Research Report Preventing Foreclosures
Subtitle
What Has Been Done? What Is to Come?
Laurie Goodman, Jun Zhu
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Loss mitigation strategies in mortgage lending have evolved significantly over the past 15 years. The response to the 2008 financial crisis catalyzed a paradigm shift in how mortgage distress is managed, leading to standardized tools. Among these pioneering efforts was the Home Affordable Modification Program, aimed at providing programmatic payment relief to financially stressed homeowners. Natural disasters in the late 2010s further refined these approaches. During the COVID-19 pandemic, these existing strategies were adapted and expanded to unprecedented scale and nature. These loss mitigation strategies were so successful that many have been made permanent.

The key feature of the COVID-19 loss mitigation efforts was the prioritization of forbearance as the first step of the waterfall, which provided borrowers a grace period to assess their financial situation. This was accompanied by a seamless transition from this grace period to a permanent solution. In this report, we trace the evolution of the loss mitigation process. We examine the changes made during pandemic era, discuss their effectiveness, and document what has been made permanent.

Building upon these insights, we propose potential improvements to the loss mitigation toolkit, aimed at continuously strengthening our capacity to preserve homeownership stability. We also investigate alternative approaches, including streamlined modifications and mortgage reserve accounts, to further reduce default rates and bolster the resilience of our housing system.

This thorough examination aims to clarify the development and effectiveness of modern loss mitigation strategies and to lay the groundwork for future innovations to enhance homeowners’ financial security during challenging times.

Research and Evidence Housing and Communities Technology and Data
Expertise Housing Finance Policy Center Housing
Tags COVID-19 Housing stability Data analysis Qualitative data analysis Quantitative data analysis
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