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The Racialized Costs of “Traditional” Banking in Segregated America: Evidence from Entry-Level Checking Accounts

Abstract

A growing body of evidence shows that America’s racial geography shapes access to basic financial services (e.g. banking), highlighting a mechanism connecting segregation to economic vulnerability: spatially organized institutional marginalization.s While the practices and policies of “mainstream” commercial banks are central to this dynamic, the costs they impose on the communities they serve have been understudied. This study leverages survey data from a stratified random sample of 1344 banks across the United States to investigate variation in the costs and fees of entry-level checking accounts at commercial banks. Our evidence shows banks charge more to open and maintain checking accounts in neighborhoods and cities with larger Black and Latinx populations even after controlling for demographic and socioeconomic characteristics as well as market competition. The higher costs of banking imposed on Black and Latinx communities are further compounded by parallel disparities in income. These findings reveal the unequal costs of banking in segregated America.

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Fig. 1

Notes

  1. While this paper uses the term Latinx to inclusively acknowledge peoples of Latin American origin who do not ascribe to gender binaries, the authors recognize that the term Latinx emerged in the United States context and can represent a form of linguistic imperialism. The authors also recognize the Latine movement that originated within trans and non-binary communities of Latin America as described by Raquel Reichard (2017).

  2. A banking desert refers to a geographic area without bank or credit union branches. Research has measured banking deserts as census tracts that lack any of these financial services within a 10-mile radius from their centers (Morgan et al. 2016).

  3. We excluded credit unions because, unlike banks, they limit services to members based on employer or residency requirements and operate on a cooperative model where members are joint owners. Credit unions are also insured and regulated differently than banks. Most importantly, commercial banks are far more common and hold far more assets than credit unions, highlighting their centrality to shaping financial services environments (CUNA 2018).

  4. The full list of survey questions and response coding schemes is provided in the Appendix.

  5. Karyen Chu and Keith Ernst of the FDIC provided assistance for implementing sample stratification.

  6. Appendix Figure A1 shows a map of the branches in the sample.

  7. Bank main branch address are geocoded to census tracts using ArcGIS 10.

  8. We also explored adding additional measures of socioeconomic status, such as median household income, but doing so caused multicollinearity problems. For example, adding median household income to place-level models resulted in a Variance Inflation Factor (VIF) of 8.92.

  9. In analyses available upon request, we find substantively identical results if we replace the missing values with zeroes.

  10. Survey questions on entry-level checking account costs and fees were placed near the beginning of the survey, helping to ensure that these questions were answered before respondents were fatigued by the survey or interrupted by their job responsibilities.

  11. We identify banks as being community, small, regional, or mega/large/national in size, consistent with FDIC designations.

  12. There were 248 unique job titles recorded for survey respondents within the analytic sample (including spelling variations). For parsimony, we collapse these titles into tellers (56% of respondents), customer service representatives (26%), and other positions (18%).

  13. In models available upon request, we clustered standard errors at the state-level and included quadratic measures of population racial makeup, population density, median rent, and financial service density. The results presented here were substantively identical in these models.

  14. In results available upon request, we also separately estimated the likelihood that banks charged a regular service fee (i.e. with a binary outcome variable and logistic regression) as well as racial disparities in fee size conditional on whether banks charge fees (i.e. with a linear variable and banks without service fees excluded from the sample). These supplemental results strongly support the results presented here. Specifically, banks in communities of color are significantly more likely to charge regular service fees and those fees are larger among the banks that charge them.

  15. In results available upon request, we also estimated a series of models of regular service fees in which we included banks that did not charge fees as zeroes (rather than as missing). These supplemental results strongly support the results presented here. Specifically, even when including banks that charge no regular service fee in statistical estimates, fees are, on average, significantly larger in Black and Latinx communities even after controlling for a wide range of covariates.

  16. Black exposure to Blacks is 45.14, exposure to Asians is 3.68, and exposure to Latinx is 14.65. Corresponding exposure indices for Asians are 8.89, 22.87, and 19.51, while they are 10.48, 5.78, and 46.35 for Latinx. Rather than simply calculating binary exposure measures, we included all four racial groups, so the sum of all exposure indices (including values for the exposure to whites, which are not mentioned here) equals 100 (Reardon 2002).

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Acknowledgements

The authors thank Drs. Jackelyn Hwang, Elizabeth Roberto, and Emily Rauscher for providing feedback on an earlier version of this manuscript. The authors bear full responsibility for the paper. The data used in this manuscript were collected via a grant from MetLife Foundation to Dr. Friedline; though, the authors received no funding for analyzing the data and writing this manuscript.

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Faber, J.W., Friedline, T. The Racialized Costs of “Traditional” Banking in Segregated America: Evidence from Entry-Level Checking Accounts. Race Soc Probl 12, 344–361 (2020). https://doi.org/10.1007/s12552-020-09296-y

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Keywords

  • Banking
  • Finance
  • Checking accounts
  • Race
  • Segregation