2019 FDIC Survey of Household Use of Banking and Financial Services | 57

How America Banks: 

Household Use of Banking and Financial Services

Appendix 1. FDIC Technical Notes

1

 See, for example, U.S. Census Bureau, Current Population Survey: Design and Methodology, Technical Paper 77 (October 2019), census.gov/programs-surveys/

cps/methodology/CPS-Tech-Paper-77.pdf.

2 California and New York State are each divided into two areas that have independent sample designs: Los Angeles County and the remainder of California, 

and New York City (five boroughs) and the remainder of New York State.

3

 The precision targets that are the basis for the sample design of the CPS are provided in Chapter 2-2 of U.S. Census Bureau, Current Population Survey: Design 

and Methodology, Technical Paper 77.

4 CPS respondents that specified they had some level of participation in their household finances but that did not answer or responded “don’t know” to 

question B20 would have also been considered Supplement respondents if they had used a bank prepaid card at the time of the survey (i.e., had responded 

“yes” to questions P10, PW10D, and PBUSE). However, no CPS respondent fell into this category. CPS respondents involved in their household finances 

include respondents in households where adults had separate finances or where the respondent was the only adult in the household. For households where 

adults shared finances or had a mix of shared and separate finances, respondents were asked to specify how much they participated in their household 

financial decisions. Only those that reported having at least some level of participation were considered to be involved in their household finances. 

5 For details on the sampling frame, refer to the technical documentation for the June 2019 Supplement, available at census.gov/programs-surveys/cps/

technical-documentation/complete.html.

The data for this report were collected through an 

FDIC-sponsored supplement (Supplement) to the Current 

Population Survey (CPS) for June 2019. The CPS, conducted by the U.S. Census Bureau for the Bureau of Labor 

Statistics (BLS), is a monthly survey with about 59,000 

households selected for interview each month. The survey is based on a scientific sample that is representative 

of the U.S. civilian noninstitutional population, aged 

15 or older.

The CPS is the primary source of information on the labor 

force characteristics of the U.S. population, including 

employment, unemployment, and earnings statistics. It 

also collects data on a variety of demographic characteristics, such as age, sex, race, marital status, and educational attainment. Additional information about the CPS 

is provided on the Census Bureau’s website.1

The CPS sample consists of independent samples in each 

state and the District of Columbia.2 The sample size for 

each state is set to meet specific precision requirements 

for the unemployment rate estimate.3

2019 Supplement

The sixth Supplement was conducted in June 2019. 

Previous Supplements were conducted in January 2009, 

June 2011, June 2013, June 2015, and June 2017. A primary 

purpose of the Supplement is to estimate the percentage 

of U.S. households that are “unbanked” and to identify the reasons why. The Supplement has also collected 

information since 2009 on household use of a variety of 

bank and nonbank financial transaction services and 

credit products. The Supplement survey instrument used 

in 2019, attached as Appendix 3, included approximately 

60 questions designed to provide this information.

The 2019 instrument was developed in conjunction with 

experts from a nationally recognized survey research 

firm. Consumer focus groups were conducted to assist 

in question development, and the survey instrument 

underwent two rounds of cognitive testing. For a detailed 

description of the 2019 revisions, see Appendix 2. 

Because of changes in the questionnaire, direct comparisons between 2019 and prior-year estimates are not 

possible in some cases.

Eligibility and Exclusions

All households that participated in the June 2019 CPS 

were eligible to participate in the Supplement. However, 

only CPS respondents that specified they had some level 

of participation in their household finances and that 

responded “yes” or “no” to whether someone in their 

household had a checking or savings account (question 

B20) were considered Supplement respondents.4

CPS Response Rate and Coverage Ratio

For the June 2019 CPS, a statistical sample of 59,320 survey-eligible households was selected from the sampling 

frame.5 Of these households, 48,863 participated in the 

CPS, resulting in an 82 percent response rate. There were 

10,457 nonrespondent eligible households, most of which 

refused to participate (83 percent). The remaining 17 percent consisted of households where (a) no one was home 

at the time of the interview, (b) the household respondent 

was temporarily absent, (c) the household could not be 

located, (d) language barriers prevented the interview, or 

(e) other reasons. Because of the availability of translators for many languages, only one percent of nonrespondents (106 households) did not participate as a result of 

language barriers.
58 | 2019 FDIC Survey of Household Use of Banking and Financial Services

Coverage ratios for the CPS measure the percentage of 

persons in the target universe (the U.S. civilian noninstitutional population, aged 15 or older) that are included 

in the sampling frame.6 The overall coverage ratio for 

the June 2019 CPS was 89 percent. The missing 11 percent 

(i.e., undercoverage) consists of three groups: (a) persons 

residing in households that are not in the CPS sampling frame, (b) noninstitutional persons not residing 

in households at the time the CPS was conducted, and 

(c) household residents that were not listed as household 

members for the CPS for various reasons. The coverage 

ratios varied across demographic groups. For example, 

among women aged 15 or older, the coverage ratio was 

94 percent for Whites, 80 percent for Blacks, and 87 percent for Hispanics.

Supplement Response Rate

Of the 48,863 households that participated in the CPS, 

32,904 (67 percent) also participated in the Supplement 

(i.e., were Supplement respondents). Taking into account 

the nonresponse to the CPS, the overall response rate for 

the Supplement was 55 percent.

CPS and Supplement Weights

The weights calculated by the Census Bureau for the 

CPS and the Supplement were adjusted to account for 

both nonresponse and undercoverage. These adjustments 

help correct any biases in estimates because of nonresponse and undercoverage, so that results are representative of the U.S. civilian noninstitutional population, 

aged 15 or older.7

Supplement Item Nonresponse and Imputation

In the 2019 Supplement, nonresponse to individual 

survey questions (i.e., item nonresponse) was addressed 

through imputation, consistent with the Census Bureau’s 

treatment of missing values in the CPS.8 For a given 

Supplement question, item nonresponse occurred when a 

Supplement respondent refused to answer the question, 

6 The coverage ratio is the weighted number of persons in a demographic group (after weights are adjusted to account for household nonresponse) divided 

by an independent count of persons in that demographic group (obtained from the 2010 Census and updated with data on the components of population 

change, including births, deaths, and net migration).

7 For details on the weighting procedure, refer to the technical documentation for the June 2019 Supplement, available at census.gov/programs-surveys/

cps/technical-documentation/complete.html. The household weight is generally the weight of the householder/reference person; however, if the 

householder/reference person is a married male, the spouse’s weight is used.

8 A description of the methodology used by the Census Bureau to impute missing values in the CPS is provided in Chapter 3-4 of U.S. Census Bureau, Current 

Population Survey: Design and Methodology, Technical Paper 77.

9 As mentioned earlier, 67 percent of the households that participated in the CPS were Supplement respondents. The remaining households (i.e., Supplement 

nonrespondents) had missing values for all Supplement questions. These households, which were not assigned a Supplement weight, did not have missing 

values imputed.

10 See Rebecca R. Andridge and Roderick J. A. Little, A Review of Hot Deck Imputation for Survey Non-response, International Statistical Review 78, No. 1 

(2010), 40-64, dx.doi.org/10.1111%2Fj.1751-5823.2010.00103.x.

11 The raw dataset, available at census.gov/programs-surveys/cps/data.html, contains an allocation flag for each Supplement question. For example, 

HXP10 is the allocation flag for question P10. Each allocation flag takes the value of -1 if the household is not in the universe for the Supplement question, 

one if the household has an allocated value (i.e., a missing value was imputed with hot deck allocation or allocated according to an edit rule), or two if the 

household does not have an allocated value (i.e., no missing value).

responded “don’t know,” or dropped out of the Supplement before the question was administered (i.e., the 

household broke off).9 Breakoffs were the most common 

source of item nonresponse.

The Census Bureau implemented “hot deck” allocation for nearly all missing values in the Supplement. 

For a household with a missing value to a given question, hot deck allocation replaced the missing value 

with a response to the same question provided by a 

household with similar characteristics, known as the 

donor household. In general, the characteristics used 

to identify donor households should be associated with 

the outcome variable, Y, and with the indicator variable 

for whether Y is missing. Identifying donors according 

to these criteria reduces both the bias and the variance 

of household estimates.10 Examples of variables used 

to select donor households in the 2019 Supplement 

included household bank account ownership, household income, and the race and age of the householder/

reference person (i.e., the person that owns or rents 

the home).

Some missing values were not imputed with hot deck 

allocation but were instead allocated according to an 

edit rule. For example, an edit rule was applied to households with (a) a missing value for having accessed a bank 

account with a bank teller in the past 12 months (question BA10A) and (b) a response of “no” for having visited 

a bank branch in the past 12 months (question BR10). For 

these households, the missing value for question BA10A 

was set to “no.”

For nearly all questions, item nonresponse due to a breakoff, a response of “don’t know,” or a refusal was treated as a missing value and was imputed.11 For questions 

A20 (satisfaction with banks) and A40 (clarity of banks’ 

communications about account fees), “don’t know” was 

considered a valid response. Therefore, missing values to 
2019 FDIC Survey of Household Use of Banking and Financial Services | 59

these questions due to a breakoff or refusal were imputed to one of the four explicit answer choices detailed on 

the questionnaire or to “don’t know.” Supporting the 

inclusion of “don’t know” as a valid response for these 

questions, unbanked households were much more likely 

to respond “don’t know” to these questions than they 

were to other Supplement questions. Moreover, qualitative research conducted by the FDIC found that many 

unbanked households lacked familiarity with banks.12

Missing values in previous Supplements were not imputed. The analysis presented in previous survey reports 

handled item nonresponse in different ways. In some 

cases, households with a missing value were dropped 

when computing an estimate, while in other cases, 

households with a missing value were retained and 

reported as “unknown.” The 2019 survey report contains 

many estimated changes in outcome variables between 

2017 and 2019. To avoid bias in these estimates for cases 

where missing values had been retained in previous 

survey years, missing values for earlier survey years were 

dropped from the analysis in the 2019 report.13

Analysis of Supplement Survey Results

Estimating the Share and Number of Unbanked Households

Using Supplement survey results, households were classified as unbanked if they responded “no” to question 

B20, “Do you or anyone else in your household have a 

checking or savings account now?”14 The proportion of 

U.S. households that were unbanked was estimated by 

dividing the sum of the weights of the household respondents that were identified as being unbanked by the sum 

of the weights of all household respondents. For estimated proportions of unbanked households for demographic 

subgroups, the same computational approach was used 

and applied to respondent households in the subgroup.

12 See Federal Deposit Insurance Corporation, Bank Efforts to Serve Unbanked and Underbanked Consumers: Qualitative Research (May 25, 2016), fdic.gov/

consumers/community/research/QualitativeResearch_May2016.pdf.

13 In the 2019 report, missing values for prepaid card use; nonbank money order, check cashing, and international remittance use; mobile phone, 

smartphone, and home internet access; and overall nonbank credit use and specific nonbank credit product use (i.e., pawn shop loan, payday loan, tax 

refund anticipation loan, rent-to-own service, and auto title loan use) were dropped for 2017 and 2015. For the primary method used to access bank 

accounts, households with missing values for methods used to access bank accounts (but not on the primary method) were dropped in previous reports. 

In the 2019 report, missing values for the primary method used to access bank accounts for 2017 and 2015 were retained to preserve consistency with 

estimates in previous reports; dropping these missing values had an immaterial effect on the estimates. Likewise, for bank branch visits, households 

with missing values for having visited a bank branch (but not on the frequency of bank branch visits) were dropped in the 2017 report (the first time these 

questions were asked). In the 2019 report, missing values for the frequency of bank branch visits for 2017 were retained to preserve consistency with 

estimates in the 2017 report; dropping these missing values had an immaterial effect on the estimates.

14 Of the 32,904 households that participated in the Supplement, 1,611 were unbanked. The skip patterns in the Supplement survey instrument (see 

Appendix 3) were such that certain questions were not asked of the 40 unbanked households that used a bank prepaid card at the time of the survey (i.e., 

unbanked households that responded “yes” to questions P10, PW10D, and PBUSE) but were asked of the remaining unbanked households. Accordingly, the 

analyses of previous and recent bank account ownership (questions UB10 and UB15), interest in having a bank account (question UB50), and reasons for not 

having a bank account (questions UB55 and UB60) in section 3 excluded the aforementioned 40 unbanked households. The analyses of satisfaction with 

banks (question A20) and clarity of banks’ communications about account fees (question A40) in section 3 also excluded these 40 households because they 

were asked different versions of the questions than other unbanked households (see Appendix 3).

15 See U.S. Census Bureau, Current Population Survey/Housing Vacancy Survey Table 13a Monthly Household Estimates: 2000 to Present, Vintage 2019 (July 28, 

2020), census.gov/housing/hvs/data/hist_tab_13a_v2019.xlsx.

16 In a few cases, the householder/reference person is classified as an ineligible respondent for the CPS, but another eligible household resident participated 

in the CPS and in the Supplement. In these cases, we use the attributes of the eligible respondent to characterize the household. 

In addition to presenting estimated proportions, the 

report includes estimated numbers of unbanked and 

banked households. The number of households for a 

given category is estimated as the sum of the weights of 

the sample households in that category. For the entire 

Supplement sample of 32,904 respondent households, 

the sum of the household weights is roughly 131.2 million, which would be an estimate of all U.S. households 

as of June 2019. The Housing Vacancy Survey, another 

survey related to the CPS that uses household controls 

to produce household weights, provided an estimate 

of 122.3 million as the number of households in June 

2019.15 This difference (131.2 million versus 122.3 million) 

is because household weights prepared by the Census 

Bureau for the CPS and for the Supplement are generally the reference person weights and are not adjusted to 

align with household count controls. Household count 

controls were not used to adjust household weights 

because the CPS is a person-level survey rather than a 

household-level survey; therefore, population controls 

were used only in the preparation of person weights. As a 

result, the sum of household weights for a category tends 

to be somewhat higher than the actual household count 

for the category.

Assigning Household Characteristics

This report also contains a number of tables for which 

unbanked rates and other household statistics are 

computed for subgroups defined by a particular socioeconomic or demographic characteristic. The household classification of a socioeconomic or demographic 

variable that is defined at the person level rather than 

the household level (e.g., race/ethnicity, education, or 

employment status) is based on the socioeconomic or 

demographic classification of the householder/reference 

person.16
60 | 2019 FDIC Survey of Household Use of Banking and Financial Services

The Census Bureau classifies households into different household types. For instance, a family household 

is a household that includes two or more people related 

by birth, marriage, or adoption and residing together, 

along with any unrelated people that may be residing 

there. Detailed definitions regarding household types 

can be found in the technical documentation on the 

CPS website.17

Classifying Household Race and Ethnicity

Consistent with U.S. Office of Management and Budget 

(OMB) standards for the classification of race and ethnicity and with CPS tabulations of race and ethnicity, 

households are classified into the following racial and 

ethnic categories:18

• “Hispanic household” refers to a household for which 

the householder identifies as Hispanic or Latino 

regardless of race.

• “Black household” refers to a household for which the 

householder identifies as Black or African American 

alone and not Hispanic or Latino.

• “Asian household” refers to a household for which the 

householder identifies as Asian alone and not Hispanic or Latino.

• “American Indian or Alaska Native household” refers 

to a household for which the householder identifies 

as American Indian or Alaska Native alone and not 

Hispanic or Latino.

• “Native Hawaiian or Other Pacific Islander household” refers to a household for which the householder 

identifies as Native Hawaiian or Other Pacific Islander 

alone and not Hispanic or Latino.

• “White household” refers to a household for which the 

householder identifies as White alone and not Hispanic or Latino.

17 See census.gov/programs-surveys/cps/technical-documentation/subject-definitions.html.

18 For the OMB standards for the classification of race and ethnicity, see Revisions to the Standards for the Classification of Federal Data on Race and 

Ethnicity, Federal Register 62, No. 210 (October 30, 1997), 58782-58790, govinfo.gov/content/pkg/FR-1997-10-30/pdf/97-28653.pdf. For information on CPS 

tabulations of race and ethnicity, see bls.gov/cps/definitions.htm. All estimates presented in the 2019 report, including 2017 and 2015 estimates provided 

for comparative purposes, use these racial and ethnic categories. Estimates presented in the 2009–2017 reports used different racial and ethnic categories; 

see Appendix 1 of the 2017 report, available at economicinclusion.gov/downloads/2017_FDIC_Unbanked_HH_Survey_Report.pdf. 

19 Specifically, we use the variable PEMLR (monthly labor force recode) to determine if the respondent is not in the labor force because of a disability. Refer 

to the CPS Data Dictionary for detail on the six-question disability sequence, available at census.gov/data/datasets/time-series/demo/cps/cps-basic.html.

20 A universally accepted method to identify the population with disabilities does not exist. Key estimates from the Supplement, such as the unbanked 

rate among disabled households, are qualitatively similar using alternative disability measures. For more information, see Appendix I of the 2013 report, 

available at economicinclusion.gov/surveys/2013household/documents/2013_FDIC_Unbanked_HH_Survey_Appendix.pdf.

21 For the February 2013 delineations, see Office of Management and Budget, OMB Bulletin Number 13-01 (February 28, 2013), whitehouse.gov/sites/

whitehouse.gov/files/omb/bulletins/2013/b13-01.pdf. For the June 2003 delineations, see Office of Management and Budget, OMB Bulletin Number 03-04

(June 6, 2003), whitehouse.gov/wp-content/uploads/2017/11/bulletins_b03-04.pdf. In each year between 2003 and 2009, OMB published minor revisions to 

the MSA delineations, based on the Census Bureau’s annual population estimates.

22 The technical documentation for the June 2015 Supplement is available at census.gov/programs-surveys/cps/technical-documentation/complete.html.

• “Two or More Races household” refers to a household 

for which the householder identifies as two or more 

races and not Hispanic or Latino.

Classifying Working-Age Households With Disabilities

This report provides unbanked and other estimates for 

the population of households with disabilities. As in the 

2013 report (the first time these estimates were presented) and later reports, households are categorized as follows: if the householder is between the ages of 25 and 64 

and either (a) indicates “yes” to any of the six-question 

disability sequence in the CPS or (b) is classified as “not 

in labor force—disabled,” the household is classified as 

“disabled, aged 25 to 64.”19 If the householder is between 

the ages of 25 and 64 and neither condition (a) nor 

(b) above is met, the household is classified as “not disabled, aged 25 to 64.” If the householder is not between 

the ages of 25 and 64, the household is classified as “not 

applicable (not aged 25 to 64).”20

Metropolitan Statistical Area Definitions

This report presents estimates of unbanked rates and 

other outcomes of interest for larger metropolitan statistical areas (MSAs). MSA delineations are established by 

OMB. OMB published a revised set of MSA delineations in 

February 2013, based on data from the 2010 Census and 

the 2006–2010 American Community Surveys. The 2013 

delineations superseded the earlier delineations based on 

2000 Census data, first established by OMB in June 2003.21

As discussed in the technical documentation to the June 

2015 Supplement, the Census Bureau phased the 2013 

MSA delineations into the CPS (and phased out the 2003 

delineations) over the period May 2014 to July 2015.22

Housing units first included in the CPS before May 

2014 were assigned metropolitan area codes based on 

the 2003 delineations. These metropolitan area codes 

consisted of metropolitan New England city and town 

area (NECTA) codes for New England states (Connecticut, 
2019 FDIC Survey of Household Use of Banking and Financial Services | 61

Maine, Massachusetts, New Hampshire, Rhode Island, 

and Vermont) and MSA codes for other states.23 Housing units first included in the CPS in May 2014 or later 

were assigned metropolitan area codes based on the 2013 

delineations. These metropolitan area codes consisted only of MSA codes, as housing units in New England 

were given MSA codes as part of the phase-in of the 2013 

delineations.

For the 2017 and 2019 survey data, all housing units were 

assigned metropolitan area codes based on the 2013 

delineations. For the 2015 survey data, approximately 

three-quarters of housing units were assigned metropolitan area codes based on the 2013 delineations, while 

the remaining housing units were assigned metropolitan 

area codes based on the 2003 delineations. To facilitate 

MSA-level estimates using the 2015 survey data, a housing unit with an obsolete 2003 MSA code was assigned 

the corresponding 2013 MSA code.24 A housing unit with a 

NECTA code was assigned the 2013 MSA code that comprised the majority of the NECTA population.25 Overall, 

less than three percent of housing units in the 2015 survey data were affected by these adjustments.

For the 2013 and earlier survey data, all housing units 

were assigned metropolitan area codes based on the 

2003 delineations. For these survey years, metropolitan area estimates are based on the 2003 delineations. 

Because of changes in geographic boundaries (e.g., the 

addition or subtraction of a county), some metropolitan area estimates that use 2015–2019 survey data are 

not directly comparable to the corresponding metropolitan area estimates that use 2013 and earlier survey 

data. In the appendix tables (published separately on 

economicinclusion.gov), a tilde (~) next to an MSA name 

indicates that the MSA was affected by a geographic 

23 Unlike MSAs, which are composed of one of more full counties or county equivalents, NECTAs are composed of cities and towns and often do not follow 

county boundaries.

24 In the 2015 survey data, some housing units were located in counties populous enough to be identified, but no MSA code was assigned because these 

counties were not in an MSA based on the 2003 delineations (all of these housing units were first included in the CPS before May 2014). Because some of 

these counties were in an MSA based on the 2013 delineations, a 2013 MSA code was assigned to housing units located in such counties.

25 For example, housing units with a NECTA code for Boston-Cambridge-Quincy, MA-NH, were assigned the MSA code for Boston-Cambridge-Newton, 

MA-NH. For each NECTA code in the 2015 survey data, at least 80 percent of the 2010 Census NECTA population (and the estimated July 1, 2015, NECTA 

population) resided within the corresponding MSA, and for the majority of the NECTAs this number was at least 90 percent.

26 For a detailed description of the methodology used to calculate standard errors based on sample replicates, see Chapter 2-4 of U.S. Census Bureau, Current 

Population Survey: Design and Methodology, Technical Paper 77.

boundary change. All MSA names in the tables, however, 

reflect the 2013 delineations.

Statistical Precision of Estimates

To indicate the precision of certain estimates, standard 

errors were calculated based on the variation of the estimates across a set of 160 sample replicates provided by 

the Census Bureau. Details of the calculation of standard errors based on sample replicates (and on the CPS 

methodology in general) are available from the Census 

Bureau.26

Estimated differences discussed in this report are significant at the 10 percent level, unless noted otherwise. 

That is, if the population difference were zero, then the 

probability of obtaining estimates having the observed 

difference or a larger difference would be no more than 

10 percent and could be considerably less. For example, 

the estimated difference in the proportions of U.S. households that were unbanked between 2019 (5.4 percent) and 

2017 (6.5 percent) is -1.1 percentage points. The estimated 

standard error of this difference (computed using the 160 

replicates as described above) is 0.2 percentage points. 

Under the assumption that the true difference in the 

unbanked rate between 2019 and 2017 is zero, the probability of observing the -1.1 percentage point difference 

in our sample data is less than 0.1 percent (the p-value 

reported by statistical software is 0.000).

Certain 2019 report appendix tables include 90 percent 

confidence intervals in addition to point estimates. The 

confidence interval is one way to describe the uncertainty surrounding the estimate. For example, as shown 

in Appendix Table A.2, the estimated proportion of U.S. 

households that were unbanked in 2019 is 5.4 percent, 

and the 90 percent confidence interval around this estimate ranges from 5.1 to 5.6 percent.
62 | 2019 FDIC Survey of Household Use of Banking and Financial Services

How America Banks: 

Household Use of Banking and Financial Services

Appendix 2. 2019 Revisions to the FDIC Survey of Household Use of Banking and Financial Services

The FDIC revised the survey instrument based on lessons learned from the administration of the 2017 survey, 

feedback received in response to the 2017 survey results, 

and an interest in topics not covered in past surveys. For 

example, the 2019 survey included new questions on use 

of nonbank bill payment services and peer-to-peer or 

person-to-person (P2P) payment services in the past 

12 months; frequency of use of nonbank money orders, 

check cashing, bill payment services, and international 

remittances; satisfaction with banks; and perceptions of 

the clarity of banks’ communications about account fees.

To accommodate new questions in the 2019 survey, 

several questions from the 2017 survey were dropped. 

For example, the 2019 survey did not include questions 

on use of a mobile phone for specific banking activities 

in the past 12 months (e.g., remote deposit capture) or on 

income receipt or bill payment in a typical month.

Specific revisions to the 2019 survey are described below.

Bank Account Ownership

The question on previous bank account ownership (2017 

Q3, 2019 UB10), which had been asked of all unbanked 

households in 2017, was asked in 2019 only of unbanked 

households that did not use a bank prepaid card at the 

time of the survey.

A question on which adults in the household had a bank 

account was broadened to include bank prepaid cards if 

the household used a bank prepaid card at the time of 

the survey (2017 Q2a, 2019 B30). A follow-up question on 

the specific types of accounts owned by each adult (2017 

Q2b) was dropped, as was a question on whether a banked 

household did not have an account at some point in the 

past 12 months (2017 Q2e).

Interest in Having a Bank Account and Reasons for Not 

Having a Bank Account

All questions in 2017 that had been asked of unbanked 

households were asked in 2019 of unbanked households 

that did not use a bank prepaid card at the time of the 

survey.

The 2019 survey included a new question on interest 

in having a bank account (2019 UB50). This question 

replaced a question on the likelihood of opening a bank 

account in the next 12 months (2017 Q7).

Three response options on reasons for not having a bank 

account (2017 Q5, 2019 UB55) were revised: 

• “Because bank account fees are unpredictable” 

was changed to “Because bank account fees are too 

unpredictable.”

• “Because banks do not offer products or services you 

need” was changed to “Because banks do not offer 

products and services you need.”

• “Because you do not have enough money to keep 

in an account” was changed to “Because you don’t 

have enough money to meet minimum balance 

requirements.”

Response options on the main reason for not having a 

bank account (2017 Q6, 2019 UB60) were revised to be 

consistent with 2019 UB55.

Prepaid Cards

The introductory language for the questions on prepaid 

card use was revised. The second sentence, “Prepaid 

cards allow you or others, like relatives or a government agency, to load funds that can later be spent,” 

was changed to “Prepaid cards allow you or others, like 

relatives, an employer, or a government agency, to load 

or reload funds that can later be spent.” The fourth (final) 

sentence, “I am not asking about gift cards or debit cards 

linked to a checking account,” was shortened to “I am 

not asking about gift cards.”

The survey question on prepaid card sources (2017 Q111, 

2019 PW10) included a revised list of sources and a new 

question structure for 2019 (separate questions for each 

source instead of “mark all that apply”).

The 2019 survey responses were: 

• Employer to pay salary or wages

• Government agency

• Place or website that is not a bank

• Bank branch or bank website
2019 FDIC Survey of Household Use of Banking and Financial Services | 63

The 2017 survey responses were: 

• Bank location or bank’s website

• Store or website that is not a bank

• Government agency

• Employer payroll card

• Family or friends

• Other (Specify)

For households that used bank prepaid cards in the past 

12 months, a new, follow-up question asked whether 

these cards were used at the time of the survey (2019 

PBUSE). For households that used government prepaid 

cards in the past 12 months, a follow-up question on the 

reasons for having these cards (2017 Q112) was dropped. 

Nonbank Financial Transaction Services

The 2019 survey included new questions on use of nonbank bill payment services and P2P payment services 

in the past 12 months. Specifically, all households were 

asked whether they paid bills through a service like 

Western Union or MoneyGram (2019 NBBP10). Households 

were instructed not to include services from a bank. In 

addition, all households were asked whether they used a 

website or app that is not a bank to send or receive money 

within the United States (2019 NBP2P). Examples provided were PayPal, Venmo, and Cash App.

While the 2017 survey asked about use of bank and nonbank international remittances in the past 12 months 

(2017 Q130 and 2017 Q135), the 2019 survey asked only 

about use of nonbank international remittances in the 

past 12 months (2019 NBRM10).

For households that used nonbank money orders, check 

cashing, bill payment services, or international remittances in the past 12 months, new, follow-up questions asked whether these services were used often, 

sometimes, or rarely (2019 NBMO15, 2019 NBCC15, 2019 

NBBP15, and 2019 NBRM15). For households that used 

nonbank money orders often or sometimes, a new, follow-up question asked whether the money orders were 

used to pay bills (2019 NBMO16).

Satisfaction and Clarity

The 2019 survey included new questions on satisfaction 

with banks (2019 A20) and clarity of banks’ communications about account fees (2019 A40). Two versions of each 

question were administered depending on the population 

segment.

On satisfaction, unbanked households that had previously been banked and that did not use a bank prepaid 

card at the time of the survey were asked, “Now, think 

about your experience with the bank your household 

most recently had an account with. How satisfied were 

you with your bank?” Banked households, as well as 

unbanked households that used a bank prepaid card at 

the time of the survey, were asked, “Now, think about 

your experience with your household’s primary bank. 

How satisfied are you with your bank?” 

On clarity, unbanked households that did not use a bank 

prepaid card at the time of the survey were asked, “Now, 

think about banks in general. How clearly do you think 

banks communicate account fees?” Banked households, 

as well as unbanked households that used a bank prepaid 

card at the time of the survey, were asked, “How clearly 

do you think your bank communicates account fees?” 

Methods Used to Access Bank Accounts

The survey question on methods used to access bank 

accounts in the past 12 months (2017 Q2g, 2019 BA10) 

included a reworded list of methods and a new question 

structure for 2019 (separate questions for each method 

instead of “mark all that apply”).

The 2019 survey responses were: 

• Visiting a bank teller

• Using an ATM or bank kiosk

• Calling the bank

• Using a computer or tablet 

• Using a mobile phone including an app

• Any other way (Specify)

The 2017 survey responses were: 

• Bank teller

• ATM or bank kiosk

• Telephone banking through phone call or automated 

voice or touch tone

• Online banking with a laptop, desktop computer, or 

tablet such as an iPad 

• Mobile banking with text messaging, mobile app, or 

internet browser or email on a mobile phone

• Other (Specify)

Additionally, 2019 BA10 was asked of banked households, 

unbanked households that used a bank prepaid card at 
64 | 2019 FDIC Survey of Household Use of Banking and Financial Services

the time of the survey, and unbanked households that 

had a bank account in the past 12 months, while 2017 Q2g 

was asked only of banked households. Response options 

on the main account access method (2017 Q2h, 2019 BA15) 

were revised to be consistent with 2019 BA10.

A question on use of a mobile phone for specific banking 

activities in the past 12 months (2017 Q80) was dropped.

Bank and Nonbank Credit

The question on use of tax refund anticipation loans in 

the past 12 months (2017 Q124, 2019 CNBTAX) was slightly modified: the clause, “or use a tax preparation service 

in order to receive your tax refund faster than the IRS 

would provide it,” in the 2017 question was replaced with 

“This is a way to receive your tax refund faster than the 

IRS would provide it.” A question on use of other types 

of loans or lines of credit from a payday lender, auto title 

lender, pawn shop, or check casher in the past 12 months 

(2017 Q127) was dropped.

Questions on whether a household had a store credit card; 

auto loan; mortgage, home equity loan, or home equity 

line of credit; student loan; or other personal loans or 

lines of credit from a company other than a bank in the 

past 12 months (2017 Q1600b-e and 2017 Q1600g) were 

dropped. To accommodate the removal of these questions, the wording of questions on whether a household 

had a Visa, MasterCard, American Express, or Discover 

credit card (2017 Q1600a, 2019 CCC10) or a personal loan 

or line of credit from a bank (2017 Q1600f, 2019 CPL10) in 

the past 12 months were changed somewhat.27

For households that had applied for a new credit card 

or a personal loan or line of credit at a bank in the past 

12 months, the follow-up question on whether the 

household was turned down or not given as much credit 

as applied for (2017 Q163, 2019 CA15) was reworded:

27 The wording of 2019 CCC10 and 2019 CPL10 is very similar to the wording of 2015 Q160 and 2015 Q161, respectively.

• 2017 Q163: “In the past 12 months, did any lender 

or creditor turn down your or someone else in your 

household’s request for new credit or not give you as 

much credit as you applied for?”

• 2019 CA15: “Did the lender or creditor turn down this 

request for new credit or not give as much credit as 

you or someone in your household applied for?”

The question on whether a household thought about 

applying for a new credit card or a personal loan or line 

of credit at a bank but did not because of concerns about 

being turned down (2017 Q164, 2019 CA20) was also 

reworded: 

• 2017 Q164: “Was there any time in the past 12 months 

that you or someone else in your household thought 

about applying for a new credit card, or a personal 

loan or line of credit at a bank, but changed your mind 

because you thought you might be turned down?”

• 2019 CA20: “Was there any time in the past 12 months 

that you or anyone in your household thought about 

applying for a new credit card, or a personal loan or 

line of credit at a bank, but didn’t apply because of 

concerns of being turned down?”

Saving for Unexpected Expenses or Emergencies, Income 

Receipt and Bill Payment in a Typical Month, and Falling 

Behind on Bill Payments

For households that saved for unexpected expenses 

or emergencies in the past 12 months, the follow-up 

question on where the savings were kept (2017 Q171) was 

dropped.

Questions on income receipt and bill payment in a typical month (2017 Q140, 2017 Q141, and 2017 Q150) and on 

whether a household fell behind on bill payments in the 

past 12 months (2017 Q181) were dropped.