Name: Global Financial Development
Creator: World Bank Group
Published: 2012-09-09

The BOOST initiative is a Bank-wide collaborative effort launched in 2010 to facilitate access to budget data and promote effective use for improved decision-making processes, transparency and accountability.

BOOST - Public Expenditure Database

This collection contains datasets that may be useful for analysis, response or modelling for the Coronavirus (COVID-19) pandemic.

Coronavirus (COVID-19) Related Datasets

The Data360 initiative aims to integrate high-value data and knowledge curated in the Bank’s verticals into a user-centered data platform. 

Data 360

The Development Data Partnership platform facilitates formation of public-private partnerships for solving development challenges with technology. Specifically, the Development Data Partnership Working Group organizes opportunities for WBG staff to work with technology companies who offer pro-bono data and resources.

Development Data Partnership

This collection contains discrepancy indexes for UN COMTRADE data that aims to capture both the frequency of missed reporting and its impact on overall recorded trade value

Discrepancy Index

A collection of datasets produced through partnership between the World Bank and the European Space Agency (ESA) Earth Observation for Sustainable Development (EO4SD) initiative.

Earth Observation for Sustainable Development

Open data and analytics for a sustainable energy future.

Energy Data Info

This collection features datasets to support building policies, institutions and investments for inclusive and sustainable growth.

Equitable Growth, Finance and Institutions

Project Page: https://worldbank.github.io/GEEST/README.html 

As part of the “Geospatial Assessment of Women Employment and Business Opportunities in the Energy Sector” project, open-source Gender-related spatial data was collected for 31 Small Island Developing States (SIDS) across the globe, resulting in curated and thoroughly documented geodatabases (GDBs) that are now ready to be explored! 
Fifty-nine spatial layers were identified and then researched for each country, covering the following categories: Demographics and Population | Renewable Energy | Energy Access | Education | Jobs and Finance | Digital Inclusion | Transportation | Safety | Amenities | Climate/Earth | Law/Policy/Government. 


However, not every country GDB contains all 59 data layers, as this was dependent on the availability of open-source data in each SIDS. Users are encouraged to check the accompanying metadata excel file for more information on the datasets in each GDB, the vintage, and the

Gender Spatial Data - Small Island States

A collection of datasets that contain geospatial data. These datasets have one or more resources in a geospatial data format.

Geospatial Datasets

Collection of useful datasets from IMF made available to Bank staff via <a href=http://mydatabank.worldbank.org>myDataBank</a>

IMF Dataset

A collection of datasets to help finance the global infrastructure gap.

Infrastructure Finance Datasets

Data and dataset subscriptions managed by the Library Network on agriculture, business, economics, energy, finance, health, risk, water, and more..

Library Databases

The LinkedIn-World Bank partnership offers data to help governments and researchers understand rapidly evolving labor markets with detailed and dynamic data. It allows leaders to benchmark and compare labor markets across the world; analyze skills, occupations, migration, and industries; and leverage real-time data to make policy changes.Visualizations for many of these data are available at <a href=https://linkedindata.worldbank.org/>linkedindata.worldbank.org</a>

LinkedIn Data for Development

Collection of merchandise trade data available to World Bank staff.

Merchandise Trade Data

This collection includes datasets associated with research organized under the Bank, <a href=http://prwp.worldbank.org target='_blank' title='Opens in a new window'>Policy Research Working Papers</a>.

Policy Research Working Papers

This collection contains data on disaster and climate risk assessments curated by the Global Facility for Disaster Reduction and Recovery (GFDRR).

Risk Data Library

This collection presents software tools and models developed by the World Bank to support monitoring, planning, programming and the economic evaluation of roads and highways works.

Road Software Tools

This spatial database, a product of the South Asia Region Chief Economist's (SARCE) Office, presents data collected from official sources and harmonized into different spatial levels. Data includes economic and environmental data across 12 topic areas, and includes data from four countries in South Asia (Bangladesh, Bhutan, India, and Nepal) for both 2001 and 2011.

SARCE Spatial Database

A collection of country Small Area Estimation (SAE) and Poverty Mapping that contains papers, shapefiles, and datasets produced through partnerships between the World Bank and country statistics offices.

Small area estimates / Poverty mapping

This collection consists of datasets compiled and created by the World Bank Data Lab in response to a request by the Syria Economic Monitor Team to explore alternative data sources to better understand changing trends in trade and economic activity, focusing on: surface cross-border transport routes, changes in observed agricultural production, observed nighttime lights, and reported conflict.

Syria Economic Monitor

A collection of relevant datasets to support operations in Ukraine.

Ukraine datasets

Catalogue lists all the data produced under the partnership contracts between the World Bank Group and the European Space Agency

World Bank (WBG) - European Space Agency (ESA) Database

A collection of datasets to help achieve universal access to reliable and fast internet services for all.

World Bank Digital Development Data

A collection of datasets to help achieve sustainable energy for all.

World Bank Energy Datasets

A collection of datasets to help achieve sustainable mobility for all.

World Bank Transport Data

From Data to a Water-Secure World for All. World Bank Water Data surrounding the three pillars of Sustain Water Resources, Deliver Services and Build Resilience.

World Bank Water Data

The World Development Report 2021: Data for Better Lives explores the tremendous potential of the changing data landscape to improve the lives of poor people, while also acknowledging its potential to open back doors that can harm individuals, businesses, and societies. To address this tension between the helpful and harmful potential of data, this Report calls for a new social contract that enables the use and reuse of data to create economic and social value, ensures equitable access to that value, and fosters trust that data will not be misused in harmful ways. The data used in the WDR2021 are curated as a collection here.

World Development Report 2021

The World Development Report 2022: Finance for an Equitable Recovery examines the central role of finance in the economic recovery from the COVID-19 pandemic. In doing so, it looks into the consequences of the crisis most likely to affect emerging economies and proposes a set of policies to mitigate the interconnected financial risks stemming from the pandemic and to steer economies toward a sustainable and equitable recovery. The data used in the WDR2022 are curated as a collection here.

World Development Report 2022

The World Settlement Footprint Collection includes country datasets describing the evolution of the built-area across the globe at a ~30m resolution.

World Settlement Footprint

Social capital: Mediator of financial literacy and financial inclusion in rural Uganda

Multitasking, but for what benefit? The dilemma facing Nigerian university students regarding part-time working

Financial inclusion, financial inclusion policy and Islamic finance

Financial Inclusion, Poverty, and Income Inequality

Heterogeneous patterns of financial development: Implications for Asian financial integration

The Next Frontier of Mobile Money Adoption

M-Pesa and the Market-LedApproach to Financial Inclusion

Islamic finance: financial inclusion or migration?

Sens capability approach and microcredit: lessons from a Malaysian case

The Policy and Practice of Microcredit in Rural China: Toward a Relational Understanding of Heterogeneous Implementation

Financial Inclusion, Financial Stability And Income Inequality: Introduction

The digital revolution in financial inclusion: international development in the fintech era

Indebted to development: microcredit as (de) marginalisation in rural China

Contesting financial inclusion

How important is mobile telephony for economic growth? Evidence from MENA countries

Introduction–risk management in global capitalism

Role of microfinance in sustainable development in rural Bangladesh

Social efficiency in microfinance institutions: Identifying how to improve it

Financial self-efficacy: a determinant of financial inclusion

Financial inclusion in India: an application of TOPSIS

Financial inclusion and agricultural commercialization in Ghana: an empirical investigation

Financial self-efficacy: a mediator in advancing financial inclusion

Institutional entrepreneurship and social innovation at the base of the pyramid: the case of M-Pesa in Kenya

Foreign Banks and Financial Inclusion in Emerging and Developing Economies: An Empirical Investigation

Game-changing trends and forces for agricultural financing in sub-Saharan Africa toward 2055: Verification and prioritization through the real-time Delphi method

Constituting financialized subjectivities: cultural political economy of financial literacy in Turkey

Financial Inclusion and Policy-Making: Strategy, Campaigns and Microcredit a la Turca

Value of all traded shares outside of the top ten largest traded companies as a share of total value of all traded shares in a stock market exchange. WFE provides data on the exchange level. This variable is aggregated up to the country level by taking a simple average over exchanges.

Value of listed shares outside of the top ten largest companies to total value of all listed shares.

Estimated proportion of purchases of fixed assets that was financed by owners’ contribution or issue of new equity shares.

Private credit by deposit money banks and other financial institutions to GDP, calculated using the following deflation method:  {(0.5)*[Ft/P_et + Ft-1/P_et-1]}/[GDPt/P_at] where F is credit to the private sector, P_e is end-of period CPI, and P_a is average annual CPI. Raw data are from the electronic version of the IMF’s International Financial Statistics. Private credit by deposit money banks (IFS line 22d); GDP in local currency (IFS line 99B..ZF or, if not available, line 99B.CZF); end-of period CPI (IFS line 64M..ZF or, if not available, 64Q..ZF); and average annual CPI is calculated using the monthly CPI values (IFS line 64M..ZF).

Raw data are from the electronic version of the IMF's International Financial Statistics (IFS lines 12 and 22, a-d).

Ratio of liquid liabilities to GDP, calculated using the following deflation method: {(0.5)*[Ft/P_et + Ft-1/P_et-1]}/[GDPt/P_at] where F is liquid liabilities, P_e is end-of period CPI, and P_a is average annual CPI. Raw data are from the electronic version of the IMF's International Financial Statistics. Liquid liabilities (IFS lines 55L or, if not available, line 35L); GDP in local currency (IFS line 99B..ZF or, if not available, line 99B.CZF); end-of period CPI (IFS line 64M..ZF or, if not available, 64Q..ZF); and average annual CPI is calculated using the monthly CPI values (IFS line 64M..ZF) For Eurocurrency  area countries liquid liabilities are estimated by summing IFS items 34A, 34B and 35.

Claims on domestic real nonfinancial sector by the Central Bank as a share of GDP, calculated using the following deflation method:  {(0.5)*[Ft/P_et + Ft-1/P_et-1]}/[GDPt/P_at] where F is Central Bank claims, P_e is end-of period CPI, and P_a is average annual CPI. Raw data are from the electronic version of the IMF's International Financial Statistics. Central Bank claims (IFS lines 12, a-d); GDP in local currency (IFS line 99B..ZF or, if not available, line 99B.CZF); end-of period CPI (IFS line 64M..ZF or, if not available, 64Q..ZF); and average annual CPI is calculated using the monthly CPI values (IFS line 64M..ZF).

Demand, time and saving deposits in deposit money banks and other financial institutions as a share of GDP, calculated using the following deflation method:  {(0.5)*[Ft/P_et + Ft-1/P_et-1]}/[GDPt/P_at] where F is demand and time and saving deposits, P_e is end-of period CPI, and P_a is average annual CPI. Raw data are from the electronic version of the IMF’s International Financial Statistics. Financial system deposits (IFS lines 24, 25, 44, and 45); GDP in local currency (IFS line 99B..ZF or, if not available, line 99B.CZF); end-of period CPI (IFS line 64M..ZF or, if not available, 64Q..ZF); and average annual CPI is calculated using the monthly CPI values (IFS line 64M..ZF).

Premium data is taken from various issues of Sigma reports (Swiss Re). Data on GDP in US dollars is from the electronic version of the World Development Indicators.

The percentage of respondents who report borrowing any money from a bank, credit union, microfinance institution, or another financial institution such as a cooperative in the past 12 months (% age 15+).

The percentage of respondents who report using their accounts at a formal financial institution to receive money or payments from the government in the past 12 months (% age 15+).

The percentage of respondents who report using their accounts at a formal financial institution to receive money from family members living elsewhere in the past 12 months (% age 15+).

The percentage of respondents who report using their accounts at a formal financial institution to receive money or payments for work or from selling goods in the past 12 months (% age 15+).

The percentage of respondents who report saving or setting aside any money in the past 12 months (% age 15+).

The percentage of respondents who borrowed any money in the past 12 months from any of the following sources: a formal financial institution, a store by using installment credit, family or friends, employer, or another private lender (% age 15+). (Note that getting a loan does not necessarily require having an account.)

The percentage of respondents who report borrowing any money from an employer in the past 12 months (% age 15+).

The percentage of respondents who borrowed any money in the past 12 months from a store by using installment credit or buying on credit (% age 15+).

The percentage of respondents who used checks in the past 12 months to make payments on bills or to buy things using money from their accounts (% age 15+).

The percentage of respondents with a credit card (% age 15+).

Percentage of firms with a checking or savings account.

Percentage of loans where a formal financial institution requires collateral in order to provide the financing.

Estimated proportion of purchases of fixed assets that was financed from bank loans.

Proportion of the working capital that was financed by bank loans.

Raw data are from the electronic version of the IMF’s International Financial Statistics. (IFS line 22A + line 22B + line 22C) / GDP. Local currency GDP is from IFS (line 99B..ZF or, if not available, line 99B.CZF).

Ratio of the value of total shares traded to average real market capitalization, the denominator is deflated using the following method:  Tt/P_at/{(0.5)*[Mt/P_et + Mt-1/P_et-1] where T is total value traded, M is stock market capitalization, P_e is end-of period CPI. (IFS line 64M..ZF or, if not available, 64Q..ZF) and annual CPI (IFS line 64..ZF) are from the IMF’s International Financial Statistics.

Consumer price index reflects changes in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used.

A measure of the degree of competition in the banking market. It measures the elasticity of banks revenues relative to input prices. Under perfect competition, an increase in input prices raises both marginal costs and total revenues by the same amount, and hence the H-statistic equals 1. Under a monopoly, an increase in input prices results in a rise in marginal costs, a fall in output, and a decline in revenues, leading to an H-statistic less than or equal to 0. When H is between 0 and 1, the system operates under monopolistic competition.  it is possible for H-stat to be greater than 1 in some oligopolistic markets. (For more information, see Panzar and Rosse 1982, 1987). Calculated from underlying bank-by-bank data from Bankscope.

A measure of market power in the banking market. It is defined as the difference between output prices and marginal costs (relative to prices). Prices are calculated as total bank revenue over assets, whereas marginal costs are obtained from an estimated translog cost function with respect to output. Higher values of the Lerner index indicate less bank competition. Lerner Index estimations follow the methodology described in Demirgüç-Kunt and Martínez Pería (2010). Calculated from underlying bank-by-bank data from Bankscope.

A measure of degree of competition, calculated as the elasticity of profits to marginal costs. To obtain the elasticity, the log of profits (measured by return on assets) is regressed on the log of marginal costs. The estimated coefficient (computed from the first derivative of a trans-log cost function) is the elasticity. The rationale behind the indicator is that higher profits are achieved by more-efficient banks. Hence, the more negative the Boone indicator, the higher the degree of competition is because the effect of reallocation is stronger. Estimations of the Boone indicator in this database follow the methodology used by Schaeck and Čihák (2010) with a modification to use marginal costs instead of average costs. Regional estimates of the Boone indicator pool the bank data by regions (for more information, see Hay and Liu 1997; Boone 2001; Boone, Griffith, and Harrison 2005). Calculated from underlying bank-by-bank data from Bankscope.

Raw data are from Bankscope. (Sum(data2025) for five largest banks in Bankscope) / (Sum(data2025) for all banks in Bankscope). Only reported if number of banks in Bankscope is 5 or more. Calculated from underlying bank-by-bank unconsolidated data from Bankscope.

Raw data are from the electronic version of the IMF's International Financial Statistics. Liquid liabilities (IFS lines 55L..ZF or, if not available, line 35L..ZF); for Eurocurrency area countries (BEF, DEM, ESP, FRF, GRD, IEP, ITL, LUF, NLG, ATS, PTE, FIM), liquid liabilities are estimated by summing IFS items 34A, 34B and 35.

Data is from BIS Statistical Appendix Table 7B: External loans and deposits of reporting banks vis-à-vis nonbanking sectors; bank deposits from IFS (IFS lines 24 and 25). End of year data (i.e. December data) are used.

Percentage of the number of foreign owned banks to the number of the total banks in an Economy. A foreign bank is a bank where 50 percent or more of its shares are owned by foreigners.

GDP data provided by IFS and converted into USD using IFS exchange rates.

For each country calculated as: 1,000*reported number of depositors/adult population in the reporting country.

The percentage of respondents who report saving or setting aside any money by using an account at a formal financial institution such as a bank, credit union, microfinance institution, or cooperative in the past 12 months (% age 15+).

Private credit by deposit money banks and other financial institutions to GDP, calculated using the following deflation method:  {(0.5)*[Ft/P_et + Ft-1/P_et-1]}/[GDPt/P_at] where F is credit to the private sector, P_e is end-of period CPI, and P_a is average annual CPI. Raw data are from the electronic version of the IMF’s International Financial Statistics. Private credit by deposit money banks and other financial institutions (IFS lines 22d and 42d); GDP in local currency (IFS line 99B..ZF or, if not available, line 99B.CZF); end-of period CPI (IFS line 64M..ZF or, if not available, 64Q..ZF); and average annual CPI is calculated using the monthly CPI values (IFS line 64M..ZF)

Value of listed shares to GDP, calculated using the following deflation  method:  {(0.5)*[Ft/P_et + Ft-1/P_et-1]}/[GDPt/P_at] where F is stock market capitalization, P_e is end-of period CPI, and P_a  is average annual CPI. End-of period CPI (IFS line 64M..ZF or, if not available, 64Q..ZF) and average annual CPI is calculated using the monthly CPI values (IFS line 64M..ZF).

Total value of all traded shares in a stock market exchange as a percentage of GDP.  Following deflation method is use:  {(0.5)*[Ft/P_et + Ft-1/P_et-1]}/[GDPt/P_at] where F is stock market capitalization, P_e is end-of period CPI, and P_a  is average annual CPI. End-of period CPI (IFS line 64M..ZF or, if not available, 64Q..ZF) and average annual CPI is calculated using the monthly CPI values (IFS line 64M..ZF).

Total amount of domestic private debt securities (amounts outstanding) issued in domestic markets as a share of GDP. It covers data on long-term bonds and notes, commercial paper and other short-term notes. Table 16A (domestic debt amount): all issuers minus governments / GDP. End of year data (i.e. December data) are considered for debt securities.  The figures are deflated using the following methodology: {(0.5)*[Ft/P_et + Ft-1/P_et-1]}/[GDPt/P_at] where F is the level domestic private debt, P_e is end-of period CPI, and P_a is average annual CPI. GDP is from World Development Indicators. End-of period CPI is taken from IFS line 64M..ZF month of December (or if not available Q4). Average annual CPI is constructed from the monthly CPI figure taken from IFS line 64..ZF.

Total amount of domestic public debt securities (amounts outstanding) issued in domestic markets as a share of GDP. It covers long-term bonds and notes, treasury bills, commercial paper and other short-term notes. Table 16A (domestic debt amount): governments / GDP. End of year data (i.e. December data) are considered for debt securities. The figures are deflated using the following methodology: {(0.5)*[Ft/P_et + Ft-1/P_et-1]}/[GDPt/P_at] where F is the level domestic public debt, P_e is end-of period CPI, and P_a is average annual CPI. GDP is from World Development Indicators. End-of period CPI is taken from IFS line 64M..ZF month of December (or if not available Q4). Average annual CPI is constructed from the monthly CPI figure taken from IFS line 64..ZF.

Total value of outstanding international debt issues both public and private, as a share of GDP. Offshore bank loan data from BIS Statistical Appendix Table 12A (Amount Outstanding): International debt securities - all issuers.

Ratio of gross portfolio equity liabilities to GDP. Equity liabilities include shares, stocks, participation, and similar documents (such as American depository receipts) that usually denote ownership of equity. Raw data are from the electronic version of the IMF's International Financial Statistics. IFS line 79LDDZF/ GDP. Local currency GDP is from IFS (line 99B..ZF or, if not available, line 99B.CZF).

Ratio of gross portfolio equity assets to GDP. Equity assets include shares, stocks, participation, and similar documents (such as American depository receipts) that usually denote ownership of equity. Raw data are from the electronic version of the IMF's International Financial Statistics. IFS line 79ADDZF / GDP. Local currency GDP is from IFS (line 99B..ZF or, if not available, line 99B.CZF).

Ratio of gross portfolio debt liabilities to GDP. Debt liabilities cover (1) bonds, debentures, notes, etc., and (2) money market or negotiable debt instruments. Raw data are from the electronic version of the IMF's International Financial Statistics. IFS line 79LEDZF / GDP. Local currency GDP is from IFS (line 99B..ZF or, if not available, line 99B.CZF).

Raw data are from Bankscope. Data2090[t] / ((data2025[t] + data2025[t-1])/2). Numerator and denominator are first aggregated on the country level before division. Note that banks used in the calculation might differ between indicators. Calculated from underlying bank-by-bank unconsolidated data from Bankscope.

Raw data are from Bankscope.  Data2115[t] / ((data2055[t] + data2055[t-1])/2). Numerator and denominator are first aggregated on the country level before division. Note that banks used in the calculation might differ between indicators. Calculated from underlying bank-by-bank unconsolidated data from Bankscope.

Percent of firms whose most recent loan application was rejected by a formal financial institution.

Percentage of firms identifying access/cost of finance as a "major" or "very severe" obstacle.

Total amount of domestic nonfinancial corporate bonds and notes outstanding (BIS Table 16B) to total amount of domestic bonds and notes outstanding, both corporate and noncorporate (BIS Table 16A).

Claims on domestic real nonfinancial sector by deposit money banks as a share of GDP, calculated using the following deflation method:  {(0.5)*[Ft/P_et + Ft-1/P_et-1]}/[GDPt/P_at] where F is deposit money bank claims, P_e is end-of period CPI, and P_a is average annual CPI. Raw data are from the electronic version of the IMF’s International Financial Statistics. Deposit money bank assets (IFS lines 22, a-d); GDP in local currency (IFS line 99B..ZF or, if not available, line 99B.CZF); end-of period CPI (IFS line 64M..ZF or, if not available, 64Q..ZF); and average annual CPI is calculated using the monthly CPI values (IFS line 64M..ZF).

Claims on domestic real nonfinancial sector by other financial institutions as a share of GDP, calculated using the following deflation method: {(0.5)*[Ft/P_et + Ft-1/P_et-1]}/[GDPt/P_at]  where F is other financial institutions' claims, P_e is end-of period CPI, and P_a is average annual CPI. Raw data are from the electronic version of the IMF’s International Financial Statistics. Nonbank financial institutions assets (IFS lines 42, a-d, h, and s); GDP in local currency (IFS line 99B..ZF or, if not available, line 99B.CZF); end-of period CPI (IFS line 64M..ZF or, if not available, 64Q..ZF); and average annual CPI is calculated using the monthly CPI values (IFS line 64M..ZF).

Data taken from a variety of sources such as Investment Company Institute and national sources.

It captures the probability of default of a country's banking system. Z-score compares the buffer of a country's banking system (capitalization and returns) with the volatility of those returns. It is estimated as (ROA+(equity/assets))/sd(ROA); sd(ROA) is the standard deviation of ROA. ROA, equity, and assets are country-level aggregate figures Calculated from underlying bank-by-bank unconsolidated data from Bankscope.

Reported by IMF staff. Note that due to differences in national accounting, taxation, and supervisory regimes, these data are not strictly comparable across countries.

Raw data are from the electronic version of the IMF’s International Financial Statistics. Private credit by deposit money banks (IFS line 22d); bank deposits (IFS lines 24 and 25).

Provisions to nonperforming loans. Nonperforming Loans are loans for which the contractual payments are delinquent, usually defined as and NPL ratio  being overdue for more than a certain number of days (e.g., usually more than 90 days). Reported by IMF staff. Note that due to differences in national accounting, taxation, and supervisory regimes, these data are not strictly comparable across countries.

Stock price volatility is the average of the 360-day volatility of the national stock market index.

GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2010 U.S. dollars.

GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current U.S. dollars.

Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.

The percentage of respondents with an account (self or together with someone else) at a bank, credit union, another financial institution (e.g., cooperative, microfinance institution), or the post office (if applicable) including respondents who reported having a debit card (% age 15+).

The percentage of respondents who report using their accounts at a formal financial institution for business purposes only or for both business purposes and personal transactions (% age 15+).

The percentage of respondents who report saving or setting aside any money by using an informal savings club or a person outside the family in the past 12 months (% age 15+).

The percentage of respondents who report borrowing any money from a private lender in the past 12 months (% age 15+).

The percentage of respondents who report borrowing any money from family or friends in the past 12 months (% age 15+).

The percentage of respondents with a debit card (% age 15+).

The percentage of respondents who used electronic payments (payments that one makes or that are made automatically including wire transfers or payments made online) in the past 12 months to make payments on bills or to buy things using money from their accounts (% age 15+).

The percentage of respondents who report using a mobile phone to pay bills in the past 12 months (% age 15+).

The percentage of respondents who report using a mobile phone to send money in the past 12 months (% age 15+).

For each country calculated as: 100,000*Number of ATMs/adult population in the reporting country.

Adults depositing/withdrawing at least once in a typical month (% age 15+). It is calculated as follows: (100 - "0 deposits/withdrawals in typical month (% with an account,  age 15+)" ) * ("Account at a formal financial institution (% age 15+)") / 100.  "0 deposits/withdrawals in typical month (% with an account,  age 15+)" denotes the percentage of respondents with an account at a formal financial institution who report making zero deposits into or zero withdrawals from their personal account(s) in a typical month (also called “inactive account”). This includes cash or electronic deposits, or any time money is put into or removed from account(s) by self or others (% age 15+, with an account). "Account at a formal financial institution (% age 15+)" denotes the percentage of respondents with an account (self or together with someone else) at a bank, credit union, another financial institution (e.g., cooperative, microfinance institution), or the post office (if applicable) including respondents who reported having a debit card (% age 15+).

Percentage of firms using banks to finance purchases of fixed assets.

Percentage of firms using bank loans to finance working capital.

Value of collateral needed by a formal financial institution for a loan or line of credit as a percentage of the loan value or the value of the line of credit.

Percent of firms that did not apply for a loan in the last fiscal year because they did not need a loan. The denominator is the sum of all firms who applied and did not apply for a loan. The numerator is the number of firms who did not apply for a loan and also stated that they did not need a loan.

Raw data are from Bankscope.  Data2090 / (data2080 + data2085). All Numerator and denominator are first aggregated on the country level before division. Note that banks used in the calculation might differ between indicators. Calculated from underlying bank-by-bank unconsolidated data from Bankscope.

Raw data are from Bankscope. Data10270[t] / ((data2025[t] + data2025[t-1])/2). Numerator and denominator are first aggregated on the country level before division. Note that banks used in the calculation might differ between indicators. Calculated from underlying bank-by-bank unconsolidated data from Bankscope.

Raw data are from Bankscope.  Data10270[t] / ((data2055[t] + data2055[t-1])/2). Numerator and denominator are first aggregated on the country level before division. Note that banks used in the calculation might differ between indicators. Calculated from underlying bank-by-bank unconsolidated data from Bankscope.

Raw data are from Bankscope. (Sum(data2025) for three largest banks in Bankscope) / (Sum(data2025) for all banks in Bankscope). Only reported if number of banks in Bankscope is 3 or more. Calculated from underlying bank-by-bank unconsolidated data from Bankscope.

Demand, time and saving deposits in deposit money banks as a share of GDP, calculated using the following deflation method: {(0.5)*[Ft/P_et + Ft-1/P_et-1]}/[GDPt/P_at] where F is demand and time and saving deposits, P_e is end-of period CPI, and P_a is average annual CPI. Raw data are from the electronic version of the IMF’s International Financial Statistics. Bank deposits (IFS lines 24 and 25); GDP in local currency (IFS line 99B..ZF or, if not available, line 99B.CZF); end-of period CPI (IFS line 64M..ZF or, if not available, 64Q..ZF); and average annual CPI is calculated using the monthly CPI values (IFS line 64M..ZF).

Ratio of net offshore bank loans to GDP. An offshore bank is a bank located outside the country of residence of the depositor, typically in a low tax jurisdiction (or tax haven) that provides financial and legal advantages. Offshore bank loan data from BIS Statistical Appendix Table 12A (Net Issues): International debt securities - all issuers.

Ratio of outstanding offshore bank loans to GDP. An offshore bank is a bank located outside the country of residence of the depositor, typically in a low tax jurisdiction (or tax haven) that provides financial and legal advantages. Offshore bank loan data from BIS Statistical Appendix Table 7A: External loans and deposits of reporting banks vis-à-vis all sectors.

Data is from BIS Statistical Appendix Table 7A minus 7B: External loans and deposits of reporting banks vis-à-vis all sectors minus external loans and deposits of reporting banks vis-à-vis nonbanking sectors; bank deposits from IFS (IFS lines 24 and 25). End of year data (i.e. December data) are used.

Data is from BIS Statistical Appendix Table 7A: External loans and deposits of reporting banks vis-à-vis all sectors; bank deposits from IFS (IFS lines 24 and 25). End of year data (i.e. December data) are used.

Workers' remittances and compensation of employees comprise current transfers by migrant workers and wages and salaries earned by nonresident workers. Data are the sum of three items defined in the fifth edition of the IMF's Balance of Payments Manual: workers' remittances, compensation of employees, and migrants' transfers. Remittances are classified as current private transfers from migrant workers resident in the host country for more than a year, irrespective of their immigration status, to recipients in their country of origin. Migrants' transfers are defined as the net worth of migrants who are expected to remain in the host country for more than one year that is transferred from one country to another at the time of migration. Compensation of employees is the income of migrants who have lived in the host country for less than a year.

The ratio of consolidated foreign claims to GDP of the banks that are reporting to BIS. Foreign claims are defined as the sum of cross-border claims plus foreign offices’ local claims in all currencies. In the consolidated banking statistics claims that are granted or extended to nonresidents are referred to as either cross-border claims.  In the context of the consolidated banking statistics, local claims refer to claims of domestic banks’ foreign affiliates (branches/subsidiaries) on the residents of the host country (i.e. country of residence of affiliates). Items (A+L from BIS Table 9A). End-of-year data (i.e. December data) are considered for banks claims. GDP is from World Development Indicators.

Percentage of the total banking assets that are held by foreign banks. A foreign bank is a bank where 50 percent or more of its shares are owned by foreigners.

For each country calculated as: 100,000*reported number of depositors/adult population in the reporting country.

Percentage of firms in the formal sector with a line of credit or a loan from a formal financial institution, such as a bank, credit union, microfinance institution, or cooperative.

Percentage of small firms (5-19 workers) in the formal sector with a line of credit or a loan from a (formal) financial institution, such as a bank, credit union, microfinance institution, or cooperative.

Raw data are from Bankscope.  Data2075 / data2030. Numerator and denominator are first aggregated on the country level before division. Calculated from underlying bank-by-bank unconsolidated data from Bankscope.

GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current U.S. dollars. Dollar figures for GDP are converted from domestic currencies using single year official exchange rates. For a few countries where the official exchange rate does not reflect the rate effectively applied to actual foreign exchange transactions, an alternative conversion factor is used.

GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2010 U.S. dollars. Dollar figures for GDP are converted from domestic currencies using 2010 official exchange rates. For a few countries where the official exchange rate does not reflect the rate effectively applied to actual foreign exchange transactions, an alternative conversion factor is used.

Global Financial Development

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