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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Insights on Updating GSE Credit Score PolicyThoughtsFHFA 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.
Insights
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The mortgage credit score market is better served by 2 providers rather than 1, or 10. Other consumer credit markets have had two major providers for years and the main reason only one score is used for mortgages is regulatory restriction. Why two? The credit score market has core characteristics of a regulated utility. Providers are commercial enterprises that have barriers to entry and large externalities; negative if run poorly, positive if run well, and large information asymmetries. Their mission is profitable but not profit maximizing. Two regulated actors provide innovation and service to market while limiting confusion or destructive competition.
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Credit providers set the rules for which score, not the credit requesters. There is concern that with a choice of credit scores, originators will pick off the GSEs. This is a false concern since FNMA (soon FRE) hasn’t used credit scores for years. As a major investor in credit risk, FNMA uses core consumer data and doesn’t rely on third party metrics. Estimates are that a dual score model could cost $500 M over three years. Since several thousand originators in other markets already use two scores this seems unlikely. Even if true, this amounts to 1 basis point on mortgage origination volume over this time.
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Important consumer data is not included in classic credit scores today, and some may never be because they’re not credit data, such as Trended Data, Telecom Utility data, and rental data. Regulators should ensure that all card companies report Trended Data. Even if it’s possible to combine into one score, it may not benefit consumers to have an even broader opaque metric of their financial lives controlled by private companies.
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It’s likely that expanding consumer financial data in mortgage underwriting and pricing will benefit first-time buyers and under-banked populations that have been historically discriminated. Since digital availability is widespread, transition expenses should not be a reason to avoid improving lending fairness.
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The data necessary to build a quantitative bridge from old scores based on limited data to new scores based on expanded data should eventually be generally available so the broader market can make their own risk decisions as well as the GSEs (MIs, servicers, investors, researchers, etc.).
It’s clear that important consumer credit data is available outside classic credit scores and that perhaps should not be embedded into single consumer credit metrics. This extra data is quite likely to benefit first time homebuyers and underserved populations. Finally, it’s quite likely that this highly regulated, private market will provide larger benefits to consumers with two actors rather than one, or ten.
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The S-Curve Archives
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ThoughtsWe’re excited to announce our latest Quantitative Perspectives providing in-depth insights into current market trends and advanced valuation techniques. This publication offers valuable information for mortgage market participants and those involved in credit risk transfer transactions.
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PodcastTune in to Laura Silberg's interview with Andrew Davidson, Eknath Belbase and Alex Levin as they discuss their latest Quantitative Perspectives, our independent commentary series, titled
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ThoughtsAs providers of mortgage models for financial institutions, Andrew Davidson & Co., Inc. (AD&Co) enables clients to validate their use of our models and offers documentation describing the conceptual framework of the models, back-testing results, and sample forecasts under a variety of economic conditions. We also work with analytics providers who have incorporated our models to ensure that the models works as intended.
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ThoughtsWe’re excited to announce two new Quantitative Perspectives that provide in-depth insights into current market trends and advanced valuation techniques. These papers offer valuable information for mortgage market participants and those involved in credit risk transfer transactions.
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EventsAndrew Davidson & Co. Inc. (AD&Co) proudly sponsored the Information Management Network (IMN)’s 10th Annual Mortgage Servicing Rights (MSR) Forum, held November 21 - 22, 2024 at the New York Marriott at Brooklyn Bridge.
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PodcastTune in to Michelle Stepien Breier's interview with Alex Levin & Matteo Caracciolo-King as they discuss their latest Pipeline article “AD&Co Updates its Home Price Index Model.” The interview highlights key points from the article as they share recent updates to the HPI3 model.
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ThoughtsWith the increasing volumes of Synthetic Risk Transfer (SRT) and Credit Risk Transfer (CRT) along with the discussion of BASEL III, we thought it would be useful to re-issue our comment letter to FHFA on the capital treatment of Credit Risk Transfer.
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PodcastRecently, senior credit modeler, Daniel Swanson had the pleasure of speaking with Rob Kessel from the Panoramic Capital Academy podcast titled, “Modeler’s Perspective on Prepayment Modeling.” T
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ThoughtsThe earliest paper we found examining the impact of climate risks on house prices was from 2017, which found a relationship between elevation/sea level rise and house price differences.[1]
We built our climate-conditioned HPA model in 2022 based on the idea that an increase in insurance costs would impact house prices (something we had not studied yet) in the same way that an increase of the same size in mortgage rates would impact house prices (something that we were quite familiar with).
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NewsAndrew Davidson & Co., Inc (AD&Co) is pleased to announce a new alliance with Mortgage Capital Trading, Inc. (MCT), a leading provider of mortgage capital market solutions.