Combatting the Effects of Algorithmic BiasThoughts
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.
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
Today marks the publication of Chris Widman's Quantitative Perspective, a comprehensive article on the newest member of our LoanDynamics suite, the Auto LoanDynamics Model. Auto LDM will be integrated into vendor systems and AD&Co tools, allowing users to perform analysis on auto loan and ABS positions.
EventsSince 1970, April 22nd has been the annual day to appreciate our planet and recognize the importance of protecting it. But more and more, we realize that everyday needs to be Earth Day, and that we need to take better care of the place that gives us life.
To seek "causes" of poverty in this way is to enter an intellectual dead end because poverty has no causes. Only prosperity has causes. – Jane Jacobs, Activist and Author
CRTcast, a new podcast series under Freddie Mac’s Home Starts Here programming, focuses on credit risk transfer (CRT) and it’s three spokes: securities, (re)insurance and mortgage insurance. Freddie Mac leadership together with CRT industry experts cover current and relevant topics.
Richard Cooperstein named co-chair of the Structured Finance Association’s Regulatory Capital & Liquidity CommitteeNews
We are proud to announce that Richard Cooperstein has accepted the position of co-chair of the Structured Finance Association’s (SFA) Regulatory Capital & Liquidity committee.
NewsToday we acknowledge the Year of the Ox. Happy Lunar New Year! We stand in solidarity with the Asian community against all violence and racism. Here’s to a year of peace, health and prosperity.
NewsThis February, AD&Co celebrates a central part of American History—Black History. The richness of the contributions of the Black community as a whole, and innumerable remarkable individuals, can not be overstated.
The January 14, 2021 revisions of the Preferred Stock Purchase Agreements between the Treasury and the GSEs[i] (Government Sponsored Enterprises) along with the Treasury Department Blueprint on Next Steps for GSE[ii] Reform perhaps represent the end of a decade- long effort to create multiple competitive enterprises and end the government support of the GSEs.
NewsMartin Luther King, Jr. was a great leader and inspirational speaker. His wisdom can serve as a guide for as long as we remember him. Andrew Davidson & Co would like to acknowledge a fraction of what he gave us with two relevant quotes that seem fitting in 2021.
In the spring of 2019, National Association of Realtors® (NAR), together with financial-market experts Susan Wachter (Wharton) and Richard Cooperstein (Andrew Davidson & Co., Inc.) proposed completing the transition of Fannie Mae and Freddie Mac (Enterprises) into market utilities in a publication entitled “A Vision for Enduring Housing Finance Reform.” This work builds on Richard Cooperstein and Andrew Davidson’s 2017 paper