FDIC National Survey of Unbanked and Underbanked Households
| Details | Count, percentage, and percent change of households that are unbanked and underbanked by age, education, household type, and race |
|---|---|
| Topics | Unbanked Households, underbanked households |
| Source | Federal Deposit Insurance Corporation |
| Years Available | 2019 – 2023 |
| Geographies | State, CBSA |
| Public Edition or Subscriber-only | Public Edition |
| Download Available | yes |
| For more information | http://www.fdic.gov/householdsurvey/ |
| Last updated on PolicyMap | May 2025 |
Description:
Every two years, the FDIC sponsors the National Survey of Unbanked and Underbanked Households to collect data on the number of U.S. households that are unbanked and underbanked; their demographic characteristics such as household type, race/ethnicity, age, and level of education; and their reasons for being unbanked or underbanked. This survey is conducted by the U.S. Census Bureau as a special supplement to the Current Population Survey (CPS). The FDIC undertakes this effort to address a gap in the availability of comprehensive data on the number of unbanked and underbanked households in the United States.These estimates are based on data aggregated from the 2019, 2021, and 2023 surveys, pulled from the multi-year microdata published by the FDIC at https://www.fdic.gov/household-survey/data-downloads-and-resources.
Like with all estimates derived from survey data, the values published in these data layers are associated with some uncertainty. In order to help users understand the reliability of the estimates, PolicyMap published margins of error at the 90% confidence level associated with each estimate. This means that there is a 90% likelihood that if every household in the given geography was interviewed, the count or percent would be within the margin of error above or below the estimate derived from the survey sample. For example, 4.5% of households in Colorado were unbanked, with a margin of error of 1.6%. This may be expressed as 4.5% ± 1.6%, which means that there is a 90% likelihood that the true percentage of unbanked households in Colorado was between 2.9% and 6.1% (expressing the margin of error in this way is known as a “confidence interval”).
PolicyMap has also published a data flag to help users interpret these margins of error. The data flags are based on the relative standard error, or the ratio of the standard error to the count or precent. The RSE is calculated by dividing the standard error of the estimate by the estimate itself, then multiplying the result by 100. Estimates considered “reliable” have standard errors that are 15% or less of the estimate. Estimates tagged “use with caution” have standard errors between 15% and 30% of the estimate. Esimates with standard errors greater than 30% of the estimate have been suppressed.