Financial inclusion / PAK
Pakistan
Pakistan appears in 5 of the 5 Global Findex rounds in this file (2011, 2014, 2017, 2021, 2024).
Account ownership by group
Share of adults aged 15 and over with an account at a bank or with a mobile money provider. Each line is a separate survey estimate on a subsample, not a decomposition of the total.
Source: World Bank Global Findex Database 2025 (CC BY-4.0) Indicators account.t.d, account.t.d.1, account.t.d.2, account.t.d.7. Methodology
| Account ownership | 2011 | 2014 | 2017 | 2021 | 2024 |
|---|---|---|---|---|---|
| Women | 3.0% | 4.8% | 7.0% | 13.5% | 11.9% |
| Men | 17.3% | 21.0% | 34.6% | 28.2% | 42.3% |
| Poorest 40% | 4.8% | 9.8% | 14.2% | 17.6% | 13.6% |
| Richest 60% | 13.9% | 15.2% | 26.0% | 23.2% | 36.4% |
| Age 15-24 | 8.0% | 13.2% | 14.9% | 18.1% | 24.3% |
| Age 25+ | 11.4% | 13.0% | 24.5% | 22.5% | 28.5% |
| Primary education or less | 3.7% | 10.0% | 15.9% | 15.3% | 18.9% |
| Secondary education or more | 24.5% | 25.2% | 34.0% | 35.3% | 46.7% |
| Rural | - | - | - | - | 21.1% |
| Urban | - | - | - | - | 32.9% |
Source: World Bank Global Findex Database 2025 (CC BY-4.0) A dash means the cut is not reported for Pakistan in that round. The rural and urban cuts exist in one round only. Methodology
The gaps
Gender gap is the men’s account rate minus the women’s; income gap is the richest 60% minus the poorest 40%. Both are differences between two survey estimates and the file publishes no standard error for either, so a gap of a few points is not distinguishable from zero.
Source: World Bank Global Findex Database 2025 (CC BY-4.0) account.t.d.2 minus account.t.d.1; account.t.d.8 minus account.t.d.7. Methodology
Payments, saving and borrowing
The digital-payment, saved and borrowed indicators are not collected in every round or for every economy: in the 2024 round they are reported for a subset of the economies that report account ownership.
| Share of adults age 15+ | 2011 | 2014 | 2017 | 2021 | 2024 |
|---|---|---|---|---|---|
| Made or received a digital payment | - | 9.5% | 17.7% | 17.6% | 24.6% |
| Mobile money account | - | 5.8% | 6.9% | 8.5% | 18.4% |
| Saved at a bank or using mobile money | 1.4% | 3.3% | 6.1% | 2.8% | 12.7% |
| Borrowed from a bank or using mobile money | - | 1.6% | 2.6% | 3.6% | 8.0% |
Source: World Bank Global Findex Database 2025 (CC BY-4.0) Indicators g20.any, mobileaccount.t.d, fin17a.17a1.d, fin22a.22a1.22g.d. A dash means no reading for Pakistan in that round. Methodology
Physical access points
From the IMF Financial Access Survey by way of the GFDD, which stops in 2021. Each figure is Pakistan’s latest reported year, which is shown beside it and is not necessarily the same year as another economy’s. These are the published values, reproduced without adjustment; for at least one economy the published branch and ATM counts are not physically possible, which the methodology page documents.
Source: World Bank Global Financial Development Database | IMF Financial Access Survey GFDD.AI.02 and GFDD.AI.25, latest reported year for this economy. Methodology
Access infrastructure (IMF Financial Access Survey)
Findex above measures use: whether adults say they have an account. The FAS measures infrastructure: what regulators count. For Pakistan the FAS carries readings from 2004 to 2024, annual rather than in survey rounds, pulled directly from the IMF’s API. In 2024, mobile-money transactions ran at 34,249 per 1,000 adults, about 34 transactions per adult over the year.
Source: IMF Financial Access Survey Access points per 100,000 adults (FA26N, FA18N, FA5N). MM agents are active mobile-money agent outlets, reported only where the country serves mobile money. Methodology
Accounts per 1,000 adults. A registered mobile-money count above 1,000 means more registrations than adults; registration is not use, and an active count (90-day use) runs well below it where both are reported.
Source: IMF Financial Access Survey Accounts per 1,000 adults (FA30N_COMBANK, LOANACCN_COMBANK, FA67N, FA63N), commercial banks and mobile money. Methodology