Northern Mariana Islands: Automated teller machines (ATMs) (per 100,000 adults)

Key figures

What the numbers say

In 2019, Northern Mariana Islands' automated teller machines (ATMs) (per 100,000 adults) rose 1.73 on 2018 (from 59.81 to 61.54).

Across the 13 yearly changes before that (2006 to 2018), the average change was +3.87 and a typical year strayed about 5.17 from that (the standard deviation). This year's change was 0.4 standard deviations below that average, so it was an ordinary year: it sits within the range of normal year-to-year movement.

On record, the biggest yearly rise was 13.78 in 2007 and the biggest yearly fall was 1.6 in 2012. The numbers show how large and when, not why; for the cause, look at what happened in that country in those years.

From 2010 to 2019 the straight-line trend is upward, about 1.37 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.

Closest to Northern Mariana Islands in the 2019 ranking

• Afghanistan — 2nd of 2: 1.79

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 15 values

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

• Australia — 105.22 (2024)
• Brunei Darussalam — 70.92 (2021)
• Cambodia — 47.61 (2024)
• China — 67.83 (2024)
• Fiji — 45.49 (2024)
• Hong Kong SAR, China — 46.04 (2024)
• Indonesia — 45.64 (2024)
• Japan — 107.04 (2024)
• Korea, Rep. — 244.47 (2023)
• Lao PDR

More financial sector data for Northern Mariana Islands

• Official exchange rate (LCU per US$, period average) — US$1 (2025)
• DEC alternative conversion factor (LCU per US$) — US$1 (2024)
• GDP deflator (base year varies by country) — 134.81 (2022)
• GDP deflator, linked series (base year varies by country) — 134.81 (2022)
• Inflation, GDP deflator (annual % growth) — 2.8% (2022)
• Inflation, GDP deflator, linked series (annual % growth) — 2.8% (2022)

Every indicator for Northern Mariana Islands is on the Northern Mariana Islands data page.

Reading data like this

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Questions people ask

What is Northern Mariana Islands's automated teller machines (ATMs) (per 100,000 adults)?

61.54 in 2019, according to the World Bank (World Development Indicators).

How has it changed since 2005?

It is up 544.41% from 9.55 in 2005 (14.23% a year on average, compounded). The highest value was 61.54 in 2019 and the lowest 9.55 in 2005.

Is the latest change in automated teller machines (ATMs) (per 100,000 adults) unusual for Northern Mariana Islands?

In 2019, Northern Mariana Islands' automated teller machines (ATMs) (per 100,000 adults) rose 1.73 on 2018 (from 59.81 to 61.54). Across the 13 yearly changes before that (2006 to 2018), the average change was +3.87 and a typical year strayed about 5.17 from that (the standard deviation). This year's change was 0.4 standard deviations below that average, so it was an ordinary year: it sits within the range of normal year-to-year movement.

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.

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