
Background and Context
Research Focus
This study investigates discrimination in mortgage lending by examining interest rate differences between minority and non-minority borrowers for loans backed by government-sponsored enterprises (GSEs) and the Federal Housing Administration (FHA).
Methodology
The researchers analyzed over 5.7 million mortgage loans issued between 2009-2015 and 3.2 million loans from 2018-2019, comparing interest rates between Latinx/Black borrowers and non-minority borrowers while controlling for credit risk factors.
Data Sources
The study merged four major mortgage datasets: McDash loan-level data, ATTOM property data, Home Mortgage Disclosure Act (HMDA) data, and Equifax loan performance data to create a comprehensive analysis.
Higher Interest Rates Paid by Minority Borrowers (2009-2015)
- Shows the additional interest rate paid by minority borrowers compared to non-minority borrowers
- Purchase loans show larger disparities than refinance loans
- Both GSE and FHA loans exhibit significant rate differences
Interest Rate Disparities by Census Tract Minority Share (2009-2015)
- Shows how rate differences increase in areas with higher minority populations
- Demonstrates geographical component of lending discrimination
- Rate disparities are highest in census tracts with highest minority share
FinTech vs Traditional Lender Rate Disparities (2018-2019)
- Compares discrimination levels between FinTech and traditional lenders
- Shows FinTech lenders exhibit similar disparities for GSE loans
- Demonstrates technology alone does not eliminate lending discrimination
Impact of Points and Loan Costs on Rate Disparities (2018-2019)
- Shows rate disparities persist even after controlling for points and loan costs
- Demonstrates discrimination cannot be explained by differences in up-front payments
- Indicates systematic pricing differences affect minority borrowers
Estimated Annual Cost of Discrimination
$450+ Million
- Represents the additional interest paid annually by minority borrowers due to rate disparities
- Calculated using 2018-2019 rate differences and total GSE/FHA mortgage volumes
- Demonstrates the substantial economic impact of lending discrimination
Contribution and Implications
- Provides first comprehensive evidence of persistent mortgage discrimination in the post-financial crisis era
- Shows algorithmic lending has not eliminated discrimination, suggesting need for additional regulatory oversight
- Demonstrates importance of GSE/FHA role in standardizing credit risk assessment to reduce discrimination
Data Sources
- Rate differentials from Table 3 (2009-2015 data) and Table 10 (2018-2019 data)
- Census tract analysis based on figures reported in Section 5.4.1 and Table 5
- FinTech comparison using data from Table 11
- Points and costs analysis from Table 10 panels (a) and (c)
- Annual cost estimate derived from methodology described in Section 8