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.

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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.

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.

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!

For several years, AD&Co has tracked the total rate of return (TRR) performance of the GSE CAS and STACR CRT in its U.S. Mortgage High-Yield Indices. The AD&Co Mid-Tier index constitutes a broad market measure of the TRR performance of GSE CRT. The related sub-indices segregate the CRT market into 4 index Tiers by attachment point, reflective of the credit exposure of the various classes of underlying CRT ranging from B to M1.

We are pleased to announce that the historical time series for these indices is now publicly available on the St. Louis Federal Reserve's FRED database, along with the credit-adjusted OAS (CrOAS) for each series. FRED is host to almost 800,000 data series from more than 100 sources. The indices published on FRED can be viewed here. Detailed performance analysis related to the index is available on a monthly basis at through AD&Co.

For more information please contact Rob Landauer at 212-274-9075, email Rob at rob@ad-co.com or visit www.ad-co.com. 

Disclaimer: The AD&Co U.S. Mortgage High-Yield Index serves as an informational index and is not for commercial-use purposes. The Index’s accuracy, completeness, timeliness, and suitability for any purpose are not guaranteed. The Index does not constitute (1) investment, legal, accounting, tax, or other professional advice or (2) any recommendation or solicitation to purchase, hold, sell, or otherwise deal in any investment. This Index has been prepared for general informational purposes, without consideration of the circumstances or objectives of any particular investor. Any reliance on the Index is at the reader’s sole risk. All investment is subject to numerous risks, known and unknown. Past performance is no guarantee of future results. For investment advice, seek a qualified investment professional. Not for redistribution without permission. Note: An affiliate of Andrew Davidson & Co., Inc. engages in trading activities in investments that may be the same or similar to those featured in the Index.