). In the social 2021-2, delinquencies among this cohort are zero. We plot the spreads at origination (SATO) of this cohort alongside delinquencies to show that the DSCR loans in 2021-2 had lower credit spreads by about 20bps. Perhaps the investor loans pooled into 2021-2 were managed to higher standards for DSCR, rent rolls or other attributes (their LTVs and ages are similar).


Figure 3: Delinquencies – and SATOs – Are Lower Among DSCR-Based Investor Loans in AOMT 2021-2 60 day-plus delinquency share and WA SATOs over time, AOMT 2021-2 vs. AOMT 2021-1, includes Detailed Doc Type = DSCR Investor Cash Flow.Source: CoreLogic, RiskSpan


Ironically, The Full Doc Loans Are the Social Deal’s Blemish

The slice of full doc loans in the social 2021-2 have a much lower WA FICO than the low doc loans in the same deal or either the low or full doc loans in 2021-1 (see the green dotted line in Figure 4). Correspondingly, these full doc loans have the highest delinquent share among the four cohorts in Figure 4 (green solid line). If this pattern holds, it highlights the viability of using tradeoffs to manage down the overall credit risk represented by loans with risky attributes.


Figure 4: AOMT 2021-2’s Full Doc Loans Are the Most Delinquent Doc Cohort from Either Deal 60 day-plus delinquency share and WA FICOs over time, AOMT 2021-2 vs. AOMT 2021-1 and Full Doc vs. Low Doc Source: CoreLogic, RiskSpan


Slower Refinances Than the Benchmark

While credit performance has been better for the social deal than we might expect, voluntary prepays so far (Figure 5) support our hypothesis that the social deal should prepay slower. Note that we plot voluntary prepays over loan age, and that all loans from this recent non-QM vintage have similar (and highly positive) refinance incentive. If the social deal’s refinances remain slower, that accomplishes two significant things: 1) it supports the claim that the social borrowers are indeed underserved; 2) if combined with sustained credit performance, it provides support in terms of financial risk and return for the price premiums that social bonds tend to command.


Figure 5: AOMT 2021-2 Is Refinancing Slower CRR over loan age, AOMT 2021-2 vs. AOMT 2021-1, July 2021-January 2022 Source: CoreLogic, RiskSpan


The Relative Refinance Slowness Is From the Large Balance Loans

The overall slowness of the social collateral in Figure 5 is driven by large loans. Figure 6 shows that, among loans <$417K, the prepay patterns of 2021-1 and 2021-2 are similar, while among loans > $417K, the prepays of 2021-2 are consistently slower. This may suggest that large loans with complex sources of income are particularly hard to underwrite.


Figure 6: The Social Deal’s Low-Balance Loans Refi Similar to Benchmark, But Large Balances Have Been Slower CRR over loan age, AOMT 2021-2 vs. AOMT 2021-1, bucketed by loan size, July 2021-January 2022 Source: CoreLogic, RiskSpan


 

Updated Collateral Mix


The Social Deal’s Credit Mix Has Drifted Riskier, Warranting Ongoing Monitoring

While the early performance of the social collateral is positive, Figure 7 provides reason for concern and ongoing watchfulness. Since origination, the composition of the social 2021-2 has drifted riskier in all respects except slight improvements in WA DTI and WA LTV. Its LTV tails, WA FICO, and FICO tails; proportions of cash-out, low doc, non-owner-occupied; and average overall risk layers are all somewhat riskier.

The drift for 2021-1 has been more mixed. Like 2021-2, it is safer with respect to WA DTI and WA LTV. Unlike 2021-2, it is also safer with respect to LTV tails, FICO tails, and cash-out proportion. Like 2021-2, it is riskier with respect to WA FICO; proportions of low doc and non-owner-occupied; and average overall risk layers.

We will continue to monitor whether this composition drift drives differential performance going forward.


Figure 7: Edge’s Collateral Comparison Screen Showing AOMT 2021-1 (aka AOAK 2101) vs. 2021-2 (aka AOAK 2102) updated to the Current Factor DateSource: CoreLogic, RiskSpan


Using Edge, you can examine prepay or credit performance of loan subsets defined by any characteristics, and generate aging curves, time series, or S-curves.

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Prepayment Spikes in Ida’s Wake – What to Expect

It is, of course, impossible to view the human suffering wrought by Hurricane Ida without being reminded of Hurricane Katrina’s impact 16 years ago. Fortunately, the levees are holding and Ida’s toll appears likely to be less severe. It is nevertheless worth taking a look at what happened to mortgages in the wake of New Orleans’s last major catastrophic weather event as it is reasonable to assume that prepayments could follow a similar pattern (though likely in a more muted way).

Following Katrina, prepayment speeds for pools of mortgages located entirely in Louisiana spiked between November 2005 and June 2006. As the following graph shows, prepayment speeds on Louisiana properties (the black curve) remained elevated relative to properties nationally (the blue curve) until the end of 2006. 

Comparing S-curves of Louisiana loans (the black curve in the chart below) versus all loans (the green curve) during the spike period (Nov. 2005 to Jun. 2006) reveals speeds ranging from 10 to 20 CPR faster across all refinance incentives. The figure below depicts an S-curve for non-spec 100% Louisiana pools and all non-spec pools with a weighted average loan age of 7 to 60 months during the period indicated.

The impact of Katrina on Louisiana prepayments becomes even more apparent when we consider speeds prior to the storm. As the S-curves below show, non-specified 100% Louisiana pools (the black curve) actually paid slightly slower than all non-spec pools between November 2003 and October 2005.

As we pointed out in June, a significant majority of prepayments caused by natural disaster events are likely to be voluntary, as opposed to the result of default as one might expect. This is because mortgages on homes that are fully indemnified against these perils are likely to be prepaid using insurance proceeds. This dynamic is reflected in the charts below, which show elevated voluntary prepayment rates running considerably higher than the delinquency spike in the wake of Katrina. We are able to isolate voluntary prepayment activity by looking at the GSE Loan Level Historical Performance datasets that include detailed credit information. This enables us to confirm that the prepay spike is largely driven by voluntary prepayments. Consequently, recent covid-era policy changes that may reduce the incidence of delinquent loan buyouts from MBS are unlikely to affect the dynamics underlying the prepayment behavior described above.

RiskSpan’s Edge Platform enables users to identify Louisiana-based loans and pools by drilling down into cohort details. The example below returns over $1 billion in Louisiana-only pools and $70 billion in Louisiana loans as of the August 2021 factor month.


Edge also allows users to structure more specified queries to identify the exposure of any portfolio or portfolio subset. Edge, in fact, can be used to examine any loan characteristic to generate S-curves, aging curves, and time series.  Contact us to learn more.



In ESG Policy, ‘E’ Should Not Come at the Expense of ‘S’

ESG—it is the hottest topic in our space. No conference or webinar is complete without a panel touting the latest ESG bond or the latest advance in reporting and certification. What a lot of these pieces neglect to address is the complicated relationship between the “E” and the “S” of ESG. In particular, that climate-risk exposed properties are also often properties in underserved communities, providing much-needed affordable housing to the country.

Last week, the White House issued an Executive Order of Climate-Related Financial Risk. The focus of the order was to direct government agencies toward both disclosure and mitigation of climate-related financial risk. The order reinforces the already relentless focus on ESG initiatives within our industry. The order specifically calls on the USDA, HUD, and the VA to ‘consider approaches to better integrate climate-related financial risk into underwriting standards, loan terms and conditions, and asset management and servicing procedures, as related to their Federal lending policies and programs.” Changes here will likely presage changes by the GSEs.

In mortgage finance, some of the key considerations related to disclosure and mitigation are as follows:

Disclosure of Climate-Related Financial Risk:

  • Homes exposed to increasing occurrence to natural hazards due to climate changes.
  • Homes exposed to the risk of decreasing home prices due to climate change, because of either increasing property insurance costs (or un-insurability) or localized transition risks of industry-exposed areas (e.g., Houston to the oil and gas industry).

Mitigation of Climate-Related Financial Risk:

  • Reducing the housing industry’s contribution to greenhouse gas emissions in alignment with the president’s goal of a net-zero emissions economy by 2050. For example, loan programs that support retrofitting existing housing stock to reduce energy consumption.
  • Considering a building location’s exposure to climate-related physical risk. Directing investment away for areas exposed to the increasing frequency and severity of natural disasters.

But products and programs that aim to support the goal of increased disclosure and mitigation of climate-related financial risk can create situations in which underserved communities disproportionately bear the costs of our nation’s pivot toward climate resiliency. The table below connects the FEMA’s National Risk Index data to HUD’s list of census tracts that qualify for low-income housing tax credits, which HUD defines as tracts that have ‘50 percent of households with incomes below 60 percent of the Area Median Gross Income (AMGI) or have a poverty rate of 25 percent or more.’ Census tracts with the highest risk of annual loss from natural disaster events are disproportionally made of HUD’s Qualified Tracts.

As an industry, it’s important to remember that actions taken to mitigate exposure to increasing climate-related events will always have a cost to someone. These costs could be in the form of increased insurance premiums, decreasing home prices, or even loss of affordable housing options altogether. All this is not to say that action should not be taken, only that balancing social ESG goals should also be considered when ambitious environmental ESG goals come at their expense.

The White House identified this issue right at the top of the order by indicating that any action on the order would need to account for ‘disparate impacts on disadvantaged communities and communities of color.’

“It is therefore the policy of my Administration to advance consistent, clear, intelligible, comparable, and accurate disclosure of climate-related financial risk (consistent with Executive Order 13707 of September 15, 2015 (Using Behavioral Science Insights to Better Serve the American People), including both physical and transition risks; act to mitigate that risk and its drivers, while accounting for and addressing disparate impacts on disadvantaged communities and communities of color (consistent with Executive Order 13985 of January 20, 2021 (Advancing Racial Equity and Support for Underserved Communities Through the Federal Government)) and spurring the creation of well-paying jobs; and achieve our target of a net-zero emissions economy by no later than 2050.”

The social impacts of any environmental initiative need to be considered. Steps should be taken to avoid having the cost of changes to underwriting processes and credit policies be disproportionately borne by underserved and vulnerable communities. To this end, a balanced ESG policy will ultimately require input from stakeholders across the mortgage industry.


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