Financial inclusion
Who has an account, who does not, and which gap actually closed
The Global Findex asks adults in each economy whether they have an account at a bank or with a mobile money provider. This file carries 162 economies across 5 survey rounds, 2011 to 2024. In the 2024 round, 140 economies report account ownership: the median is 72.9% of adults aged 15 and over, from 14.8% in Niger to 99.9% in Iceland.
Account ownership, 2011 to 2024
The median runs over the 117 economies with a reading in all 5 rounds, so the line moves with the world and not with the sample: it rose from 41.3% to 78.8%. The rounds are unevenly spaced, so the x axis is the round, not a year.
Source: World Bank Global Findex Database 2025 (CC BY-4.0) Indicator account.t.d. Balanced panel of 117 economies. Methodology
Economy by economy: of the 128 with an account reading in both the 2011 and the 2024 round, 118 are higher in 2024, 10 are lower, and the median change is 21.6 points. Points above the dashed line gained.
Source: World Bank Global Findex Database 2025 (CC BY-4.0) Indicator account.t.d. 128 economies with a reading in both rounds; the dashed line is no change. Methodology
Do not subtract the medians. Over these same 128 economies the median level moved from 40.5% to 74.5%, a shift of 34.1 points, while the median economy gained 21.6. Both are correct and they are different statistics. Splitting the same 128 into quartiles by their 2011 level shows why: the 32 economies in the highest quartile gained a median of 2.2 points, having started with a median of 95.5%, while the 32 in the lowest gained 36.1.
| Quartile of 2011 account ownership | Economies | Range, 2011 | Median, 2011 | Median, 2024 | Median change |
|---|---|---|---|---|---|
| Q1 | 32 | 1.5% to 19.6% | 12.0% | 51.6% | 36.1 |
| Q2 | 32 | 20.5% to 39.7% | 27.7% | 59.8% | 30.0 |
| Q3 | 32 | 41.3% to 77.9% | 59.9% | 84.9% | 21.9 |
| Q4 | 32 | 79.6% to 99.7% | 95.5% | 98.0% | 2.2 |
Source: World Bank Global Findex Database 2025 (CC BY-4.0) Indicator account.t.d. Quartiles of the 128 economies by their 2011 level. Methodology
The income gap narrowed. The gender gap did not.
Both lines are medians over a balanced panel and are in the same unit, percentage points of account ownership. The gender gap (men minus women) runs over the 106 economies with both cuts in all 5 rounds: 3.6 points in 2011, 3.9 points in 2024. The income gap (richest 60% minus poorest 40%) runs over 102 economies: 14.1 points in 2011, 11.1 points in 2024.
Source: World Bank Global Findex Database 2025 (CC BY-4.0) Gender: account.t.d.2 minus account.t.d.1, 106 economies. Income: account.t.d.8 minus account.t.d.7, 102 economies. Methodology
Of the 117 economies with both cuts in the 2011 and 2024 rounds (a wider set than the 106-economy panel charted above, which needs all 5 rounds), the gap is narrower in 52 and wider in 65. The median moved from 3.59 to 3.63 points.
The movement is concentrated at the top. Of the 28 economies whose 2011 gap was 10 points or more, 19 narrowed and 9 widened, and their median gap fell from 15.5 to 9.6 points. Of the 89 that started below 10 points, 33 narrowed and 56 widened, and their median moved from 2.0 to 2.1 points.
Of the 110 economies with both cuts in the 2011 and 2024 rounds (again a wider set than the 102-economy panel above), the gap is narrower in 73 and wider in 37. The median moved from 13.99 to 11.37 points.
In the 2024 round, 139 economies report both cuts. The richest 60% are ahead in 127 of them and the poorest 40% are ahead in 12; the median gap is 11.1 points.
The gender gap in the 2024 round
140 economies report both cuts. Men are ahead in 112 of them and women in 28; the median gap is 4.5 points. Green bars are economies where women are ahead.
Source: World Bank Global Findex Database 2025 (CC BY-4.0) account.t.d.2 minus account.t.d.1, 2024 round, 2-point bins. Methodology
| Widest gender gaps, 2024 | Women | Men | Gap |
|---|---|---|---|
| Algeria | 18.1% | 51.9% | 33.8 |
| Pakistan | 11.9% | 42.3% | 30.4 |
| Togo | 45.3% | 70.0% | 24.7 |
| Palestine | 27.7% | 51.2% | 23.4 |
| Tunisia | 26.6% | 49.6% | 23.0 |
| Nigeria | 52.2% | 74.3% | 22.1 |
| Iraq | 18.8% | 40.8% | 22.0 |
| Azerbaijan | 46.2% | 67.0% | 20.8 |
| El Salvador | 34.4% | 54.7% | 20.3 |
| Bangladesh | 33.3% | 53.5% | 20.2 |
Source: World Bank Global Findex Database 2025 (CC BY-4.0) Ten widest of 140 economies. Methodology
Digital payments after 2014
The digital-payment question (g20.any) carries no rows before the 2014 round. Across the 85 economies that report it in all 4 rounds that have it, the median share of adults who made or received a digital payment rose from 25.5% in 2014 to 51.8% in 2024. Mobile money accounts are reported for 80 economies in the 2024 round, with a median of 31.9% and a maximum of 87.5% in Kenya.
Source: World Bank Global Findex Database 2025 (CC BY-4.0) Indicator g20.any. Balanced panel of 85 economies. Methodology
The rural gap cannot be tracked over time
The rural (account.t.d.9) and urban (account.t.d.10) cuts of the account indicator carry rows in 1 of the 5 rounds in this file (2024), and none in the others. There is no earlier rural gap to compare against, so what follows is a level and not a trend. In the 2024 round, 137 economies report both cuts: the median urban-minus-rural gap is 4.5 points, urban adults are ahead in 101 economies and rural adults are ahead in 36.
Source: World Bank Global Findex Database 2025 (CC BY-4.0) account.t.d.10 minus account.t.d.9, 2024 round, 2-point bins. Green bars are economies where the rural rate is higher. Methodology
Branches, and a branch series that cannot be taken at face value
Bank branches per 100,000 adults, from the IMF Financial Access Survey by way of the GFDD, against account ownership. Across the 124 economies with both, the Spearman rank correlation is 0.41. The two readings are 4 years apart: 2020 is the last GFDD year in which at least 100 economies report a branch count, and 2024 is the latest Findex round.
Source: World Bank Global Financial Development Database | IMF Financial Access Survey | World Bank Global Findex Database 2025 (CC BY-4.0) GFDD.AI.02 (2020) against account.t.d (2024 round). Methodology
What this data cannot tell you
- Whether a small gap is a real gap. The Findex file in this estate has four columns (iso3, year, indicator_code, value). It carries no standard error and no sample size, so a difference of a few points between two subgroups cannot be distinguished from zero using the file alone. The World Bank publishes a margin of error for each economy’s full national sample: in the 2025 report those run from 2.1 to 5.4 percentage points on a median sample of 1,000 interviews. A subgroup is a fraction of that sample, so its margin is wider still.
- A change for every economy. Only 117 of the 162 economies in the file have an account reading in all 5 rounds. 128 have one in both the 2011 and the 2024 round, which is the only set on which a change since the first round is defined.
- Anything about rural adults before 2024. The rural and urban cuts exist in one round only.
- What is actually in the account. Every Findex value is a self-reported survey answer, not an administrative record. No balance and no transaction record underlies any number here.
- How many branches an economy really has. The GFDD branch and ATM series carry values that cannot be physical: Saudi Arabia’s 2020 reading is one branch for every 63 adults. They are published here as the World Bank publishes them, which is why the cross-economy statistic above is a rank correlation.
- Anything about financial systems after 2021. The GFDD half of this layer stops in 2021, and its last year is thin, which is why the cross-section above uses 2020, the last year with at least 100 reporting economies. The coverage by year is on the methodology page.
155 economies with a page
An economy gets a page when it has an account reading in two or more rounds, so that a change is defined. That is 155 of the 162 economies in the file. The other 7 appear in exactly one round and have no page: Bhutan (2014), Djibouti (2011), Maldives (2017), Puerto Rico (2014), Qatar (2011), Somalia (2014), Syria (2011).
| Economy | Rounds | Account, 2011 | Account, 2024 | Gender gap, 2024 |
|---|---|---|---|---|
| Afghanistan | 4 | 9.0% | - | - |
| Albania | 5 | 28.3% | 46.1% | 10.3 |
| Algeria | 5 | 33.3% | 35.3% | 33.8 |
| Angola | 2 | 39.2% | - | - |
| Argentina | 5 | 33.1% | 81.7% | -5.3 |
| Armenia | 5 | 17.5% | 71.4% | 7.6 |
| Australia | 5 | 99.1% | 98.0% | 0.6 |
| Austria | 5 | 97.1% | 99.5% | 0.7 |
| Azerbaijan | 5 | 14.9% | 56.3% | 20.8 |
| Bahrain | 4 | 64.5% | 82.3% | -1.1 |
| Bangladesh | 5 | 31.7% | 43.3% | 20.2 |
| Belarus | 3 | 58.6% | - | - |
| Belgium | 5 | 96.3% | 98.2% | 0.6 |
| Belize | 2 | - | 68.0% | 5.9 |
| Benin | 5 | 10.5% | 51.8% | 6.0 |
| Bolivia | 5 | 28.0% | 56.8% | 6.9 |
| Bosnia and Herzegovina | 5 | 56.2% | 77.5% | 3.5 |
| Botswana | 5 | 30.3% | 61.4% | 3.9 |
| Brazil | 5 | 55.9% | 86.4% | 8.6 |
| Bulgaria | 5 | 52.8% | 84.7% | -0.7 |
| Burkina Faso | 5 | 13.4% | 51.4% | 15.8 |
| Burundi | 2 | 7.2% | - | - |
| Cambodia | 5 | 3.7% | 39.0% | 4.8 |
| Cameroon | 5 | 14.8% | 60.9% | 16.5 |
| Canada | 5 | 95.8% | 98.4% | -0.7 |
| Central African Republic | 2 | 3.3% | - | - |
| Chad | 5 | 9.0% | 20.9% | 1.6 |
| Chile | 5 | 42.2% | 85.1% | 3.9 |
| China | 5 | 63.8% | 89.4% | 0.4 |
| Colombia | 5 | 30.4% | 57.1% | 12.7 |
| Comoros | 3 | 21.7% | 45.5% | 7.8 |
| Congo DR | 5 | 3.7% | 39.2% | 11.1 |
| Costa Rica | 5 | 50.4% | 71.4% | 6.2 |
| Croatia | 5 | 88.4% | 92.6% | 1.2 |
| Cyprus | 5 | 85.2% | 96.1% | -3.8 |
| Czech Republic | 5 | 80.7% | 92.3% | 5.3 |
| Denmark | 5 | 99.7% | 98.7% | 1.1 |
| Dominican Republic | 5 | 38.2% | 64.8% | 6.8 |
| Ecuador | 5 | 36.7% | 64.5% | 2.1 |
| Egypt | 5 | 9.7% | 43.1% | 5.7 |
| El Salvador | 5 | 13.8% | 43.4% | 20.3 |
| Estonia | 5 | 96.8% | 98.9% | -1.8 |
| Eswatini | 3 | 28.6% | 65.1% | -0.5 |
| Ethiopia | 4 | - | 48.8% | 14.9 |
| Finland | 5 | 99.7% | 99.8% | 0.3 |
| France | 5 | 97.0% | 99.2% | -1.4 |
| Gabon | 5 | 18.9% | 68.2% | 8.7 |
| Gambia | 3 | - | 38.2% | 6.9 |
| Georgia | 5 | 33.0% | 78.8% | -5.4 |
| Germany | 5 | 98.1% | 98.3% | -1.2 |
| Ghana | 5 | 29.4% | 81.2% | 6.1 |
| Greece | 5 | 77.9% | 88.6% | 9.2 |
| Guatemala | 5 | 22.3% | 38.3% | 12.1 |
| Guinea | 5 | 3.7% | 36.0% | 9.6 |
| Haiti | 3 | 22.0% | - | - |
| Honduras | 5 | 20.5% | 42.4% | 18.7 |
| Hong Kong | 5 | 88.7% | 97.3% | 1.2 |
| Hungary | 5 | 72.7% | 87.0% | 6.8 |
| Iceland | 2 | - | 99.9% | 0.3 |
| India | 5 | 35.2% | 89.0% | -0.4 |
| Indonesia | 5 | 19.6% | 56.3% | -3.4 |
| Iran | 5 | 73.7% | 91.1% | 8.5 |
| Iraq | 5 | 10.6% | 30.2% | 22.0 |
| Ireland | 5 | 93.9% | 98.3% | 2.7 |
| Israel | 5 | 90.5% | 89.3% | 2.4 |
| Italy | 5 | 71.0% | 86.0% | 12.8 |
| Ivory Coast | 4 | - | 57.6% | 7.4 |
| Jamaica | 3 | 71.0% | - | - |
| Japan | 5 | 96.4% | 98.5% | -0.4 |
| Jordan | 5 | 25.5% | 46.5% | 19.7 |
| Kazakhstan | 5 | 42.1% | 87.0% | 2.8 |
| Kenya | 5 | 42.3% | 90.1% | 7.4 |
| Kosovo | 5 | 44.3% | 64.2% | 9.0 |
| Kuwait | 4 | 86.8% | 74.5% | 4.6 |
| Kyrgyzstan | 5 | 3.8% | 72.3% | 2.1 |
| Laos | 4 | 26.8% | 37.7% | -11.9 |
| Latvia | 5 | 89.7% | 95.0% | -1.0 |
| Lebanon | 5 | 37.0% | 23.0% | 15.7 |
| Lesotho | 4 | 18.5% | 61.6% | 2.5 |
| Liberia | 4 | 18.8% | 52.2% | 11.9 |
| Libya | 2 | - | 33.1% | 16.7 |
| Lithuania | 5 | 73.8% | 99.0% | 1.2 |
| Luxembourg | 3 | 94.6% | - | - |
| Macedonia | 5 | 73.7% | 84.3% | 14.4 |
| Madagascar | 5 | 5.5% | 24.5% | 8.7 |
| Malawi | 5 | 16.5% | 50.4% | 8.6 |
| Malaysia | 5 | 66.2% | 88.7% | 0.9 |
| Mali | 5 | 8.2% | 54.7% | 18.6 |
| Malta | 5 | 95.3% | 96.6% | 1.0 |
| Mauritania | 5 | 17.5% | 27.3% | 5.6 |
| Mauritius | 5 | 80.1% | 89.6% | 4.3 |
| Mexico | 5 | 27.4% | 53.0% | 11.7 |
| Moldova | 5 | 18.1% | 55.5% | 2.1 |
| Mongolia | 5 | 77.7% | 98.3% | -1.5 |
| Montenegro | 4 | 50.4% | 75.4% | 4.2 |
| Morocco | 2 | - | 44.4% | 19.9 |
| Mozambique | 3 | - | 54.4% | 17.9 |
| Myanmar | 3 | - | - | - |
| Namibia | 4 | - | 72.9% | -4.4 |
| Nepal | 5 | 25.3% | 60.0% | 0.4 |
| Netherlands | 5 | 98.7% | 99.2% | -0.2 |
| New Zealand | 5 | 99.4% | 97.9% | -1.4 |
| Nicaragua | 5 | 14.2% | 23.5% | 4.7 |
| Niger | 5 | 1.5% | 14.8% | 5.4 |
| Nigeria | 5 | 29.7% | 63.3% | 22.1 |
| Norway | 4 | - | 98.6% | 1.4 |
| Oman | 2 | 73.6% | 69.5% | 3.6 |
| Pakistan | 5 | 10.3% | 27.3% | 30.4 |
| Palestine | 5 | 19.4% | 39.6% | 23.4 |
| Panama | 5 | 24.9% | 64.1% | 12.3 |
| Paraguay | 4 | 21.7% | 60.9% | 1.7 |
| Peru | 5 | 20.5% | 59.3% | 6.3 |
| Philippines | 5 | 26.6% | 50.2% | -14.1 |
| Poland | 5 | 70.2% | 86.1% | -0.4 |
| Portugal | 5 | 81.2% | 91.4% | 6.6 |
| Republic of the Congo | 5 | 10.0% | 55.6% | 10.0 |
| Romania | 5 | 44.6% | 71.3% | 3.1 |
| Russian Federation | 5 | 48.2% | 79.3% | 4.4 |
| Rwanda | 3 | 32.8% | - | - |
| Saudi Arabia | 5 | 46.4% | 78.8% | 8.4 |
| Senegal | 5 | 5.8% | 76.5% | 6.0 |
| Serbia | 5 | 62.2% | 83.3% | 4.6 |
| Sierra Leone | 5 | 15.3% | 38.6% | 5.5 |
| Singapore | 5 | 98.2% | 98.0% | 0.7 |
| Slovakia | 5 | 79.6% | 92.2% | 2.3 |
| Slovenia | 5 | 97.1% | 98.7% | -0.4 |
| South Africa | 5 | 53.6% | 81.1% | 0.3 |
| South Korea | 5 | 93.0% | 96.9% | -0.5 |
| South Sudan | 2 | - | - | - |
| Spain | 5 | 93.3% | 98.4% | 1.2 |
| Sri Lanka | 5 | 68.5% | 81.7% | 3.2 |
| Sudan | 2 | 6.9% | - | - |
| Sweden | 5 | 99.0% | 98.6% | 1.9 |
| Switzerland | 4 | - | 98.4% | 1.6 |
| Taiwan | 5 | 87.3% | 95.6% | -0.1 |
| Tajikistan | 5 | 2.5% | 54.5% | 15.7 |
| Tanzania | 5 | 17.3% | 59.8% | 10.4 |
| Thailand | 5 | 72.7% | 91.8% | -1.8 |
| Togo | 5 | 10.2% | 57.4% | 24.7 |
| Trinidad and Tobago | 3 | 75.9% | 74.6% | 2.6 |
| Tunisia | 4 | - | 37.8% | 23.0 |
| Turkey | 5 | 57.6% | 81.6% | 19.9 |
| Turkmenistan | 2 | 0.4% | - | - |
| Uganda | 5 | 20.5% | 72.8% | 13.9 |
| Ukraine | 5 | 41.3% | 87.6% | 7.6 |
| United Arab Emirates | 4 | 59.7% | - | - |
| United Kingdom | 5 | 97.2% | 99.3% | 0.0 |
| United States | 5 | 88.0% | 97.0% | -0.2 |
| Uruguay | 5 | 23.5% | 73.7% | 1.0 |
| Uzbekistan | 5 | 22.5% | 59.7% | -2.2 |
| Venezuela | 5 | 44.1% | 87.3% | -0.8 |
| Vietnam | 5 | 21.4% | 70.6% | 1.4 |
| Yemen | 3 | 3.7% | - | - |
| Zambia | 5 | 21.4% | 72.7% | 5.3 |
| Zimbabwe | 5 | 39.7% | 49.5% | 5.4 |
Source: World Bank Global Findex Database 2025 (CC BY-4.0) A dash means the economy has no reading for that cell. Gender gap is account.t.d.2 minus account.t.d.1. Methodology