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Cited by 9

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Do Credit‐Based Insurance Scores Proxy for Income in Predicting Auto Claim Risk?

Morris, Darcy Steeg, Schwarcz, Daniel, Teitelbaum, Joshua C.·2017·Journal of Empirical Legal Studies
DOI 10.1111/jels.12151
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Abstract

Property and casualty insurers often use credit‐based insurance scores in their underwriting and rating processes. The practice is controversial—many consumer groups oppose it, and most states regulate it, in part out of concern that insurance scores proxy for policyholder income in predicting claim risk. We offer new evidence on this issue in the context of auto insurance. Prior studies on the subject suffer from the limitation that they rely solely on aggregate measures of income, such as the median income in a policyholder's census tract or zip code. We analyze a panel of households that purchased auto and home policies from a U.S. insurance company. Because we observe the households’ home policies as well as their auto policies, we are able to employ two measures of income: the median income in a household's census tract, an aggregate measure, and the insured value of the household's dwelling, a policyholder‐level measure. Using these measures, we find that insurance scores do not proxy for income in a standard actuarial model of auto claim risk.

Overview

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Registry

Crossref · 10.1111/jels.12151

Cites

26 of 26 references verified0 citation errors · 0 not checkable

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Verification

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Citations

Cites

Research works printed but not linked: 3

  1. Avraham Ronen, 2014, Understanding Insurance Discrimination, Southern California Law Rev, 87, 195
  2. Hunter J. Robert TomFeltner &DouglasHeller(2013) “What Works: A Review of Auto Insurance Rate Regulation in America and How Best Practices Save Billions of Dollars ” Consumer Federation of America http://www.consumerfed.org/pdfs/whatworks-report_nov2013_hunter-feltner-heller.pdf.
  3. National Conference of Insurance Legislators (NCOIL)(2009) “Model Act Regarding Use of Credit Information in Personal Insurance ”http://www.ncoil.org/Private/2009/Docs/07172009CreditScoringModel.pdf.

Cited by

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Metadata

Authors
Morris, D. S., Schwarcz, D., & Teitelbaum, J. C.
Venue
Journal of Empirical Legal Studies
Publisher
Wiley
Published
2017-04-25
Volume
14
Issue
2
Pages
397-423
ISSN
  • 1740-1453
  • 1740-1461
DOI
10.1111/jels.12151
Cited by
9
References
26
Language
en
Licence
Funders
National Science Foundation (SES‐1031136)

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.