Global Financial Inclusion (Global Findex) Database 2014
The Global Financial Inclusion (Global Findex) Database is the world’s most comprehensive gauge of how adults around the world save, borrow, make payments and manage risk. Launched in 2011 with the support of the Bill & Melinda Gates Foundation, the Global Findex for the first time made it possible to measure financial inclusion for adults around the world, including women, the poor, and rural residents.
Three years later, the 2014 Global Findex provides an update on the indicators collected in 2011 while adding more nuanced data on mobile money accounts and domestic payments. The Global Findex indicators are drawn from survey data collected by Gallup, Inc. over the 2014 calendar year, covering around 150,000 adults in more than 140 economies and representing about 97 percent of the world’s population. The set of indicators will be collected again in 2017.
Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.
By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
While the first edition provided more than 60 indicators on financial inclusion, the 2014 Global Findex features more than 100 indicators. The database includes indicators on ownership of financial institution accounts and mobile money accounts; use of mobile money accounts for savings and payments; purposes of account use, such as receiving government transfers, wage payments, and agricultural payments; how adults send and receive domestic remittances; savings behavior; use of savings methods, such as banks, and informal savings clubs or people outside the family; sources of borrowing, such as banks, friends, family members; and purposes of borrowing, such as home purchases, school fees, and emergencies. The 2014 Global Findex survey also explored the topic of financial resilience and contains information on how adults deal with emergencies by asking whether and how they can come up with money to deal with them.
Sample excludes the Northwest Territories, Nunavut, and Yukon, which represent approximately 0.3% of the population.
The target population is the civilian, non-institutionalized population 15 years and above.
Producers and sponsors
Development Research Group, Finance and Private Sector Development Unit
Carried out the survey in association with its annual Gallup World Poll.
Development Research Group, World Bank
The Bill and Melinda Gates Foundation
As in the first edition, the indicators in the 2014 Global Findex are drawn from survey data covering almost 150,000 people in more than 140 economies-representing more than 97 percent of the world's population. The survey was carried out over the 2014 calendar year by Gallup, Inc. as part of its Gallup World Poll, which since 2005 has continually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 140 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. The set of indicators will be collected again in 2017.
Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or is the customary methodology. In most economies the fieldwork is completed in two to four weeks. 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 by means of the Kish grid. In economies where cultural restrictions dictate gender matching, respondents are randomly selected through the Kish grid from among all eligible adults of the interviewer's gender.
In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to reach a person in each household, spread over different days and times of day.
The sample size in Canada was 1,004 individuals.
Data weighting is used to ensure a nationally representative sample for each economy. Final weights consist of the base sampling weight, which corrects for unequal probability of selection based on household size, and the poststratification weight, which corrects for sampling and nonresponse error. Poststratification weights use economy-level population statistics on gender and age and, where reliable data are available, education or socioeconomic status.
Dates of Data Collection
Frequency of Data Collection
Data Collection Mode
Data Collection Notes
Data collection was done using landline and cellular telephone.
Interviews were conducted in the following languages: English, French
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 multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.
Questions on cash withdrawals, saving using an informal savings club or person outside the family, domestic remittances, school fees, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.
Estimates of Sampling Error
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 Asli Demirguc-Kunt, Leora Klapper, Dorothe Singer, and Peter Van Oudheusden, “The Global Findex Database 2014: Measuring Financial Inclusion around the World.” Policy Research Working Paper 7255, World Bank, Washington, D.C.
Asli Demirguc-Kunt, Leora Klapper, Dorothe Singer, and Peter Van Oudheusden, “The Global Findex Database 2014: Measuring Financial Inclusion around the World”. Policy Research Working Paper 7255, World Bank, Washington, D.C.
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.