Cost of Misaligned CARES Act: Overcrowding, Selective Verification and Unintended Racial Consequences
60 Pages Posted: 28 Sep 2020 Last revised: 19 Apr 2021
Date Written: October 2, 2020
I utilize a novel data on proprietary servicer call transcripts to investigate strategic borrower responses to mortgage forbearance program (13% with only 1.5% unemployed) contained in the Coronavirus Aid, Relief, and Economic Security Act. I document selective verification of unemployment status (financial hardship) by the servicer. I also discern unintended consequences (disparate impact) of 2.4% for Inbound and 2% for Outbound communications for African American borrowers (without the servicer having race information) by the servicer to reduce ex-post risk. The soft information helps identify the incentives for these communications between the borrower and the servicer. My finding sheds light on the poor-targeting of Government programs (FHA, VA, USDA) during exacerbated income shocks from COVID-19 and estimates a $5.76 Trillion exposure from plausible non-payment of residential mortgage debt obligations from forbearance.
Keywords: Strategic Behavior, Forbearance, Machine Learning, NLP, Race, COVID-19, CARES Act
JEL Classification: R38, R28, K32, J15, H12, H81, G01, E61, E63, D80, D61, D12, D18
Suggested Citation: Suggested Citation