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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Combatting the Effects of Algorithmic BiasThoughtsHomeownership is the largest source of wealth accumulation and inter-generational wealth transfer for the working and middle class. However, the history of racial discrimination (it was actually legal to discriminate by race in housing until the Fair Housing Act of 1968), suggests that we have a continuing responsibility to ensure fair access to housing and housing finance.
The homeownership rate for white Americans has averaged 70-75% over the last 25 years but only 40-50% for black Americans. In fact, the gap has widened over this period.
What is Equitable Housing Finance, and how do we make progress towards it?
The issues of economic opportunity, and geographic and housing inequality, are long-standing and varied. But as practitioners in mortgage risk and analytics, we focus on data, assessing risk and equal access to mortgage credit. Households of moderate means generally use credit to buy their first home so we must consider credit access and the quantitative process carefully, especially in the context of artificial intelligence and unintentionally biased algorithms.
The premise is simple: Use the same comprehensive set of financial data for everyone and apply it fairly.
Going beyond credit scores
Most people know about credit scores, which serve as the principal metric used for credit decisioning. What if it turns out that credit scores don’t reflect all relevant consumer financial data? What if this data gap has grown over time, and what if it’s larger for targeted groups like minorities and low-income families?
To the degree that mortgage decisioning models omit relevant data, they become less accurate. To the degree that such omissions are concentrated among certain groups, these models will contain algorithmic bias.
Consumer credit scores were created in the 1950s, and the Equal Credit Opportunity Act of 1974 ensured they could not include discriminatory information. The FICO formulation commonly used for mortgage credit today was built about 2004 and it correlates well to the likelihood of short-term delinquency.
However, financial data is now available that is materially relevant to consumer credit performance, but is not included in credit scores. This data is generally more significant for renters and underserved populations, those with smaller traditional financial footprints. Such indicators include consumer credit card balances, telecom/utility payment data, and free cash flow from bank accounts.
The mortgage ecosystem is beginning to work towards using expanded consumer financial data. AD&Co is acquiring this data and improving our analytics make mortgage decisioning both more accurate and more fair.
Working through public policy
Leveraging new data, advancing national standards, and broadly implementing improved decisioning are not automatic. Most mortgage lending is federally connected (GSEs, FHA/VA, banks), and compliance standards are universally applied. This occurs in part because the mortgage market contains inherent information asymmetries and social externalities around fairness and stability. The confluence of finance and policy leads us to combine our analytic efforts with actively engaging with federal counter-parties and in the policy debate. This includes focusing on how to integrate new data sources into mortgage decisioning on a national scale as a means to improve accuracy and fairness.
The S-Curve Archives
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ProductsAndrew Davidson & Co., Inc (AD&Co) is pleased to announce the beta release of a new monthly report series titled “Specified Pool Prepayment Trends,” which aims at showing market prepayment trends for specified agency pools in support of pay-up analyses by investors, traders, and alike.
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ProductsAndrew Davidson & Co., Inc (AD&Co) is pleased to announce that Polypaths LLC supports AD&Co’s Auto LoanDynamics Model (Auto LDM) providing prepayments, defaults and losses on auto loans and securities.
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EventsThe Structured Finance Association hosted SFVegas 2023 (February 26 - March 1), a broad capital markets conference with thousands of attendees in Las Vegas. Andrew Davidson & Co. Inc. (AD&Co) was a sponsor focused on the mortgage sector. As we engaged with clients and policy leaders, a few themes emerged: Data, Expanding Access Safely, Ginnie Mae Servicing and Auto Loan Performance.
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ProductsAndrew Davidson & Co., Inc (AD&Co) is pleased to announce the official release of the LoanDynamics Module in Kinetics, AD&Co's new modular platform for running AD&Co analytics via a desktop application, web browser, or REST API. The LoanDynamics Module is the latest way to run the LoanDynamics Model, allowing users to perform sensitivity analysis, validation testing, and scenario analysis in a modern, user-friendly application.
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ThoughtsRecently the Federal Housing Finance Agency (FHFA) announced some upcoming changes related to the use of new credit scores, FICO 10T and VantageScore 4.0 by Fannie Mae and Freddie Mac. “FHFA expects that implementation of FICO 10T and VantageScore 4.0 will be a multiyear effort. Once implemented, lenders will be required to deliver both FICO 10T and VantageScore 4.0 credit scores with each loan sold to the Enterprises”.[1] This announcement will impact the entire mortgage ecosystem.
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ThoughtsJanuary is National Mentoring Month which is very appropriate since it coincides with the time when we typically set out our goals and intentions for the New Year. Organizations are embracing mentoring programs and these programs have indeed become a strategic imperative for many. There are many benefits to mentorship and it's easy enough to comprehend. The individuals involved in a mentoring relationship and the organizations that choose to sponsor a mentoring program all are likely to benefit.
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ThoughtsHomeownership is the largest source of wealth accumulation and inter-generational wealth transfer for the working and middle class. However, the history of racial discrimination (it was actually legal to discriminate by race in housing until the Fair Housing Act of 1968), suggests that we have a continuing responsibility to ensure fair access to housing and housing finance.
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ThoughtsDear Friends,
As Andrew Davidson & Co., Inc. (AD&Co) reaches its 30-year milestone, I reflect on two seemingly contradictory ideas: Firms need experience to guide clients through difficult times but sometimes it is necessary to discard past practices to achieve breakthroughs.
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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.