期刊
JOURNAL OF FINANCIAL ECONOMICS
卷 143, 期 1, 页码 30-56出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.jfineco.2021.05.047
关键词
Discrimination; FinTech; GSE mortgages; Credit scoring; Algorithmic underwriting; Big-data lending; Platform loans; Statistical discrimination; Legitimate business necessity
U.S. fair-lending law prohibits lenders from making credit determinations that disparately affect minority borrowers based on characteristics unrelated to creditworthiness. Research shows that risk-equivalent Lat-inx/Black borrowers pay significantly higher interest rates in high-minority-share neighborhoods, resulting in over $450 million yearly loss for minority borrowers. FinTech lenders' rate disparities were similar to non-Fintech lenders for GSE mortgages, but lower for FHA mortgages issued in 2009-2015 and FHA refi mortgages issued in 2018-2019.
U.S. fair-lending law prohibits lenders from making credit determinations that disparately affect minority borrowers if those determinations are based on characteristics unrelated to creditworthiness. Using an identification under this rule, we show risk-equivalent Lat-inx/Black borrowers pay significantly higher interest rates on GSE-securitized and FHA-insured loans, particularly in high-minority-share neighborhoods. We estimate these rate differences cost minority borrowers over $450 million yearly. FinTech lenders' rate dispar-ities were similar to those of non-Fintech lenders for GSE mortgages, but lower for FHA mortgages issued in 2009-2015 and for FHA refi mortgages issued in 2018-2019. (c) 2021 Elsevier B.V. All rights reserved.
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