Household Sector Loan Accounts with Commercial Banks per 1,000 Adults in Myanmar
Myanmar: Household Sector Loan Accounts with Commercial Banks per 1,000 Adults was 11.5 in 2020. ◆ Volatile
Household Sector Loan Accounts with Commercial Banks per 1,000 Adults in Myanmar, 2004–2020
Source: International Monetary Fund.
Analysis
Myanmar recorded 11.5 for household sector loan accounts with commercial banks per 1,000 adults in 2020. That is the highest value across all 17 years on record.
Compared with earlier readings it is up 10.5% on the previous year and up 4,359.1% over ten years.
Over the whole period, household sector loan accounts with commercial banks per 1,000 adults in Myanmar peaked at 11.5 in 2020 and was at its lowest, 0.1845, in 2004.
That places Myanmar 95th out of 98 countries with data for 2020, putting it in the bottom quarter.
The series is highly variable year to year, so single readings are best treated with caution.
Household Sector Loan Accounts with Commercial Banks per 1,000 Adults in Myanmar, year by year
| Year | Value | Change |
|---|---|---|
| 2004 | 0.1845 | — |
| 2005 | 0.2481 | +34.4% |
| 2006 | 0.2176 | -12.3% |
| 2007 | 0.2065 | -5.1% |
| 2008 | 0.2203 | +6.7% |
| 2009 | 0.2367 | +7.4% |
| 2010 | 0.2579 | +9.0% |
| 2011 | 0.2729 | +5.8% |
| 2012 | 0.3115 | +14.2% |
| 2013 | 0.6292 | +102.0% |
| 2014 | 1.18 | +87.2% |
| 2015 | 2.72 | +130.9% |
| 2016 | 3.54 | +30.0% |
| 2017 | 3.78 | +6.7% |
| 2018 | 4.85 | +28.6% |
| 2019 | 10.4 | +114.3% |
| 2020 | 11.5 | +10.5% |
Myanmar compared with similar countries
- Myanmar's 11.5 is below the median for lower middle income countries, which is 57.8, 20% of the median. (22 countries reporting)
- Myanmar's 11.5 is below the median for East Asia & Pacific, which is 175.08, 7% of the median. (14 countries reporting)
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2000s | 0.2189 | 0.1845 | 0.2481 | 6 |
| 2010s | 2.79 | 0.2579 | 10.4 | 10 |
| 2020s | 11.5 | 11.5 | 11.5 | 1 |
Countries ranked near Myanmar
More financial sector data for Myanmar
- Net domestic credit (current LCU), per capita 1.15 million current LCU per person (2020)
- Net domestic credit (current LCU), per unit of GDP 771.31 current LCU per US$ of GDP (2020)
- Net domestic credit (current LCU), annual growth rate 15.1 % change on previous year (2020)
- Total reserves in months of imports, per capita 0 units per person (2019)
- Total reserves in months of imports, per unit of GDP 0 units per US$ of GDP (2019)
- Total reserves in months of imports, annual growth rate 5.72 % change on previous year (2019)
- Reserve tranche position, SDR, per capita 0 units per person (2025)
- Reserve tranche position, SDR, per unit of GDP 0 units per US$ of GDP (2025)
- Reserve tranche position, SDR, annual growth rate -100 % change on previous year (1985)
- Reserve tranche position, US dollar, per capita 0 units per person (2025)
Frequently asked questions
- What is household sector loan accounts with commercial banks per 1,000 adults in Myanmar?
- Household sector loan accounts with commercial banks per 1,000 adults in Myanmar was 11.5 in 2020, according to International Monetary Fund.
- What is the highest household sector loan accounts with commercial banks per 1,000 adults recorded in Myanmar?
- The highest recorded value was 11.5 in 2020.
- What is the lowest household sector loan accounts with commercial banks per 1,000 adults recorded in Myanmar?
- The lowest recorded value was 0.1845 in 2004.
- How does Myanmar rank for household sector loan accounts with commercial banks per 1,000 adults?
- Myanmar ranks 95th out of 98 countries with data for 2020.
- Is household sector loan accounts with commercial banks per 1,000 adults rising or falling in Myanmar?
- Over the last ten years it is up 4,359.1%. The long-run trend across the full record is volatile.
- Where does this Myanmar data come from?
- The figures come from International Monetary Fund, published as part of Household Sector Loan Accounts with Commercial Banks per 1,000 Adults. Statizoid updates them automatically from the source API.
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About this data
Gender-disaggregated data on access to and use of financial services.