East Asia & Pacific (IDA & IBRD): Automated teller machines (ATMs) (per 100,000 adults)

Key figures

What the numbers say

In 2024, East Asia & Pacific (IDA & IBRD)'s automated teller machines (ATMs) (per 100,000 adults) rose 7.57 on 2023 (from 38.07 to 45.64).

Across the 18 yearly changes before that (2006 to 2023), the average change was +1.61 and a typical year strayed about 1.44 from that (the standard deviation). This year's change was 4.1 standard deviations above that average, so it was unusually large compared with the rest of the record.

On record, the biggest yearly rise was 7.57 in 2024. The numbers show how large and when, not why; for the cause, look at what happened in that country in those years.

From 2015 to 2024 the straight-line trend is upward, about 2.12 a year. A straight line explains 84% of the movement over 10 observed years.

Worked out from the yearly values above. How the checks work: standard deviation, z-scores and straight-line trends.

How it compares

See how every economy compares in the full ranking.

What this measures

Automated teller machines (ATMs) are electromechanical devices which enable customers of financial institutions to perform financial transactions such as cash withdrawals, balance inquiries, deposits, transfer of funds, and obtaining account information, using an electronic card.

Limitations: Population-based ratios of the number of branches and ATMs assume a uniform distribution of bank outlets within a country's area and across its population, while in most countries bank branches and ATMs are concentrated in urban centers of the country and are accessible only to some individuals.

Regional and income-group figures are computed by the World Bank as a median.

All 20 values

Automated teller machines (ATMs) (per 100,000 adults) in nearby economies

• Afghanistan — 1.79 (2019)
• Algeria — 12.09 (2024)
• Bahrain — 31.36 (2024)
• Djibouti — 17.64 (2024)
• Egypt, Arab Rep. — 37.06 (2024)
• Iran, Islamic Rep. — 83.63 (2018)
• Iraq — 14.18 (2023)
• Israel — 133.06 (2024)
• Jordan — 30.36 (2024)
• Kuwait

More financial sector data for East Asia & Pacific (IDA & IBRD)

• Inflation, GDP deflator (annual % growth) — 2.96% (2025)
• Monetary sector credit to private sector (% of GDP) — 176.6% (2024)
• Broad money (% of GDP) — 210.61% (2024)
• Claims on central government, etc. (% of GDP) — 42.53% (2024)
• Domestic credit to private sector (% of GDP) — 177.72% (2024)
• Stocks traded, turnover ratio of domestic shares (%) — 269.56% (2024)
• Domestic credit to private sector by banks (% of GDP) — 176.6% (2024)
• Inflation, consumer prices (annual % growth)

Reading data like this

• Where to find free public data, and how to check it before you trust it — 2 min read
• Data analysis examples: 6 worked from one dataset — 3 min read
• Real change or random noise? A plain guide to reading your numbers — 2 min read

Questions people ask

What is East Asia & Pacific (IDA & IBRD)'s automated teller machines (ATMs) (per 100,000 adults)?

45.64 in 2024, according to the World Bank (World Development Indicators).

How has it changed since 2005?

It is up 405.38% from 9.03 in 2005 (8.9% a year on average, compounded). The highest value was 45.64 in 2024 and the lowest 9.03 in 2005.

Is the latest change in automated teller machines (ATMs) (per 100,000 adults) unusual for East Asia & Pacific (IDA & IBRD)?

In 2024, East Asia & Pacific (IDA & IBRD)'s automated teller machines (ATMs) (per 100,000 adults) rose 7.57 on 2023 (from 38.07 to 45.64). Across the 18 yearly changes before that (2006 to 2023), the average change was +1.61 and a typical year strayed about 1.44 from that (the standard deviation). This year's change was 4.1 standard deviations above that average, so it was unusually large compared with the rest of the record.

Source

World Bank, World Development Indicators, indicator FB.ATM.TOTL.P5, licensed CC BY 4.0. Original source: Financial Access Survey, International Monetary Fund (IMF), uri: https://data.imf.org/?sk=E5DCAB7E-A5CA-4892-A6EA-598B5463A34C Figures are fetched from the World Bank API and refreshed monthly; see the series on data.worldbank.org. The full definition and method are in the World Bank's metadata glossary. Comparisons use the same World Bank release.

Want to ask your own questions of data like this? Try AnalyzeIt: upload a file or ask about public data in plain words, and every figure comes with its working.