The S-Curve

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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Blog - Latest
  • Combatting the Effects of Algorithmic Bias

    Richard Cooperstein


    Homeownership 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.

    FRED chart

    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.

Blog - Archives

The S-Curve Archives

  • Tom Parrent


    Separating signal from noise is at the heart of what we do at AD&Co. One of the key tools we utilize for that purpose is a sophisticated set of model performance trigger reports. These monthly reports not only alert us to model drift but also point to possible causes for the drift.

  • News

    We proudly launched our new website on November 13th. As you familiarize yourself with the new look of, you will come to know the many new offerings we provide. Along with the new website, we have organized our products as a menu of models and applications for a wide range of investor appetites. Let us review the menu of our product offerings.

  • News

    Andrew Davidson & Co., Inc. (AD&Co), is proud to support Fite Analytics’ innovative cloud-native Mortgage-Backed Securities Analytics Service. The Fite Analytics solution incorporates AD&Co’s LoanDynamics models that provide forecasts of voluntary prepayments, defaults and losses that drive risk analytics across the mortgage-backed securities market with comprehensive coverage.

  • News

    We are thrilled to announce that Andrew Davidson & Co., Inc. has launched a new look for Some of the exciting new features of this site include:

    • A dynamic homepage highlighting the firm’s latest innovations, AD&Co client benefits, announcements, and Diversity, Equity and Inclusion efforts.