Welcome to The S-Curve
Now you will be able to receive the latest announcements, product updates, and our insights on the mortgage market in real time.
The name of the blog, the S-Curve, is a reflection of our logo and the central feature of our prepayment model. S-curves are seen in nature in many phenomenon, from population growth to prepayment and default models. Our first S-curve, in the early 1990s, used the arctangent function, then piece-wise linear functions, and evolved over time to be more complex and vary by FICO, loan size and LTV. This evolution encapsulates both the timeless nature of fundamental relationships and constant innovation to describe them better over time.
We hope you find the information useful and we look forward to your feedback.
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Why Financial Firms Need a New Climate Change Risk Strategy Starting NowThoughts
According to a report by the Research Institute for Housing America, climate change risk is rapidly increasing in the housing industry and will continue to demand more attention and regulation in the near future.
Climate change will impact risk factors in the housing industry in nearly every corner of the globe. Wildfires are becoming more common and the area they ravage more extensive. Hurricanes and severe storms are happening with more frequency and severity. Potential damage from excess heat and droughts elevates risk to properties every day.
However, flooding is currently one of the highest risk factors posed to the housing industry. Many housing areas are used to the idea of flood risk and are adequately prepared and protected, but many properties that were never at risk before are now in the danger zone. The housing market is currently in a vulnerable position.
When Floods Outpace Insurance Policies
Depending on geography, more properties without previous flood risk are increasingly likely to experience flood damage. Homes and communities that were erected in floodplains are used to the protocols: Safety procedures such as evacuating or securing the area, working with insurance to cover damage, or receiving aid to rebuild when possible.
Under the National Flood Insurance Program, homes that are federally backed by programs such as Freddie Mac and Fannie Mae in certain areas require the owners to carry flood insurance. Those homes are located in floodplains that are defined based on a 100-year flood probability.
The problem is that floodplain boundaries are rapidly changing. One hundred years' worth of flooding data is not as relevant as it used to be when flooding zones are becoming more and more volatile. Even as the area of potential flooding damage overflows into neighboring regions, the floodplain boundaries have not been redrawn recently enough to impact flood policy uptake.
That means many homes that are at risk of future flooding are not likely or required to carry flood insurance. Experts are predicting that the National Flood Insurance Program will be stretched to its limits very soon, and that banking and insurance regulation will need to act quickly to spread and manage climate-related risk. It's possible that soon, the total cost of owning homes will outpace the value of the home.
This becomes very concerning when we consider the likelihood of mortgages going unpaid; a lack of flood insurance then quickly becomes not just a housing risk but a credit risk for the owners and an economic risk for the country if housing prices plummet and people’s debts begin to far outvalue their assets.
Updating Risk Calculations on Climate Change Analysis
Firms currently vary in their preparedness to face climate change insurance risk. As data becomes more advanced, some firms have begun to license property-level climate risk data, and specialist analytics firms are appearing with expertise in climate models.
The Fed and the SEC are also trying to adapt regulations to fit the new (and ever-changing) reality of climate change risk. There are new committees dedicated to assessing climate change analysis and determining systemic risk to the entire financial world, including the Supervision Climate Committee. These regulators will need updated methods to quantify risk and mandate disclosure, but for now, changes are nascent and firms will have to add their own experience to the bank of loss exposure research.
Financial firms are facing — or are about to face — considerable pressure from investors, governing and regulatory bodies, and insurance and banking regulators concerning the way they calculate risk. They will probably also feel some pressure from employees and workers in the financial sector, who are becoming increasingly alarmed about the impending disruption of climate change.
Firms will need to manage climate risk alongside their broader risk management strategy. For that to work, they’ll need to understand climate change data and the set of exposure scenarios that are relevant to them. For example, McKinsey predicts that about one-third of the planet's land will be affected by climate change. In addition, flooding exacerbated by climate change is expected to double the damage to capital stock by 2030.
Financial institutions urgently need to understand how to calculate and explain the risks posed by climate change, both for their own risk management strategies and for stakeholders. Quantifying climate change risk will be an evolving science. Property portfolios will require new risk scores based on the potential hazards that climate change will bring. Those scores will then need translating into commonly used financial measures, such as credit risk, market risk and prepayment risk.
As financial firms wait for regulatory approaches to become clear, they will need to continue to educate themselves and to remember that climate change models will shift rapidly — the best climate change risk strategy will be the one that is most able to change.
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Policy Perspectives: Fed 2020 Intervention And Mortgage Market OutcomesThoughts
Mortgage market participants are keenly aware that the Federal Reserve has been scaling back its UST and MBS purchases and factoring the outcomes of its actions on stakeholders across markets. In this Policy Perspectives article, we take a retrospective look back at the March 2020 ease from a mortgage markets view point and highlight how the outcomes of intervention manifest through the interaction of related primary and secondary mortgage markets activities. We show that Fed activity can have unintended and disruptive impacts on the functioning of housing finance and result in wealth effects that benefit the more affluent segments of the housing economy.
Read Now
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It’s Time to Change Our Definition of Who Qualifies as a ‘Good’ Homeowner — Here’s HowThoughts
The growing prevalence of artificial intelligence in the mortgage industry is shining a new light on the human biases that have pervaded the industry since its inception. AI is meant to bring fairness and objectivity to mortgage decisions, but it can’t perform fairly if it was built on an unfair system.
In particular, racial bias in mortgage lending is a prevalent issue. The homeownership gap between the Black and white populations has remained relatively unchanged for more than a century, and today, it’s as wide as ever. Moreover, Black borrowers were 2.5 times more likely to be rejected for a home loan last year than their white counterparts — and that data does not account for applicants who ended up not making a home purchase.
Equipping lenders with more software and better algorithms will not reduce this gap. Before AI can be deployed effectively as a tool for positive change in the mortgage industry, a widespread shift in perspective must take place.
Importantly, lenders must change their definition of who qualifies as a “good” or successful homeowner in order for AI to operate with true objectivity. To reduce inequity in the mortgage industry, lenders need to change the question from “Who is delinquent?” to “If someone is delinquent, what can cure the delinquency to ensure long-term success?”
The Delinquency Dilemma
Historically, lenders have relied on delinquency as an influential metric when assessing borrower capacity and have (both consciously and unconsciously) equated it with the moral worth of mortgage applicants. In the midst of increasingly numerous and devastating natural disasters and the ongoing COVID-19 pandemic, however, the delinquency metric has come under scrutiny.
As an indicator of potential success in mortgage fulfillment, delinquency is not an accurate representation of a borrower. It is increasingly being understood as a result of circumstances, and not necessarily the result of a person’s ability to own a home.
A credit score, for example — which is based on measures of delinquency — is not a viable indicator of a person’s long-term ability to afford a car or home. Still, it will exert a disproportionate influence on the costs of borrowed capital, which are often prohibitive for BIPOC mortgage applicants.
If nothing else, the social, political, and economic uncertainty that has characterized the past several years has shown that delinquency alone cannot be a viable metric. As people around the world dealt with the pandemic, a halting economy, and disruption in nearly every aspect of life, it became clear that delinquency simply was not a relevant differentiating metric.
It’s also important to realize that circumstances resulting in delinquency have historically impacted people of color disproportionately. According to the Consumer Financial Protection Bureau’s May 2021 report on the characteristics of mortgage borrowers through COVID-19, BIPOC homeowners faced higher rates of delinquency and forbearance than their white counterparts. Specifically, Black and Hispanic borrowers account for only 18% of all mortgage borrowers, yet these groups represented 33% of mortgages in forbearance and 27% of the mortgages that were delinquent.
There are numerous social, economic, and political factors that impact why BIPOC communities are affected more heavily than others in extenuating circumstances. To begin with, BIPOC families have historically had less generational wealth. According to a September 2020 report from the U.S. Federal Reserve, white families have eight times more wealth on average than Black families, and five times more wealth on average than Hispanic families.
If the industry continues to use the same metrics that exacerbated this wealth disparity in the first place, then equity in lending will always be out of arm’s reach.
Progressing Toward Equality
Thankfully, the wider perspective has begun to shift over the past few years. Rather than punishing delinquent borrowers with additional fees or removing them from their homes, lenders are seeing the value of assisting homeowners so they can remain in their homes over the long term. After all, penalizing short-term financial hardship is not as profitable as helping a borrower successfully complete payments over the course of the mortgage.
As such, lenders are beginning to focus on different types of metrics, which will have important (and positive) implications for mortgage decisions and even AI-led mortgage analytics.
Increasingly, lenders are realizing that forbearance, loss mitigation, income disruption assistance, and other approaches are far more effective when it comes to extending homeownership. They’re considering attributes that might make borrowers more likely to re-perform if given some leeway as well as the systems that will be needed to ensure temporary setbacks are rectified.
This is a massive step in the right direction. As lenders continue to shift their focus toward metrics of sustainable homeownership instead of delinquency, the hurdles these borrowers face should become smaller.
That said, AI-powered lending tools must be deliberately and thoughtfully designed around those metrics, and with the intention to create a more equitable system. Otherwise, technology will reinforce old ways of thinking — and racial bias in mortgage lending will persist.
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Andrew Davidson & Co., Inc. (AD&Co) is pleased to announce the first release of the Auto LoanDynamics Model (AutoLDM).Products
The LDM v3.0.2 library adds AutoLDM to the v3.0.1 library.
Key benefits include:
- AutoLDM is a loan-level model that produces monthly default, prepayment, severity, balance, and delinquency projections.
- The projections are sensitive to individual borrower attributes (e.g., credit score, contract rate, loan term, delinquency status) and vehicle characteristics (e.g., vehicle age, type, new/used).
- The model utilizes a delinquency state transition framework to model the migration of the borrower conditional on their attributes and the unemployment projections.
- AutoLDM covers the full credit spectrum of loans from subprime through prime borrowers.
- Extensive support of AutoLDM is available from experienced modelers.
- Model validation documentation is available.
AutoLDM is available via the LDM library and through the AutoKinetics application. For a full list of updates, read our LoanDynamics Model v3.0.2 Release Notes.
We are working closely with our third-party vendors on the integration of this release into their platform. For more information about the availability of this release through your vendor system, please contact michelle@ad-co.com. For all other requests, please contact support@ad-co.com.
Release notes for all our products are available at https://www.ad-co.com/support/release-notes.
To access AutoLDM demo on-demand, please click here.
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Andrew Davidson & Co., Inc. Celebrates Pride MonthEvents

We at Andrew Davidson & Co., Inc. (AD&Co) are once again thrilled to celebrate Pride Month, especially the contributions of LGBTQ professionals in the field of finance including affordable housing policy and the GSEs. This year, in addition to celebrating, we are also paying increased attention to the challenges that LGBTQ individuals face, particularly around issues of housing. Our pride in our LGBTQ staff and community sits alongside our concern about discriminatory lending practices, including in mortgages. As of February 2021, for the first time, lesbian, gay, bisexual, transgender, queer, and questioning (LGBTQ) Americans will be protected from housing discrimination under the Fair Housing Act.
We have also had our eyes opened to youth homelessness. LGBTQ people make up 40% of the homeless youth population in the country: Their risk of homelessness is 120% of the general population.
We at AD&Co are committed to change. Here’s to Pride!
The S-Curve Archives
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ThoughtsFor many people, having accessible transportation (a car, for example) is necessary. Most U.S. people live in areas without adequate public transportation and require vehicles to access jobs, healthcare, and groceries.
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Thoughts
As interest rates rise and fewer loans with refinancing incentive remain, other factors are primed to play a larger role in determining prepayment speeds in the coming months (and perhaps years). Turnover, the rate at which people move, is the most cited of these factors. In this blog post, we’ll consider two other potential drivers: curtailments, or partial prepayments, and mortgage payoffs that don’t involve taking out a new loan.
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Thoughts
Summary
In 2021, Andrew Davidson & Co. Inc. (AD&Co) proposed a benchmark cohort approach to setting Ability-to-Repay (ATR) Qualified Mortgages (QM) standards. Successful benchmarks based on data are model-free and transparent, and the cohorts must perform consistently in comparison to one another and across time. Our original work used data through the early stages of the pandemic when non-performing loan percentages skyrocketed.
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ThoughtsHow Lowering Capital Costs Affects Higher-Risk Loans
Government-sponsored enterprises (or GSEs) are companies that provide guarantees and financing to originators through the mortgage secondary market. The size and resilience of the GSE secondary market maximizes diversification and liquidity which reduces financial risk and cost of capital. This benefit accrues to conforming borrowers through lower mortgage rates and resiliently available financing.
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ProductsThe release of Andrew Davidson & Co., Inc.’s (AD&Co) new generation of financial engineering tools marks a shift to a new reality; when the traditional benchmark for MBS valuation, the LIBOR/ Swap yield curve, becomes unavailable. Our recent Product Release email informed our readers about the change. In short, our users can:
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ThoughtsFHFA held a listening session for interested parties on its proposed rule on the GSE process for credit scores. The objective is making mortgage underwriting and pricing more accurate and more fair while balancing practical implementation by firms in the mortgage ecosystem. Along with many others, I had the opportunity to provide insights on this proposed rulemaking.
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ThoughtsIn our January 19th blog entitled, A More Equitable Lending System Will Not Be Created by Accident, we described the efforts it will take to overcome not just bias in lending today, but the systemic factors that have limited access to credit in the past and have created an unjust system.
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ThoughtsIn this short blog post I discuss some developments taking place in the flood insurance landscape in the US and look ahead at a few potential directions things could go. I suggest that universal catastrophic flood insurance coverage with a continuation of the introduction of risk-based pricing would be a significant improvement.
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ThoughtsIntroduction
The Government-Sponsored Enterprises (GSEs) entered conservatorship in September 2008. One could view the succeeding thirteen years as a journey back to financial stability with a refined operating model that looks more like a financial utility than a hedge fund. This business model is more compatible with a fair lending mission for a standard-setter that maintains secondary markets under an effective regulator. The GSEs remain the largest part of the housing finance backbone and a resilient funding source during economic stress.
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Thoughts
Around 75% of white American families were homeowners in the first quarter of 2020, according to data from the United States Census Bureau. However, only 44% of Black American families owned their homes at the same time.