Equatorial Guinea vs Montenegro: Number of Borrowers, Commercial Banks, of Which: Household Sector
Equatorial Guinea
65,374
in 2022
Montenegro
159,194
in 2024
Equatorial Guinea rank
76th
Montenegro rank
73rd
Number of Borrowers, Commercial Banks, of Which: Household Sector over time
- Equatorial Guinea
- Montenegro
How they compare
Montenegro currently reports 159,194 against 65,374 in Equatorial Guinea, a difference of 93,820.
That makes Montenegro's figure about 2.4 times Equatorial Guinea's.
Across all 16 years both countries report, Montenegro has been ahead every year.
Equatorial Guinea ranks 76th and Montenegro ranks 73rd of 89 countries.
Montenegro has averaged higher in every one of the 3 decades both report.
Head to head by decade
| Decade | Equatorial Guinea | Montenegro | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 2,680 | 124,912 | 122,232 | Montenegro |
| 2010s | 13,378 | 109,547 | 96,169 | Montenegro |
| 2020s | 44,002 | 138,814 | 94,812 | Montenegro |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher number of borrowers, commercial banks, of which: household sector, Equatorial Guinea or Montenegro?
- Montenegro, at 159,194 against 65,374 in Equatorial Guinea as of 2024.
- What is the difference in number of borrowers, commercial banks, of which: household sector between Equatorial Guinea and Montenegro?
- 93,820, with Montenegro ahead.
- How many years of comparable data are there for Equatorial Guinea and Montenegro?
- 16 years are reported by both, from 2007 to 2022.
- How do Equatorial Guinea and Montenegro rank globally for number of borrowers, commercial banks, of which: household sector?
- Equatorial Guinea ranks 76th and Montenegro ranks 73rd of 89 countries.
- Where does this data come from?
- International Monetary Fund, published as Number of Borrowers, Commercial Banks, of Which: Household Sector Borrowers. Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
Gender-disaggregated data on access to and use of financial services.