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 almost 145,000 people in 139 economies, representing 97 percent of the world’s population. 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

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. Additionally, phone surveys were not a viable option in 16 economies in 2021, which were then surveyed in 2022.

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 Lesotho is 1010.

Mode of data collection

Face-to-face [f2f]

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.

Abstract

Well-functioning financial systems serve a vital purpose, offering savings, credit, payment, and risk management products to people with a wide range of needs. Yet until now little had been known about the global reach of the financial sector - the extent of financial inclusion and the degree to which such groups as the poor, women, and youth are excluded from formal financial systems. Systematic indicators of the use of different financial services had been lacking for most economies.

The Global Financial Inclusion (Global Findex) database provides such indicators. This database contains the first round of Global Findex indicators, measuring how adults in more than 140 economies save, borrow, make payments, and manage risk. The data set can be used to track the effects of financial inclusion policies globally and develop a deeper and more nuanced understanding of how people around the world manage their day-to-day finances. By making it possible to identify segments of the population excluded from the formal financial sector, the data can help policy makers prioritize reforms and design new policies.

Geographic coverage

National Coverage.

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Global Findex indicators are drawn from survey data collected by Gallup, Inc. over the 2011 calendar year, covering more than 150,000 adults in 148 economies and representing about 97 percent of the world's population. Since 2005, Gallup has surveyed adults annually around the world, using a uniform methodology and randomly selected, nationally representative samples. The second round of Global Findex indicators was collected in 2014 and is forthcoming in 2015. The set of indicators will be collected again in 2017.

Surveys were conducted face-to-face in economies where landline telephone penetration is less than 80 percent, or where face-to-face interviewing is customary. The first stage of sampling is the identification of primary sampling units, consisting of clusters of households. The primary sampling 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. 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 by means of the Kish grid.

Surveys were conducted by telephone in economies where landline telephone penetration is over 80 percent. The telephone surveys were conducted using random digit dialing or a nationally representative list of phone numbers. In selected countries where cell phone penetration is high, a dual sampling frame is used. Random respondent selection is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to teach a person in each household, spread over different days and times of year.

The sample size in Afghanistan was 1,000 individuals. Gender-matched sampling was used during the final stage of selection.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup, Inc. also provided valuable input. The questionnaire was piloted in over 20 countries using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

Questions on insurance, mobile payments, and loan purposes were asked only in developing economies. The indicators on awareness and use of microfinance insitutions (MFIs) are not included in the public dataset. However, adults who report saving at an MFI are considered to have an account; this is reflected in the composite account indicator.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country- and indicator-specific standard errors, refer to the Annex and Country Table in Demirguc-Kunt, Asli and L. Klapper. 2012. "Measuring Financial Inclusion: The Global Findex." Policy Research Working Paper 6025, World Bank, Washington, D.C.

United States NCUA: State: Saving: Others: Share Certificates data was reported at 95,990,872.616 USD th in Mar 2018. This records an increase from the previous number of 94,624,764.110 USD th for Dec 2017. United States NCUA: State: Saving: Others: Share Certificates data is updated quarterly, averaging 89,318,854.859 USD th from Mar 2005 (Median) to Mar 2018, with 53 observations. The data reached an all-time high of 104,393,576.465 USD th in Mar 2009 and a record low of 58,772,027.632 USD th in Mar 2005. United States NCUA: State: Saving: Others: Share Certificates data remains active status in CEIC and is reported by National Credit Union Administration. The data is categorized under Global Database’s USA – Table US.KB019: Financial Data: National Credit Union Administration: State Institutions.

United States COF: Net Interest Income data was reported at 2,690,788.000 USD th in Dec 2019. This records an increase from the previous number of 2,520,031.000 USD th for Sep 2019. United States COF: Net Interest Income data is updated quarterly, averaging 1,291,972.000 USD th from Dec 2000 (Median) to Dec 2019, with 77 observations. The data reached an all-time high of 2,690,788.000 USD th in Dec 2019 and a record low of 112,510.000 USD th in Dec 2005. United States COF: Net Interest Income data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB060: Financial Data: Federal Deposit Insurance Corporation: Capital One.

The global graph database market growth will be propelled through 2034 at a massive CAGR of 19.4%. With the growing data usage and the rising data storage requirements, the global graph database market size will likely inflate from US$ 3.17 billion to US$ 18.68 billion in the next decade. Technological advancements also fuel the growth prospects of the industry.

Attributes	Key Insights
Estimated Industry Size in 2024	US$ 3.17 billion
Projected Industry Value in 2034	US$ 18.68 billion
Value-based CAGR from 2024 to 2034	19.4%

Growing Technology to Enlarge the Global Graph Database Market Size

Attributes	Values
Historical CAGR	16.5%
Valuation in 2019	US$ 1.46 billion
Valuation in 2023	US$ 2.69 billion

Country-wise Analysis

Countries	Forecasted CAGR
Germany	8.9%
Japan	9.2%
The United States of America	13.5%
China	19.9%
Australia	22.9%

Category-wise Insights

Category	Solution- Graph Database Platform
Industry Share in 2024	63.3%
Segment Drivers	Seamless integration with traditional systems increases their usability, enhancing the demand for these platforms. Excellent scalability of these platforms elevates the usability standards. The wider adaptability drives the segment’s popularity, fueling the global graph database market size.

Category	Application- Fraud & Risk Analytics
Industry Share in 2024	24.3%
Segment Drivers	Due to the ability of graph databases to deliver accurate risk forecasting, they save a lot of time and money. With the rising financial transactions, the demand for fraud detection and potential risk identification is rising. Therefore, the increasing popularity of the segment drives the global graph database market size.

United States COF: LC: EC: BE: Perpetual Preferred Stock data was reported at 0.000 USD th in Dec 2019. This stayed constant from the previous number of 0.000 USD th for Sep 2019. United States COF: LC: EC: BE: Perpetual Preferred Stock data is updated quarterly, averaging 0.000 USD th from Dec 2000 (Median) to Dec 2019, with 77 observations. The data reached an all-time high of 0.000 USD th in Dec 2019 and a record low of 0.000 USD th in Dec 2019. United States COF: LC: EC: BE: Perpetual Preferred Stock data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB060: Financial Data: Federal Deposit Insurance Corporation: Capital One.

United States STT: Memo: Risk-Based Capital: Core Tier 1 data was reported at 16,757,000.000 USD th in Dec 2019. This records a decrease from the previous number of 17,467,000.000 USD th for Sep 2019. United States STT: Memo: Risk-Based Capital: Core Tier 1 data is updated quarterly, averaging 11,545,550.000 USD th from Dec 2000 (Median) to Dec 2019, with 77 observations. The data reached an all-time high of 19,012,115.000 USD th in Sep 2018 and a record low of 3,296,055.000 USD th in Mar 2001. United States STT: Memo: Risk-Based Capital: Core Tier 1 data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB063: Financial Data: Federal Deposit Insurance Corporation: State Street Bank & Trust.

United States COF: Memo: Total Unused Commitments data was reported at 129,872,595.000 USD th in Dec 2019. This records an increase from the previous number of 113,598,628.000 USD th for Sep 2019. United States COF: Memo: Total Unused Commitments data is updated quarterly, averaging 12,883,457.000 USD th from Dec 2000 (Median) to Dec 2019, with 77 observations. The data reached an all-time high of 151,007,546.000 USD th in Jun 2012 and a record low of 2,916,911.000 USD th in Mar 2001. United States COF: Memo: Total Unused Commitments data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB060: Financial Data: Federal Deposit Insurance Corporation: Capital One.

United States NCUA: State: Assets: Allowance for Loan & Lease Losses data was reported at 4,035,357.653 USD th in Jun 2018. This records an increase from the previous number of 4,021,106.705 USD th for Mar 2018. United States NCUA: State: Assets: Allowance for Loan & Lease Losses data is updated quarterly, averaging 3,502,101.970 USD th from Mar 2005 (Median) to Jun 2018, with 54 observations. The data reached an all-time high of 4,458,985.560 USD th in Dec 2010 and a record low of -3,625,990.978 USD th in Jun 2009. United States NCUA: State: Assets: Allowance for Loan & Lease Losses data remains active status in CEIC and is reported by National Credit Union Administration. The data is categorized under Global Database’s USA – Table US.KB046: Financial Data: National Credit Union Administration: State Institutions.

United States BAC: LC: TL: Trading Liabilities data was reported at 26,947,000.000 USD th in Dec 2019. This records an increase from the previous number of 25,668,000.000 USD th for Sep 2019. United States BAC: LC: TL: Trading Liabilities data is updated quarterly, averaging 37,572,940.000 USD th from Dec 2000 (Median) to Dec 2019, with 77 observations. The data reached an all-time high of 94,016,778.000 USD th in Mar 2008 and a record low of 25,668,000.000 USD th in Sep 2019. United States BAC: LC: TL: Trading Liabilities data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB055: Financial Data: Federal Deposit Insurance Corporation: Bank of America.

United States STT: Pre-Tax Net Operating Income data was reported at 717,000.000 USD th in Dec 2019. This records an increase from the previous number of 712,000.000 USD th for Sep 2019. United States STT: Pre-Tax Net Operating Income data is updated quarterly, averaging 575,114.000 USD th from Dec 2000 (Median) to Dec 2019, with 77 observations. The data reached an all-time high of 1,028,331.000 USD th in Dec 2009 and a record low of -53,292.000 USD th in Jun 2003. United States STT: Pre-Tax Net Operating Income data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB063: Financial Data: Federal Deposit Insurance Corporation: State Street Bank & Trust.

United States WFC: Applicable Income Taxes data was reported at 793,000.000 USD th in Dec 2019. This records a decrease from the previous number of 1,302,000.000 USD th for Sep 2019. United States WFC: Applicable Income Taxes data is updated quarterly, averaging 1,205,000.000 USD th from Dec 2000 (Median) to Dec 2019, with 77 observations. The data reached an all-time high of 6,693,000.000 USD th in Sep 2012 and a record low of -2,234,000.000 USD th in Dec 2017. United States WFC: Applicable Income Taxes data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB056: Financial Data: Federal Deposit Insurance Corporation: Wells Fargo.

Brazil Foundry: Operating Revenue: Others data was reported at 13,631.000 BRL th in 2017. This records an increase from the previous number of 9,327.000 BRL th for 2016. Brazil Foundry: Operating Revenue: Others data is updated yearly, averaging 10,742.000 BRL th from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 19,463.000 BRL th in 2008 and a record low of 5,205.000 BRL th in 2015. Brazil Foundry: Operating Revenue: Others data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Metal and Steel Sector – Table BR.WAM004: Metal Financial Data: Foundry.

Retail Trade: CNAE 2.0: Appliances, Audio & Video Equipment: Gross Value Added data was reported at 13,838,629.000 BRL th in 2017. This records an increase from the previous number of 12,403,517.000 BRL th for 2016. Retail Trade: CNAE 2.0: Appliances, Audio & Video Equipment: Gross Value Added data is updated yearly, averaging 11,308,689.000 BRL th from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 14,303,359.000 BRL th in 2014 and a record low of 4,487,542.000 BRL th in 2008. Retail Trade: CNAE 2.0: Appliances, Audio & Video Equipment: Gross Value Added data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Wholesale Trade, Retail Trade, Repair of Automotive and Motorcycles Sector – Table BR.RJD015: Retail Trade: Financial Data: CNAE 2.0: Appliances, Audio & Video Equipment.

United States BAC: Memo: Loans & Leases Held for Sale data was reported at 8,938,000.000 USD th in Dec 2019. This records a decrease from the previous number of 9,594,000.000 USD th for Sep 2019. United States BAC: Memo: Loans & Leases Held for Sale data is updated quarterly, averaging 11,667,296.000 USD th from Dec 2000 (Median) to Dec 2019, with 77 observations. The data reached an all-time high of 41,144,154.000 USD th in Jun 2009 and a record low of 4,438,000.000 USD th in Dec 2000. United States BAC: Memo: Loans & Leases Held for Sale data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB055: Financial Data: Federal Deposit Insurance Corporation: Bank of America.

United States FFC: MA: Foreign: Other data was reported at 9.000 USD mn in Mar 2018. This stayed constant from the previous number of 9.000 USD mn for Dec 2017. United States FFC: MA: Foreign: Other data is updated quarterly, averaging 3.000 USD mn from Mar 2003 (Median) to Mar 2018, with 61 observations. The data reached an all-time high of 44.000 USD mn in Dec 2011 and a record low of 0.000 USD mn in Dec 2010. United States FFC: MA: Foreign: Other data remains active status in CEIC and is reported by US Department of Treasury. The data is categorized under Global Database’s USA – Table US.KA023: US Financial Firms Claims on Foreigner: Quarterly.

United States Other Financial Corporations: Money Market Funds: Assets: Financial data was reported at 6,357.551 USD bn in 2023. This records an increase from the previous number of 5,223.061 USD bn for 2022. United States Other Financial Corporations: Money Market Funds: Assets: Financial data is updated yearly, averaging 3,085.760 USD bn from Dec 2005 (Median) to 2023, with 19 observations. The data reached an all-time high of 6,357.551 USD bn in 2023 and a record low of 2,026.821 USD bn in 2005. United States Other Financial Corporations: Money Market Funds: Assets: Financial data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s United States – Table US.IMF.FSI: 2019 Methodology: Sectoral Financial Statement: Balance Sheet: Annual.

United States US: Non Financial Corporations: Capital and Reserves data was reported at 27,007.411 USD bn in 2016. This records an increase from the previous number of 25,178.010 USD bn for 2015. United States US: Non Financial Corporations: Capital and Reserves data is updated yearly, averaging 19,249.737 USD bn from Dec 2005 (Median) to 2016, with 12 observations. The data reached an all-time high of 27,007.411 USD bn in 2016 and a record low of 16,260.299 USD bn in 2009. United States US: Non Financial Corporations: Capital and Reserves data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s USA – Table US.IMF.FSI: Sectoral Financial Statement: Balance Sheet: Annual.

United States FDIC Insured Inst: RE: Home Equity Lines data was reported at 398.436 USD bn in Mar 2018. This records a decrease from the previous number of 411.152 USD bn for Dec 2017. United States FDIC Insured Inst: RE: Home Equity Lines data is updated quarterly, averaging 266.300 USD bn from Dec 1987 (Median) to Mar 2018, with 122 observations. The data reached an all-time high of 674.238 USD bn in Mar 2009 and a record low of 28.836 USD bn in Dec 1987. United States FDIC Insured Inst: RE: Home Equity Lines data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s USA – Table US.KB012: Financial Data: Federal Deposit Insurance Corporation: Insured Institutions.

Retail Trade: CNAE 2.0: Construction Material: Self Employed: Family Members data was reported at 10,156.000 Person in 2017. This records a decrease from the previous number of 10,186.000 Person for 2016. Retail Trade: CNAE 2.0: Construction Material: Self Employed: Family Members data is updated yearly, averaging 15,004.000 Person from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 30,643.000 Person in 2012 and a record low of 10,081.000 Person in 2009. Retail Trade: CNAE 2.0: Construction Material: Self Employed: Family Members data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Wholesale Trade, Retail Trade, Repair of Automotive and Motorcycles Sector – Table BR.RJD017: Retail Trade: Financial Data: CNAE 2.0: Construction Material.