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Exploring the Use of Credit Scores in Selection Processes: Beware of Adverse Impact

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Abstract

Purpose

The use of credit checks or credit scores in personnel selection has received widespread media attention of late. Though there is speculation that basing hiring decisions (even partially) on credit-related variables may produce or increase adverse impact, virtually no empirical literature exists to support or refute this claim. The present study explores the impact of using credit scores, in the context of a larger selection system, on adverse impact.

Design/Methodology/Approach

We conducted Monte Carlo simulations representing various real-world selection systems (i.e., multiple hurdle, multiple hurdle with cut-off score, single hurdle). In addition to applicant credit scores, each simulation included variables that organizations commonly use during selection (i.e., educational background, personality).

Findings

Results showed that in a majority of simulated hiring scenarios, using credit scores (as opposed to a random, race-neutral variable) widened the Black-White gap in hiring, producing more violations of the 4/5ths rule and statistically significant adverse impact.

Implications

These results imply that organizations should be cautious when using credit scores to evaluate potential or current employees for jobs.

Originality/Value

This is one of the first studies to provide empirical evidence of a relationship between credit scores in selection and adverse impact. The use of simulations helps organizations be proactive in regards to choosing selection practices. Our results in particular pinpoint the situations where implementing credit scores as part of a larger selection process might be most problematic in terms of adverse impact, thereby providing much needed guidance to those considering credit scores for their selection processes.

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References

  • Ababneh, K. I., Hackett, R. D., & Schat, A. C. H. (2013). The role of attributions and fairness in understanding applicant reactions to selection procedures and decisions. Journal of Business Psychology.

  • Adelman, C. (2006). The tool box revisited: Paths to degree completion from high school through college. Washington, DC: U.S. Department of Education.

    Google Scholar 

  • Agresti, A. (1992). A survey of exact inference for contingency tables. Statistical Science, 7, 131–153.

    Article  Google Scholar 

  • Arvey, R., & Renz, G. (1992). Fairness in the selection of employees. Journal of Business Ethics, 11, 331–340.

    Article  Google Scholar 

  • Avis, J. M., Kudisch, J. D., & Fortunato, V. J. (2002). Examining the incremental validity and adverse impact of cognitive ability and conscientiousness on job performance. Journal of Business Psychology, 17, 87–105.

    Article  Google Scholar 

  • Barrick, M. R., & Mount, M. K. (1991). The big five personality dimensions and job performance: A meta-analysis. Personnel Psychology, 44, 1–26.

    Article  Google Scholar 

  • Bernerth, J. B. (2012). Demographic variables and credit scores: an empirical study of a controversial selection tool. International Journal of Selection and Assessment, 20, 242–246. doi:10.1111/j.1468-2389.2012.00585.x.

    Article  Google Scholar 

  • Bernerth, J., Taylor, S., Walker, J., & Whitman, D. (2012). An empirical investigation of dispositional antecedents and performance-related outcomes of credit scores. Journal of Applied Psychology, 97, 469–478. doi:10.1037/a0026055.

    Article  PubMed  Google Scholar 

  • Berry, C. M., Gruys, M. L., & Sackett, P. R. (2006). Educational attainment as a proxy for cognitive ability in selection: Effects on levels of cognitive ability and adverse impact. Journal of Applied Psychology, 91, 696–705.

    Article  PubMed  Google Scholar 

  • Biddle, D. A. (2005). Adverse impact and test validation: A practitioner’s guide to valid and defensible employment testing. London: Gower.

    Google Scholar 

  • Biddle, D. A. (2006). Adverse impact and test validation: A practitioner’s guide to valid and defensible employment testing (2nd ed.). Burlington, VT: Ashgate Publishing Company.

    Google Scholar 

  • Biddle, D. A., & Morris, S. B. (2011). Using Lancaster’s mid-p correction to the Fisher exact test for adverse impact analyses. Journal of Applied Psychology, 96, 956–965.

    Article  PubMed  Google Scholar 

  • Bills, D. (1988). Credentials and capacities: Employers’ perceptions of the acquisition of skills. The Sociological Quarterly, 29, 439–449.

    Article  Google Scholar 

  • Bills, D. (1992). The mutability of educational credentials as hiring criteria: How employers evaluate atypically highly credentialed job candidates. Work and Occupations, 19, 79–95.

    Article  Google Scholar 

  • Birkenmaier, J., & Tyuse, S. W. (2005). Affordable financial services and credit for the poor: The foundation of asset building. Journal of Community Practice, 13, 69–85.

    Article  Google Scholar 

  • Board of Governors of the Federal Reserve System (2007, August). Report to the congress on credit scoring and its effects on the availability and affordability of credit. Retrieved from http://www.transunion.com/docs/rev/business/clientSupport/legislativeUpdate/CreditScoreRpt.pdf.

  • Bobko, P., & Roth, P. L. (2010). An analysis of two methods for assessing and indexing adverse impact: A disconnect between the academic literature and some practice. In J. L. Outtz (Ed.), Adverse impact: Implications for organizational staffing and high stakes selection (pp. 29–49). New York: Routledge.

    Google Scholar 

  • Bradley, J. P., Nicol, A. A. M., Charbonneau, D., & Meyer, J. P. (2002). Personality correlates of leadership development in Canadian forces officer candidates. Canadian Journal of Behavioral Science, 34, 92–103.

    Article  Google Scholar 

  • Brody, R. G. (2010). Beyond the basic background check: Hiring the “right” employees. Management Research Review, 33, 210.

    Article  Google Scholar 

  • Bureau of Labor Statistics (2011). Labor force characteristics by Race and Ethnicity, 2010. Retrieved on December 15, 2013 from http://www.bls.gov/cps/cpsrace2010.pdf.

  • Bureau of Labor Statistics (2012). Labor force characteristics by Race and Ethnicity, 2011. Retrieved on December 15, 2013 from http://www.bls.gov/cps/cpsrace2011.pdf.

  • Bureau of Labor Statistics (2013). Labor force characteristics by Race and Ethnicity, 2012. Retrieved on December 15, 2013 from http://www.bls.gov/cps/cpsrace2012.pdf.

  • Chideya, F. (1995). Don’t believe the hype: Fighting cultural misinformation about African Americans. New York: A Plume Book.

    Google Scholar 

  • Costa, P. T, Jr, & McCrae, R. R. (1992). NEO PI-R professional manual. Odessa, FL: Psychological Assessment Resources Inc.

    Google Scholar 

  • Darling-Hammond, L. (2004). The color line in American education: Race, resources, and student achievement. Du Bois Review, 11, 213–246.

    Google Scholar 

  • Deschenaux, J. (2011, February). States seek to limit employment-related credit checks. Retrieved from www.shrm.org/LegalIssues/StateandLocalResources/Pages/CreditChecks.aspx.

  • Devereux, P. (2002). Occupational upgrading and the business cycle. Labour, 16, 423–452.

    Article  Google Scholar 

  • Dunn, W., Mount, M., Barrick, M., & Ones, D. (1995). Relative importance of personality and general mental ability in managers’ judgments of applicant qualifications. Journal of Applied Psychology, 80, 500–509.

    Article  PubMed  Google Scholar 

  • Equal Employment Opportunity Commission. (1978). Uniform Guidelines on employment selection procedures. Federal Register, 43, 38289–38309.

    Google Scholar 

  • Equal Employment Opportunity Commission. (2010, October 10). EEOC public meeting explores the use of credit histories as employee selection criteria. Retrieved from http://www.eeoc.gov/eeoc/newsroom/release/10-20-10b.cfm.

  • Finch, D. M., Edwards, B. D., & Wallace, J. C. (2009). Multistage selection strategies: Simulating the effects on adverse impact and expected performance for various predictor combinations. Journal of Applied Psychology, 94, 318–340.

    Article  PubMed  Google Scholar 

  • Fine, J., & Davis, J. (2003). Grade retention and enrollment in post-secondary education. Journal of School Psychology, 41, 401–411.

    Article  Google Scholar 

  • Foldes, H. J., Duehr, E. E., & Ones, D. S. (2008). Group differences in personality: Meta-analyses comparing five U.S. racial groups. Personnel Psychology, 61, 579–616.

    Article  Google Scholar 

  • Freeman, C., & Fox, M. A. (2005). Status and trends in the education of American Indians and Alaska Natives. NCES Publication No. 2005-108. Washington, DC: National Center for Education Statistics.

  • Gallagher, K. (2006). Rethinking the fair credit reporting act: When requesting credit reports for “employment purposes” goes too far. Iowa Law Review, 91, 1593.

    Google Scholar 

  • Guion, R. M. (1998). Assessment, measurement, and prediction for personnel decisions. Mahwah, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Gurchiek, K. (2011, November). SHRM: Credit checks are legitimate screening tool. Retrieved from www.shrm.org/about/news/Pages/LegitimateScreeningTool.aspx.

  • Hargis, M. B., Baltes, B. B., Friend, Y., & Levi, A. (2006). Race differences in termination at work: The role of educational inequality. Journal of Business Psychology, 20, 587–598.

    Article  Google Scholar 

  • Hough, L., Oswald, F., & Ployhart, R. (2001). Adverse impact and group differences in constructs, assessment tools, and personnel selection procedures: Issues and lessons learned. International Journal of Selection and Assessment, 9, 152–194.

    Article  Google Scholar 

  • Hughes, R. (2003). Skill or diploma? The potential influence of skill-based pay systems on sources of skills acquisition and degree programs. Work Study, 52, 179–183.

    Article  Google Scholar 

  • Hurtz, G. M., & Donovan, J. J. (2000). Personality and job performance: The big five revisited. Journal of Applied Psychology, 85, 869–879. doi:10.1037//0021-9010.85.6.869.

    Article  PubMed  Google Scholar 

  • James, E. H., & Wooten, L. P. (2006). Diversity crises: How firms manage discrimination lawsuits. Academy of Management Journal, 49, 1103–1118. doi:10.5465/AMJ.2006.23478091.

    Article  Google Scholar 

  • Judge, T. A., & Ilies, R. (2002). Relationship of personality to performance motivation: A meta-analytic review. Journal of Applied Psychology, 87, 797–807.

    Article  PubMed  Google Scholar 

  • Karpoff, J., & Lott, J. (1993). The reputational penalty firms bear from committing criminal fraud. Journal of Law and Economics, 36, 757–802.

    Article  Google Scholar 

  • Kuhn, K. M., & Nielsen, M. L. (2008). Understanding applicant reactions to credit checks: Uncertainty, information effects and individual differences. International Journal of Selection and Assessment, 16, 307–320. doi:10.1111/j.1468-2389.2008.00437.x.

    Article  Google Scholar 

  • Löckenhoff, C. E., Terracciano, A., Bienvenu, O., Patriciu, N. S., Nestadt, G., McCrae, R. R., et al. (2008). Ethnicity, education, and the temporal stability of personality traits in the East Baltimore epidemiologic catchment area study. Journal of Research in Personality, 42, 577–598. doi:10.1016/j.jrp.2007.09.004.

    Article  PubMed Central  PubMed  Google Scholar 

  • Lotokowski, V. A., Robbins, S. B., & Noeth, R. J. (2004). The role of academic and non-academic factors in improving college retention. Iowa: American College Testing.

    Google Scholar 

  • Marcus, B., Lee, K., & Ashton, M. C. (2007). Personality dimensions explaining relationships between integrity tests and counterproductive behavior: Big five, or one in addition? Personnel Psychology, 60, 1–34.

    Article  Google Scholar 

  • McDaniel, A., DiPrete, T., Buchmann, C., & Shwed, U. (2011). The black gender gap in educational attainment: Historical trends and racial comparisons. Demography, 48, 889–914.

    Article  PubMed  Google Scholar 

  • Nelson, A. A. (2010). Credit scores, race, and residential sorting. Journal of Policy Analysis and Management, 29, 39–68. doi:10.1002/pam.20478.

    Article  Google Scholar 

  • Nielsen, M., & Kuhn, K. (2009). Late payments and Leery applicants: Credit checks as a selection test. Employee Responsibilities and Rights Journal, 21, 115–130.

    Article  Google Scholar 

  • Ones, D. S., & Anderson, M. (2002). Gender and ethnic group differences on personality scales in selection: Some British data. Journal of Occupational and Organizational Psychology, 75, 255–276.

    Article  Google Scholar 

  • Outtz, J. A. (Ed.). (2009). Adverse Impact: Implications for organizational staffing and high stakes selection. New York: Routledge.

    Google Scholar 

  • Pfeffer, J. (1998). The human equation: Building profits by putting people first. Boston: Harvard Business School Press.

    Google Scholar 

  • Ployhart, R. E., & Holtz, B. C. (2008). The diversity–validity dilemma: Strategies for reducing racioethnic and sex subgroup differences and adverse impact in selection. Personnel Psychology, 61, 153–172. doi:10.1111/j.1744-6570.2008.00109.x.

    Article  Google Scholar 

  • Pruitt, S. W., & Nethercutt, L. L. (2002). The Texaco racial discrimination case and shareholder wealth. Journal of Labor Research, 23, 685–693.

    Article  Google Scholar 

  • Risavy, S. D., & Hausdorf, P. A. (2011). Personality testing in personnel selection: Adverse impact and differential hiring rates. International Journal of Selection and Assessment, 19, 18–30.

    Article  Google Scholar 

  • Roberts, B. (2011). Your cheating heart. HR Magazine, 56, 55–60.

    Google Scholar 

  • Robertson, I., & Smith, M. (2001). Personnel selection. Journal of Occupational and Organizational Psychology, 74, 441–472.

    Article  Google Scholar 

  • Roscigno, V., & Ainsworth-Darnell, J. (1999). Race, cultural capital, and educational resources: Persistent inequalities and achievement returns. Sociology of Education, 72, 158–178.

    Article  Google Scholar 

  • Roth, P. L., Bobko, P., & Switzer, F. S. (2006). Modeling the behavior of the 4/5ths rule for determining adverse impact: Reasons for caution. Journal of Applied Psychology, 91, 507–522.

    Article  PubMed  Google Scholar 

  • Rothstein, M. G., & Goffin, R. D. (2006). The use of personality measures in personnel selection: What does current research support? Human Resource Management Review, 16, 155–180. doi:10.1016/j.hrmr.2006.03.004.

    Article  Google Scholar 

  • Sackett, P. R., & Ellingson, J. E. (1997). The effects of forming multi-predictor composites on group differences and adverse impact. Personnel Psychology, 50, 707–721. doi:10.1111/j.1744-6570.1997.tb00711.x.

    Article  Google Scholar 

  • Schmitt, N., Rogers, W., Chan, D., Sheppard, L., & Jennings, D. (1997). Adverse impact and predictive efficiency of various predictor combinations. Journal of Applied Psychology, 82, 719–730. doi:10.1037/0021-9010.82.5.719.

    Article  Google Scholar 

  • Siskin, B. R., & Trippi, J. (2005). Statistical issues in litigation. In F. J. Landy (Ed.), Employment discrimination litigation: Behavioral, quantitative, and legal perspectives (pp. 132–166). San Francisco: Jossey-Bass.

    Google Scholar 

  • Smith, A. (2007, March). EEOC urges caution on unnecessary credit checks. Retrieved from www.shrm.org/Publications/HRNews/Pages/CMS_020975.aspx.

  • Society for Human Resource Management (SHRM) (2010, January 22). Background checking: Conducting credit background checks. Retrieved from http://www.shrm.org/Research/SurveyFindings/Articles/Pages/BackgroundChecking.aspx.

  • Terpstra, D., Mohamed, A., & Kethley, R. (1999). An analysis of federal court cases involving nine selection devices. International Journal of Selection and Assessment, 7, 26–34.

    Article  Google Scholar 

  • Tett, R. P., & Christiansen, N. D. (2007). Personality tests at the crossroads: A response to Morgeson, Campion, Dipboye, Hollenbeck, Murphy, and Schmitt (2007). Personnel Psychology, 60, 967–993.

    Article  Google Scholar 

  • Tett, R. P., Jackson, D. N., & Rothstein, M. (1991). Personality measures as predictors of job performance: A meta-analytic review. Personnel Psychology, 44, 703–742.

    Article  Google Scholar 

  • Tews, M., Michel, J., & Lyons, B. (2010). Beyond personality: The impact of GMA on performance for entry-level service employees. Journal of Service Management, 21, 344–362.

    Article  Google Scholar 

  • Thompson, M. S., Gorin, J. S., Obeidat, K., & Chen, Y.-H. (2006). Understanding differences in postsecondary educational attainment: A comparison of predictive measures for Black and White students. The Journal of Negro Education, 75, 546–562.

    Google Scholar 

  • Thurm, S. (2011, October). Next frontier in credit scores: Predicting personal behavior. Retrieved from online.wsj.com/article/SB10001424052970203687504576655182086300912.html?mod=googlenews.

  • Tracey, J., Sturman, M., & Tews, M. (2007). Ability versus personality. Cornell Hotel & Restaurant Administration Quarterly, 48, 313–322.

    Article  Google Scholar 

  • Wentling, R. M., & Palma-Rivas, N. (1997). Diversity in the workforce: A literature review (MDS 934). Berkeley, CA: National Center for Research in Vocational Education.

    Google Scholar 

  • What’s In Your FICO Score (2012) Retrieved June 2, 2012, from http://www.myfico.com/CreditEducation/WhatsInYourScore.aspx.

  • Williams, K. Z., Schaffer, M. M., & Ellis, L. E. (2013). Legal risk in selection: An analysis of processes and tools. Journal of Business and Psychology, 28(4), 401–410.

    Article  Google Scholar 

  • Wright, P., Ferris, S., Hiller, J., & Kroll, M. (1995). Competitiveness through management of diversity: Effects on stock price valuation. The Academy of Management Journal, 38, 272–287.

    Article  Google Scholar 

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Volpone, S.D., Tonidandel, S., Avery, D.R. et al. Exploring the Use of Credit Scores in Selection Processes: Beware of Adverse Impact. J Bus Psychol 30, 357–372 (2015). https://doi.org/10.1007/s10869-014-9366-5

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