Abstract

The survey on financial literacy among the citizens of Bosnia and Herzegovina was conducted within a larger project that aims at creating the Action Plan for Consumer Protection in Financial Services.

The conclusion about the need for an Action Plan was reached by the representatives of the World Bank, the Federal Ministry of Finance, the Central Bank of Bosnia and Herzegovina, supervisory authorities for entity financial institutions and non-governmental organizations for the protection of consumer rights, based on the Diagnostic Review on Consumer Protection and Financial Literacy in Bosnia and Herzegovina conducted by the World Bank in 2009-2010. This diagnostic review was conducted at the request of the Federal Ministry of Finance, as part of a larger World Bank pilot program to assess consumer protection and financial literacy in developing countries and middle-income countries. The diagnostic review in Bosnia and Herzegovina was the eighth within this project.

The financial literacy survey, whose results are presented in this report, aims at establishing the basic situation with respect to financial literacy, serving on the one hand as a preparation for the educational activities plan, and on the other as a basis for measuring the efficiency of activities undertaken.

Geographic coverage

Data collection was based on a random, nation-wide sample of citizens of Bosnia and Herzegovina aged 18 or older (N = 1036).

Analysis unit

Household, individual

Universe

Population aged 18 or older

Kind of data

Sample survey data [ssd]

Sampling procedure

SUMMARY

In Bosnia and Herzegovina, as is well known, there is no completely reliable sample frame or information about universe. The main reasons for such a situation are migrations caused by war and lack of recent census data. The last census dates back to 1991, but since then the size and distribution of population has significantly changed. In such a situation, researchers have to combine all available sources of population data to estimate the present size and structure of the population: estimates by official statistical offices and international organizations, voters? lists, list of polling stations, registries of passport and ID holders, data from large random surveys etc.

The sample was three-stage stratified: in the first stage by entity, in the second by county/region and in the third by type of settlement (urban/rural). This means that, in the first stage, the total sample size was divided in two parts proportionally to number of inhabitants by entity, while in the second stage the subsample size for each entity was further divided by regions/counties. In the third stage, the subsample for each region/county was divided in two categories according to settlement type (rural/urban).

Taking into the account the lack of a reliable and complete list of citizens to be used as a sample frame, a multistage sampling method was applied. The list of polling stations was used as a frame for the selection of primary sampling units (PSU). Polling station territories are a good choice for such a procedure since they have been recently updated, for the general elections held in October 2010. The list of polling station territories contains a list of addresses of housing units that are certainly occupied.

In the second stage, households were used as a secondary sampling unit. Households were selected randomly by a random route technique. In total, 104 PSU were selected with an average of 10 respondents per PSU. The respondent from the selected household was selected randomly using the Trohdal-Bryant scheme.

In total, 1036 citizens were interviewed with a satisfactory response rate of around 60% (table 1). A higher refusal rate is recorded among middle-age groups (table 2). The theoretical margin of error for a random sample of this size is +/-3.0%.

Due to refusals, the sample structure deviated from the estimated population structure by gender, age and education level. Deviations were corrected by RIM weighting procedure.

MORE DETAILED INFORMATION

IPSOS designed a representative sample of approximately 1.000 residents age 18 and over, proportional to the adult populations of each region, based on age, sex, region and town (settlement) type.

For this research we designed three-stage stratified representative sample. First we stratify sample at entity level, regional level and then at settlement type level for each region.

Sample universe:

Population of B&H -18+; 1991 Census figures and estimated population dynamics, census figures of refugees and IDPs, 1996. Central Election Commision - 2008; CIPS - 2008;

Sampling frame:

Polling stations territory (approximate size of census units) within strata defined by regions and type of settlements (urban and rural) Polling stations territories are chosen to be used as primary units because it enables the most reliable sample selection, due to the fact that for these units the most complete data are available (dwelling register - addresses)

Type of sample:

Three stage random representative stratified sample

Definition and number of PSU, SSU, TSU, and sampling points

• PSU - Polling station territory Definition: Polling stations territories are defined by street(s) name(s) and dwelling numbers; each polling station territory comprises approximately 300 households, with exception of the settlements with less than 300 HH which are defined as one unite. Number of PSUs in sample universe: 4710
• SSU - Household Definition: One household comprises people living in the same apartment and sharing the expenditure for food
• TSU - Respondent Definition: Member of the HH , 18+ Number of TSUs in sample universe: = 2.966.766
• Sampling points Approximately 10 respondents per one PSU, total 104

Stratification, purpose and method

• First level strata: Federation of B&H Republika Srpska Brc ko District
• Second level strata: 10 cantons 2 regions -
• Third level strata: urban and rural settlements
• Purpose: Optimisation of the sample plan, and reducing the sampling error

• Method: The strata are defined by criteria of optimal geographical and cultural uniformity

• Selection procedure of PSU, SSU, and respondent Stratification, purpose and method

• PSU Type of sampling of the PSU: Polling station territory chosen with probability proportional to size (PPS) Method of selection: Cumulative (Lachirie method)

• SSU Type of sampling of the SSU: Sample random sampling without replacement Method of selection: Random walk - Random choice of the starting point

• TSU - Respondent Type of sampling of respondent: Sample random sampling without replacement Method of selection: TCB (Trohdal-Bryant scheme)

• Sample size N=1036 respondents

• Sampling error Marginal error +/-3.0%

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey was modelled after the identical survey conducted in Romania. The questionnaire used in the Financial Literacy Survey in Romania was localized for Bosnia and Herzegovina, including adaptations to match the Bosnian context and methodological improvements in wording of questions.

Cleaning operations

Before data entry, 100% logic and consistency controls are performed first by local supervisors and once later by staff in central office.

Verification of correct data entry is assured by using BLAISE system for data entry (commercial product of Netherlands statistics), where criteria for logical and consistency control are defined in advance.

Response rate

• Nobody at home: 2,8%
• Eligible person is not home: 2,8%
• Refusal : 32,79%
• Given up after a minimum of two visits: 0,82%
• Other (excluded after control): 0,29%
• Finished: 60,5%

Abstract

The survey is the follow-up of the Diagnostic Review on Consumer Protection and Financial Literacy conducted by the World Bank in 2008-2009. The Diagnostic Review in Romania was the fourth in a World Bank-sponsored pilot program to assess consumer protection and financial literacy in developing and middle-income countries.1 The objectives of this Review were three-fold to: (1) refine a set of good practices for assessing consumer protection and financial literacy, including financial literacy; (2) conduct a review of the existing rules and practices in Romania compared to the good practices; and (3) provide recommendations on ways to improve consumer protection and financial literacy in Romania. The Diagnostic Review was prepared at the request of the National Authority for Consumers' Protection (ANPC), whose request was endorsed by the Ministry of Economy and Finance. Support was provided by the National Bank of Romania (BNR), which supervises banks and non-bank credit institutions. Further assistance was given by the supervisory commissions for securities (CNVM), insurance (CSA) and private pensions (CSSPP).

The Diagnostic Review found that the basic foundations needed for consumer protection and financial literacy are in place in Romania but they benefit from further strengthening support. The Review proposes improvements in six areas: consumer awareness, information and disclosure for consumers, professional competence, dispute resolution, financial education and financial literacy surveys.

Consequently, in 2010 the World Bank commissioned a nation-wide survey of the levels of financial literacy. A consultant (sociologist Manuela Sofia Stanculescu) developed the survey methodology (sampling methodology and questionnaire) in line with the Financial Literacy Survey in Russia (the World Bank, 2008) and the baseline survey Financial Capability in the UK (Financial Services Authority, 2005).2 The final form of the questionnaire was agreed with representatives of the National Bank of Romania (BNR), the Romanian Banking Institute (IBR), the National Authority for Consumers' Protection (ANPC), and the Financial Companies Association in Romania (ALB). The Institute for World Economy (Romanian Academy) collected the data in May 2010.

The main objective of this work is the establishment (and later the evaluation) of a well targeted national program of financial education.

Geographic coverage

National

Analysis unit

Household, individual

Universe

Non-institutionalized persons aged 18 or older

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the survey is probabilistic, two-stage, stratified, representative at national level with an error of +/- 3% at a 95% confidence level.

The sample is based on two stratification criteria: (i) historical region (8 regions) and (ii) type of locality (7 types depending on the city size, in urban areas, and on the synthetic index of community development,4 in the rural ones).

The sample volume is 2048,5 out of which 148 cases represent a boost of persons aged 16, 17 or those had their 18th birthday after November 2009.6 Respondents were randomly selected from electoral registers corresponding to 185 voting sections (randomly selected), located in 141 localities (77 communes, 63 towns/cities and the capital Bucharest).

The sample includes a slight over-representation of men, rural respondents, and elderly particularly due to the boost of young but also to the fact that people left abroad concentrate among the 25-44 age category. Nevertheless, the sample fairly reproduces the structure (by gender, age categories and area of residence) of the country population 16+ years according to the data for 2009 provided by the National Institute for Statistics. Socio-demographic structure of the sample is presented in table 3 of the survey report.

Demographic data and data regarding the use of financial services were collected for all members of respondents? households. In the respondents? households live 5406 persons overall. This extended sample has also a slight over-representation of rural respondents and an under-representation of children (0-14 years) and persons 25-24 years (most probably young people who left abroad with children).

MORE INFORMATION ON THE SAMPLING METHODOLOGY

Sample volume: 2,200 non-institutionalized persons aged 18 or older. In addition, the sample will be boosted with 180 persons aged 16-18 years old. Overall, at least 2,000 valid questionnaires should be completed during fieldwork.

Type of the sample: Probabilistic, two-stage, stratified, representative at national level, with an error of +/- 2.8% at a 95% confidence level.

Stratification criteria: The sampling scheme is based on two stratification criteria

(a) Historical region (8 regions) (b) Type of locality, with 7 theoretical strata

i. Urban areas - 4 strata 1. very small towns under 30 thou inhabitants 2. small towns 30,001-100 thou inhabitants 3. medium cities 100,001-199 thou inhabitants 4. large cities 200 thou inhabitants or more

ii. Rural areas - 3 strata determined based on the synthetic index of community development 37 1. poor communes (the 30% communes with the lowest level of development within the country) 2. medium developed communes 3. developed communes (the 30% communes with the highest level of development within the country).

Sampling stages: The sampling scheme includes two stages.

Sampling units: There are two sampling units corresponding to the two sampling stages. In the first sampling stage, voting sections are selected and in the second stage, non-institutionalized persons aged 18 years or more.

Selection: Random selection in all sampling stages.

Sampling scheme: In the first stage the sample is distributed proportionally with the volume of population for each of the 56(= 8 x 7) theoretical strata different from zero.

The corresponding number of voting sections for each strata is determined taking into account on the one hand, the volume of each strata sub-sample (= sample size x share of total population in that strata) and, on the other hand, a minimum level of 10 questionnaires for each sampling point. The voting sections which will represent sampling points are then randomly selected based on the exhaustive national list of voting sections (the latest available from the Permanent Electoral Authority).

The sample has 188 sampling points (voting sections) of which 104 are in urban areas, and 84 are in rural localities, including the capital city.

For each sampling point is computed the number of corresponding questionnaires by dividing the strata sub-sample by the number of sampling points of that strata. In the second sampling stage, the electoral registers corresponding to the voting sections (selected as sampling points) are used as sampling frame. Non-institutionalized persons aged 18 or more are randomly selected from the electoral registers based on the mechanical step method.

In those localities where the electoral registers are not available (or the municipality do not grant access), the random route method will be used. All these cases will be specified and explained in the fieldwork report, except for Bucharest, where the random route method will be used for all voting sections, as the rate of replacement from electoral registers is high in all national representative surveys.

The electoral registers include only persons 18 years or more. Accordingly, the sample will include a boost of persons aged 16, 17 or persons that had their 18th birthday after November 2009.39 For each voting section, one person aged 16-18 years will be added. They will be selected based on the random route method.

Mode of data collection

Face-to-face [f2f]

Response rate

The overall response rate of the survey is 95.2%. More detailed information is provided in "Table 2 Response rates and quality of the sampling frame by sampling method (%) " of the survey report.

This statistic presents factors that are expected to have a substantial impact on the future business performance of financial sector companies in the United Kingdom, according to financial field workers in August 2014. Regulatory requirements are expected to have the greatest influence, as per ** percent of respondents. The other key factor is the UK economy, which was mentioned by ** percent.

The A2F Survey, which stands for “Access to Financial Services,” is a nationally representative survey conducted in Nigeria. It assesses the access to and use of financial services by Nigerian adults aged 18 and above across all 36 states and the Federal Capital Territory (FCT) of Abuja. The primary purpose of the A2F Survey was to gather credible data on financial inclusion in Nigeria. This data helps to identify opportunities for policy reform and market opportunities for financial service providers. The A2F Survey provides credible data that is essential for understanding the landscape of financial inclusion in Nigeria. It highlights opportunities for policy reform and market opportunities for financial service providers. The A2F Survey provides information about how Nigerians access and use financial services. It also offers insights into national trends in financial inclusion, financial health, the impact of events like Covid-19, Naira re-design, customer trust in financial institutions, and the adoption of digital financial services. The survey assesses all Nigerians’ access to and use of financial services, describes the access landscape, and identifies opportunities to promote financial inclusion in the country. It covers various aspects, including financial health, customer trust in financial institutions, and digital financial services. The A2F Survey is universally recognized by financial sector stakeholders in Nigeria. It serves as an established and leading source of information on national trends in financial inclusion, aiding industry professionals and policymakers in making informed decisions.

The A2F Survey, which stands for “Access to Financial Services,” is a nationally representative survey conducted in Nigeria. It assesses the access to and use of financial services by Nigerian adults aged 18 and above across all 36 states and the Federal Capital Territory (FCT) of Abuja. The survey assesses all Nigerians’ access to and use of financial services, describes the access landscape, and identifies opportunities to promote financial inclusion in the country. It covers various aspects, including financial health, customer trust in financial institutions, and digital financial services. The primary purpose of the A2F Survey was to gather credible data on financial inclusion in Nigeria. This data helps to identify opportunities for policy reform and market opportunities for financial service providers. The A2F Survey provides credible data that is essential for understanding the landscape of financial inclusion in Nigeria. It highlights opportunities for policy reform and market opportunities for financial service providers. The A2F Survey provides information about how Nigerians access and use financial services. It also offers insights into national trends in financial inclusion, financial health, the impact of events like Covid-19, Naira re-design, customer trust in financial institutions, and the adoption of digital financial services. The A2F Survey is universally recognized by financial sector stakeholders in Nigeria. It serves as an established and leading source of information on national trends in financial inclusion, aiding industry professionals and policymakers in making informed decisions.

This statistics presents change in numbers of staff employed and expenses of training for all financial field companies in United Kingdom, as of June 2014 (quarterly between June 2013 and June 2014). The change is calculated as the difference between the percentage of respondents reporting increase in numbers and percentage of respondents reporting decrease. Both trends increased between September 2013 and March 2014. Since then the trend slowed down, to negative 12 percent in staff employed and 12 percent in training expenses in June 2014.

Generative AI experienced a massive expansion of use cases in financial services during 2024, with customer experience and engagement emerging as the dominant application. A 2024 survey revealed that ** percent of respondents prioritized this area, a dramatic increase from ** percent in the previous year. Report generation, investment research, and document processing also gained significant traction, with over ** percent of firms implementing these applications. Additional use cases included synthetic data generation, code assistance, software development, marketing and sales asset creation, and enterprise research.

Abstract

The Ghana Statistical Service (GSS) and the World Bank Development Economics Research Group (DECRG) partnered to implement the survey. The purpose was to find out household's access to and use of available financial services.This was a follow-up to an earlier test of survey designs regarding household access to financial services. The underlying premise is that the identity of a respondent can affect the quality and completeness of the information provided, especially when that respondent is providing information about other household members.

The survey will examine whether questions about specific products (e.g. credit cards, life insurance policies, savings clubs) elicit more complete information than questions asking whether a respondent uses services from a type of provider (e.g. commercial bank, credit union).

To derive the data necessary for these tests, the Financial Service Survey incorporated an experimental design in which one of three versions of the survey instrument (questionnaire) was randomly administered to each household. Individual household members were also randomly selected to respond to some sections of the questionnaire.

Geographic coverage

National Regional District, Municipal, Metropolitan

Analysis unit

Individuals

Universe

The survey covered all adult household members (usual residents) aged 15 years and older.

Kind of data

Sample survey data [ssd]

Sampling procedure

The most recently visited enumeration areas (EAs) for the Ghana Living Standards Survey Round 5 (GLSS5) were targeted for the survey. This is because the characteristics of these households may not have changed much, and they were more likely to recollect information they had already provided. All the 120 EAs visited in the 10th and 11th cycles of the GLSS5 were included in the survey, with an additional 34 EAs selected from the 60 EAs visited in the 9th cycle. Households within the 154 EAs were listed and 15 selected randomly from each EA yielding a total of 2,310 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three types of questionnaires were used in the survey:

1. Group 1 Questionnaire - All questions in the three (3) sections were administered to all household members aged 15 years and older. It collected information on background characteristics, the use of financial services and products and actions and attitudes towards accessing and using financial services and products.

2. Group 2 Questionnaire - Sections 1 and 2 of this questionnaire were administered to all household members aged 15 years and older. Sections 3 and 4 were administered to household members randomly selected using the Kish Grid based on given criteria.

3. Group 3 Questionnaire - All questions in section (1) were administered to heads of household and one randomly selected household member and covered background characteristics. Section two (2) was administered to heads of household and covered the use of financial services. Sections 3 and 4 were administered to a randomly selected household member and covered the use of financial services and products and actions and attitudes towards access and use of financial services and products.

All the questionnaires were in English and whenever necessary, the interview was conducted in a language of the respondent's choice. An interpreter was also used where the interviewer was not proficient in the respondent's choice of language.

Cleaning operations

The GSS data editing occurs at three levels:

1. Field editing by interviewers and supervisors
2. Office editing
3. Data cleaning and imputation

Response rate

Out of the 2,310 households selected for the survey, 2,292 were identified and successfully enumerated. This yielded a response rate of 99.2 percent.

Data are used in the National Accounts.

The A2F Survey, which stands for “Access to Financial Services,” is a nationally representative survey conducted in Nigeria. It assesses the access to and use of financial services by Nigerian adults aged 18 and above across all 36 states and the Federal Capital Territory (FCT) of Abuja. EFInA initiated the A2F Survey in 2008 when financial inclusion was relatively unknown in Nigeria, even among bankers and regulators. The primary purpose of the A2F Survey was to gather credible data on financial inclusion in Nigeria. This data helps to identify opportunities for policy reform and market opportunities for financial service providers. The A2F Survey provides information about how Nigerians access and use financial services. It also offers insights into national trends in financial inclusion, financial health, the impact of events like Covid-19, Naira re-design, customer trust in financial institutions, and the adoption of digital financial services. The A2F Survey is universally recognized by financial sector stakeholders in Nigeria. It serves as an established and leading source of information on national trends in financial inclusion, aiding industry professionals and policymakers in making informed decisions. The survey is conducted every two years and aims to: a. Document the usage of financial products across both the formal and informal sectors from an urban and rural perspective. b. Provide insights into regulatory and market obstacles to growth and innovation in the financial sector. c. Identify the financial needs of the adult population and thereby allow service providers to develop innovative products to serve them. d. Provide credible data that highlights opportunities for policy reform and supports evidence-based financial inclusion policies. The EFInA Access to Financial Services in Nigeria 2020 survey results have been disseminated. The findings from the survey highlight the opportunities to extend financial services to the unbanked and under-banked low-income segments in the country. The EFInA Access to Financial Services in Nigeria survey is nationwide and covers over 20,000 consumers.

Data analytics maintained its position as the leading AI application among financial services firms in 2024. A 2024 industry survey indicated that ** percent of companies leveraged AI for data analytics, showing modest growth from the previous year. Generative AI experienced the strongest year-over-year adoption increase, becoming the second most widely used AI technology, with more than half of firms either implementing or evaluating the technology. Reflecting this growing embrace of AI solutions, the financial sector's investment in AI technologies continues to surge, with spending projected to reach over ** billion U.S. dollars in 2025 and more than double to *** billion U.S. dollars by 2028. The main benefits of AI in the financial services sector Financial services firms reported that AI delivered the greatest value through operational efficiencies, according to a 2024 industry survey. The technology also provided significant competitive advantages, cited by ** percent of respondents as a key benefit. Enhanced customer experience emerged as the third most important advantage of AI adoption in the sector. Adoption across business segments The integration of AI varies across different areas of financial services. In 2023, operations lead the way with a ** percent adoption rate, closely followed by risk and compliance at ** percent. In customer experience and marketing, voice assistants, chatbots, and conversational AI are the most common AI applications. Meanwhile, financial reporting and accounting dominate AI use in operations and finance.

GenAI saw significant growth across financial services in 2024, with ** percent of survey respondents reporting active use of the technology - up from ** percent in 2023. The companies primary generative AI use case was enhancing customer experience and engagement, particularly through applications like chatbots, virtual assistants, and agent support tools.

Quarterly data from the Financial Services Survey (FSS 266) return of assets and liabilities, including derivatives. These are Experimental Statistics.

The displayed data on the frequency of using digital financial services shows results of an exclusive Statista survey conducted in the United States in 2018. Some ** percent of respondents answered the question ''How often do you use digital financial services?'' with ''daily''.The Survey Data Table for the Statista survey Tech Giants and Digital Services in the United States 2019 contains the complete tables for the survey including various column headings.

As of the third quarter of 2024, according to a survey on the use of online financial services, around **** percent of internet users in South Korea used a banking, investment, or insurance website or mobile app each month, which accounted for the highest usage rate. Closely behind, around **** percent of users in the survey responded to using mobile payment service, and ** percent to owning cryptocurrency.

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

National coverage

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for United Kingdom is 1000.

Mode of data collection

Landline and mobile telephone

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

The Community Credit research project explores pathways for trusted collaboration between credit unions and the communities they serve. To understand the experiences of people historically underserved by the consumer financial services industry, we focused in particular on the lived experience of low-income residents in Southern California. As part of a larger, mixed-methods study, in 2022 we conducted an online survey investigating people’s everyday financial practices, evolving perceptions of trust and risk, and their unmet financial needs. The general population survey data was collected between April 15 and April 22, 2022. The credit union data was collected between May 3 and July 18, 2022. This data set contains the responses of the survey participants after excluding any personally identifying data. All study materials and procedures were approved by the University of California, Irvine Office of Human Research Protections and the Institutional Review Board (protocol ID 20216839)...., Survey data was collected via the Qualtrics platform. The survey contains 52 questions. It was distributed to the general population in zip codes within the counties of Los Angeles and Orange. It was also distributed directly to members of a large credit union headquartered in Orange County (“large†according to NCUA asset classes). Participants were eligible to complete the survey if they live in Orange County or Los Angeles County, are older than 18, and have a combined household income of less than $100,000. Incomplete responses have been removed. The survey yielded 1,370 complete responses (1,213 from the general population participants and 157 from members of the large credit union)., Note that the files do not contain all the responses from the survey questions. Responses that provided potentially identifying information were removed. Survey participants’ gender, education status, employment status, and marital status were removed; data on these elements are provided in aggregate in the readme file. Responses are segmented into two files reflecting participants from the general population (“Gen Pop†) and from the credit union (“CU†).

Data are used in the National Accounts.

Abstract

The purpose was to find out household's access to and use of available financial services.This was a follow-up to an earlier test of survey designs regarding household access to financial services. The underlying premise is that the identity of a respondent can affect the quality and completeness of the information provided, especially when that respondent is providing information about other household members. The survey will examine whether questions about specific products (e.g. credit cards, life insurance policies, savings clubs) elicit more complete information than questions asking whether a respondent uses services from a type of provider (e.g. commercial bank, credit union). To derive the data necessary for these tests, the Financial Service Survey incorporated an experimental design in which one of three versions of the survey instrument (questionnaire) was randomly administered to each household. Individual household members were also randomly selected to respond to some sections of the questionnaire.

Geographic coverage

National coverage

Analysis unit

Household, individual

Universe

The survey covered all adult household members (usual residents) aged 15 years and older.

Kind of data

Sample survey data [ssd]

Sampling procedure

The most recently visited enumeration areas (EAs) for the Ghana Living Standards Survey Round 5 (GLSS5) were targeted for the survey. This is because the characteristics of these households may not have changed much, and they were more likely to recollect information they had already provided. All the 120 EAs visited in the 10th and 11th cycles of the GLSS5 were included in the survey, with an additional 34 EAs selected from the 60 EAs visited in the 9th cycle. Households within the 154 EAs were listed and 15 selected randomly from each EA yielding a total of 2,310 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three types of questionnaires were used in the survey:

1. Group 1 Questionnaire - All questions in the three (3) sections were administered to all household members aged 15 years and older. It collected information on background characteristics, the use of financial services and products and actions and attitudes towards accessing and using financial services and products.
2. Group 2 Questionnaire - Sections 1 and 2 of this questionnaire were administered to all household members aged 15 years and older. Sections 3 and 4 were administered to household members randomly selected using the Kish Grid based on given criteria.
3. Group 3 Questionnaire - All questions in section (1) were administered to heads of household and one randomly selected household member and covered background characteristics. Section two (2) was administered to heads of household and covered the use of financial services. Sections 3 and 4 were administered to a randomly selected household member and covered the use of financial services and products and actions and attitudes towards access and use of financial services and products. All the questionnaires were in English and whenever necessary, the interview was conducted in a language of the respondent's choice. An interpreter was also used where the interviewer was not proficient in the respondent's choice of language.

Cleaning operations

The GSS data editing occurs at three levels: 1. Field editing by interviewers and supervisors 2. Office editing 3. Data cleaning and imputation

Response rate

Out of the 2,310 households selected for the survey, 2,292 were identified and successfully enumerated. This yielded a response rate of 99.2 percent.

This statistic shows consumer usage of financial services in the United States in 2019. During the survey, ** percent of the respondents said they use telephone banking.