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PreprintCited by 7Housing Market and EconomicsUrban, Neighborhood, and Segregation StudiesBanking stability, regulation, efficiency

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'On the Take': The Black Box of Credit Scoring and Mortgage Discrimination

Open access
Havard, Cassandra·2010·SSRN Electronic Journal

Abstract

Subprime credit, a relatively new method of risk-based pricing, has been hailed as a way to open up markets and provide access to credit to those who would otherwise be excluded. Evidence suggests that subprime mortgage segmentation increases rather than reduces exclusionary practices in lending. Furthermore, what is unclear is how lenders determine who qualifies as a subprime borrower. This concern became manifested when studies demonstrated that minority borrowers, regardless of creditworthiness, are more likely to receive expensive, sub-prime loans. The disparity is properly attributed to lenders’ credit pricing policies which included discretionary increases despite the objectively-determined risk-based interest rate as well as minority borrowers’ search costs and asymmetric information about prices in this market. This Article reviews the theory and history of credit scoring in mortgage lending and argues that lenders’ practices arguably justified by "legitimate business need" as well as lenders’ credit scoring models exacerbate lending disparities. It argues that the failure of competitive forces to disallow these unjustified and illegal increases also speaks to regulatory failure. It proposes that lenders operating in noncompetitive subprime mortgage markets address how their practices interact with lending disparities even apart from their complicity in creating conditions that worsen economic disadvantage.

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Crossref · 10.2139/ssrn.1710063

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Research works printed but not linked: 42

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  2. As Dymski explains, "structural discrimination, insofar as it reflects the legacy of earlier market outcomes, can be the basis of a legal disparate-impact claim, only if overt historical discrimi� nation can be identified in the markets in question, Behavioral economists recognize as valid the idea of structural discrimination: that policies and practices that can only result in inequitable outcomes for minorities exist, 79
  3. Genevieve M See Generally, An Analysis of the Correlates of Discrimination Facing Young Hispanic Job-Seekers, 84, AM. ECON. REV, 674
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  11. Similarly, researchers also presume that any deviations from assigned weights are random, instead of indicating bias
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  37. 2010, The dynamics of credit reporting are discretionary. What is most beneficial to the average consumer is to have comprehensive credit re� porting. Comprehensive credit files contain information across all sectors. These are compared to segmented files, which are restricted to a single sector in which the con� sumer has a credit line. Finally, there are privately-owned credit bureaus owned by more detail below, the variables and weights may disadvantage certain types of borrowers. See, e.g" Finkelstein, supra note 260, at 36, 263 See generally STAFF OF II, The best structures are those which are comprehensive, full-file, rather than segmented, reporting from reporting bureaus
  38. The probability of mistaken characterizations of borrowers, e.g., a low-risk borrower mistaken as a high-risk borrower, occurs when insufficient infonnation is reported, Computerized Credit Scoring's Effect on the Lending Industry
  39. N C Banking, 2000, 443, 450
  40. See generally CAPRON, supra note 121
  41. & Ross, 277-286; see generally Mark Schreiner, Benefits and Pitfalls of Statistical Credit Scoring for Microflnance, 28 SAVINGS AND DEVELOPMENT 63 (discussing personal knowledge as a basis for making loan decisions in poor countries and how credit scoring can improve risk prediction), 28
  42. And Ross, 340, 10.1006/juec.1999.2146 · DOI

Cited by

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Metadata

Authors
Havard, C.
Affiliations
University of Baltimore (US)
Corresponding author
Havard, Cassandra
Venue
SSRN Electronic Journal
Publisher
Elsevier BV
Published
2010
ISSN
1556-5068 (ISSN-L)
OpenAlex
W1806306520
Cited by
7
References
0
Citations by year
2026: 1 · 2025: 1 · 2024: 1 · 2023: 1 · 2020: 1 · 2018: 1 · 2017: 1
Type
posted content
Language
en
Open access
Locations
  • SSRN Electronic Journal (acceptedVersion)
  • University of Baltimore Law Forum (submittedVersion)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Housing Market and Economics
  • Social Sciences › Sociology and Political Science › Urban, Neighborhood, and Segregation Studies
  • Social Sciences › Economics, Econometrics and Finance › Finance › Banking stability, regulation, efficiency
Keywords
subprime lending, credit scoring, mortgage discrimination, racial discrimination in lending, risk-based pricing, minority borrowers, search costs, information asymmetry, credit scoring models, regulatory failure, access to credit

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CoChat. (2026). Citation check: 'On the Take': The Black Box of Credit Scoring and Mortgage Discrimination. https://app.cochat.ai/papers/10.2139/ssrn.1710063
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Havard, C. (2010). 'On the Take': The Black Box of Credit Scoring and Mortgage Discrimination. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1710063

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