Bank non-performing loans to gross loans (%) in Equatorial Guinea
Equatorial Guinea: Bank non-performing loans to gross loans (%) was 48.8% in 2019. ◆ Volatile
Bank non-performing loans to gross loans in Equatorial Guinea, 2010–2019
Source: Financial Soundness Indicators Database (fsi.imf.org), International Monetary Fund (IMF). Measured in %.
Analysis
The most recent figure for bank non-performing loans to gross loans in Equatorial Guinea is 48.8%, measured in 2019. That is the highest value across all 10 years on record.
That represents a change of up 33.1% on the previous year and up 934.1% over ten years.
Over the whole period, bank non-performing loans to gross loans in Equatorial Guinea peaked at 48.8% in 2019 and was at its lowest, 4.4%, in 2011.
Equatorial Guinea ranks 1st of 141 countries on this measure, in the top 10%.
The series is highly variable year to year, so single readings are best treated with caution.
Bank non-performing loans to gross loans (%) in Equatorial Guinea, year by year
| Year | % | Change |
|---|---|---|
| 2010 | 4.7% | — |
| 2011 | 4.4% | -6.4% |
| 2012 | 5.8% | +30.6% |
| 2013 | 20.1% | +249.0% |
| 2014 | 19.7% | -2.0% |
| 2015 | 16.8% | -14.9% |
| 2016 | 24.6% | +46.7% |
| 2017 | 27.2% | +10.4% |
| 2018 | 36.7% | +34.8% |
| 2019 | 48.8% | +33.1% |
Equatorial Guinea compared with similar countries
- Equatorial Guinea's 48.8% is above the median for upper middle income countries, which is 4.3%, 11.4× the median. (43 countries reporting)
- Equatorial Guinea's 48.8% is above the median for Sub-Saharan Africa, which is 8.2%, 6.0× the median. (29 countries reporting)
Countries ranked near Equatorial Guinea
- 2 Ukraine 41.0% compare
- 3 Sierra Leone 31.7% compare
- 4 Mauritania 27.6% compare
More financial sector data for Equatorial Guinea
- Reserve position in the IMF, US dollar, annual growth rate 5.01 % change on previous year (2025)
- Reserve position in the IMF, US dollar, per unit of GDP 0.0005 units per US$ of GDP (2025)
- Reserve position in the IMF, US dollar, per capita 3.49 units per person (2025)
- Reserve position in the IMF, SDR, annual growth rate 0 % change on previous year (2025)
- Reserve position in the IMF, SDR, per unit of GDP 0.0004 units per US$ of GDP (2025)
- Reserve position in the IMF, SDR, per capita 2.55 units per person (2025)
- Reserve tranche position, US dollar, annual growth rate 5.01 % change on previous year (2025)
- Reserve tranche position, US dollar, per unit of GDP 0.0005 units per US$ of GDP (2025)
- Reserve tranche position, US dollar, per capita 3.49 units per person (2025)
- Reserve tranche position, SDR, annual growth rate 0 % change on previous year (2025)
Frequently asked questions
- What is bank non-performing loans to gross loans in Equatorial Guinea?
- Bank non-performing loans to gross loans in Equatorial Guinea was 48.8% in 2019, according to Financial Soundness Indicators Database (fsi.imf.org), International Monetary Fund (IMF).
- What is the highest bank non-performing loans to gross loans recorded in Equatorial Guinea?
- The highest recorded value was 48.8% in 2019.
- What is the lowest bank non-performing loans to gross loans recorded in Equatorial Guinea?
- The lowest recorded value was 4.4% in 2011.
- How does Equatorial Guinea rank for bank non-performing loans to gross loans?
- Equatorial Guinea ranks 1st out of 141 countries with data for 2019.
- Is bank non-performing loans to gross loans rising or falling in Equatorial Guinea?
- Over the last ten years it is up 934.1%. The long-run trend across the full record is volatile.
- Where does this Equatorial Guinea data come from?
- The figures come from Financial Soundness Indicators Database (fsi.imf.org), International Monetary Fund (IMF), published as part of Bank non-performing loans to gross loans (%). Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 10 observations, free to reuse under CC BY 4.0 (World Bank Open Data).
About this data
Reported by IMF staff. Note that due to differences in national accounting, taxation, and supervisory regimes, these data are not strictly comparable across countries.