Access to finance is a major concern in many developing countries. This topic includes several indicators assessing credit sources, loan requirements, and access to financial services. The fifteen indicators on this page measure the availability of financing in 139 countries. The results are based on surveys of more than 135,000 firms. A database query tool helps you gauge the availability of credit across various firm subgroups. You can also generate graphs to compare countries.

To see the details for a specific economy, click on the links below. Click on column headers to sort data.



Custom Data Set

Generate a Custom Data Set for Finance including standard errors, indicator values by firm subgroups, historical data and selected countries.


Percent of firms with a checking or savings accountPercent of firms with a checking or savings account.
Percent of firms with a bank loan/line of creditPercent of firms with a bank loan/line of credit.
Proportion of loans requiring collateral (%)Proportion of loans requiring collateral in order to get the financing.
Value of collateral needed for a loan (% of the loan amount)Value of collateral needed for a loan or line of credit as a percentage of the loan value or the value of the line of credit.
Percent of firms not needing a loanPercent of firms that did not apply for a loan in the last fiscal year because they did not need a loan.
Percent of firms whose recent loan application was rejectedPercent of firms whose recent loan application was rejected.
All Countries 287.533.678.9204.246.511.0
East Asia & Pacific81.034.082.2229.549.16.7
Europe & Central Asia91.637.978.1191.655.011.3
Latin America & Caribbean92.947.770.7199.045.43.3
Middle East & North Africa80.429.478.7188.251.310.6
South Asia77.627.081.1236.044.714.4
Sub-Saharan Africa86.621.784.1206.038.715.2
Afghanistan (2014)
Albania (2013)76.829.487.4266.971.03.8
Angola (2010)86.49.594.6n.a.47.0n.a.
Antigua and Barbuda (2010)
Argentina (2017)98.942.447.8219.440.54.3
Armenia (2013)91.346.288.7263.645.32.7
Azerbaijan (2013)69.915.985.5247.751.418.0
Bahamas, The (2010)97.634.281.3231.649.2n.a.
Bangladesh (2013)86.434.184.4271.141.915.6
Barbados (2010)97.458.250.9138.164.6n.a.
Belarus (2018)98.739.372.4150.945.712.2
Belize (2010)100.043.997.5182.444.3n.a.
Benin (2016)92.524.079.2231.331.123.9
Bhutan (2015)93.346.594.5178.957.88.3
Bolivia (2017)82.247.395.8206.744.44.7
Bosnia and Herzegovina (2013)98.066.382.4190.148.53.8
Botswana (2010)
Brazil (2009)
Bulgaria (2013)99.342.084.7165.648.44.6
Burkina Faso (2009)96.828.491.7175.515.1n.a.
Burundi (2014)
Cabo Verde (2009)96.541.590.1176.430.5n.a.
Cambodia (2016)39.419.977.5165.158.33.0
Cameroon (2016)
Central African Republic (2011)98.526.083.9233.425.323.8
Chad (2018)
Chile (2010)97.979.651.1209.530.8n.a.
China (2012)96.025.377.6197.045.56.6
Colombia (2017)98.962.450.5165.430.65.6
Congo, Dem. Rep. (2013)56.69.471.9152.132.712.2
Congo, Rep. (2009)86.712.867.747.332.3n.a.
Costa Rica (2010)97.556.893.3251.444.2n.a.
Côte d'Ivoire (2016)88.321.385.7156.833.417.5
Croatia (2013)99.253.786.2192.749.329.2
Czech Republic (2013)97.855.175.9158.063.47.9
Djibouti (2013)91.630.584.1227.974.60
Dominica (2010)100.032.888.2194.140.2n.a.
Dominican Republic (2016)80.750.847.1173.862.21.5
Ecuador (2017)96.759.658.1204.135.95.4
Egypt, Arab Rep. (2016)68.96.698.5158.270.520.9
El Salvador (2016)83.640.275.7205.154.01.7
Eritrea (2009)98.210.966.2n.a.84.6n.a.
Estonia (2013)
Eswatini (2016)91.526.764.3285.541.60
Ethiopia (2015)92.632.885.8296.232.815.1
Fiji (2009)96.137.870.3214.769.1n.a.
Gabon (2009)
Gambia, The (2018)94.110.692.5224.415.66.8
Georgia (2013)94.235.895.6223.359.84.6
Ghana (2013)95.023.379.5240.022.59.4
Greece (2018)99.235.574.9171.564.815.3
Grenada (2010)98.749.066.6220.147.5n.a.
Guatemala (2017)82.342.466.6190.154.42.7
Guinea (2016)98.13.9100.0n.a.54.814.8
Guinea-Bissau (2006)59.02.7n.a.n.a.6.0n.a.
Guyana, CR (2010)100.050.584.5202.250.3n.a.
Honduras (2016)81.444.672.8223.234.05.9
Hungary (2013)87.237.377.3180.451.78.3
India (2014)86.521.384.7255.150.112.9
Indonesia (2015)59.827.480.4241.142.80.1
Iraq (2011)43.23.849.5158.8028.5
Israel (2013)
Jamaica (2010)99.827.297.1204.339.3n.a.
Jordan (2013)83.316.789.6127.048.95.6
Kazakhstan (2013)
Kenya (2018)89.333.981.4252.743.13.7
Kosovo (2013)98.266.892.1299.347.84.0
Kyrgyz Republic (2013)94.729.289.5187.740.03.9
Lao PDR (2018)54.627.493.2225.149.89.6
Latvia (2013)89.720.160.6228.978.635.7
Lebanon (2013)92.857.368.7207.745.07.7
Lesotho (2016)82.518.797.8105.849.92.2
Liberia (2017)72.618.982.9171.834.28.7
Lithuania (2013)96.332.874.2192.853.829.2
Madagascar (2013)78.614.582.1n.a.43.24.1
Malawi (2014)81.926.792.6293.632.228.0
Malaysia (2015)74.731.964.7182.649.30
Mali (2016)91.326.386.2233.221.210.5
Mauritania (2014)88.232.875.7110.830.114.1
Mauritius (2009)97.247.481.159.964.8n.a.
Mexico (2010)61.832.067.0208.953.7n.a.
Micronesia, Fed. Sts. (2009)98.543.071.7265.238.8n.a.
Moldova (2013)94.326.095.0215.363.423.2
Mongolia (2013)91.944.698.0235.627.39.5
Montenegro (2013)96.054.989.9243.447.211.6
Morocco (2013)97.051.984.0165.762.36.1
Mozambique (2018)83.510.090.0271.745.821.2
Myanmar (2016)43.711.398.4412.961.23.4
Namibia (2014)97.021.782.691.947.83.5
Nepal (2013)
Nicaragua (2016)83.447.890.6192.647.81.0
Niger (2017)95.427.687.7159.538.27.3
Nigeria (2014)70.411.488.8227.749.418.1
North Macedonia (2013)95.745.490.7275.559.91.0
Pakistan (2013)58.16.764.0153.457.013.5
Panama (2010)69.120.767.9240.259.1n.a.
Papua New Guinea (2015)95.345.775.1223.544.90
Paraguay (2017)91.860.527.8190.159.30
Peru (2017)96.277.847.9167.621.82.4
Philippines (2015)93.229.951.0156.768.914.8
Poland (2013)92.731.659.5154.064.310.1
Romania (2013)49.447.480.7186.838.99.0
Russian Federation (2012)100.021.684.2154.043.126.4
Rwanda (2011)71.245.592.4272.630.310.2
Samoa (2009)97.051.382.0206.237.1n.a.
Senegal (2014)77.622.678.9271.728.82.6
Serbia (2013)
Sierra Leone (2017)
Slovak Republic (2013)97.242.676.2154.561.03.5
Slovenia (2013)99.165.664.1153.658.15.8
Solomon Islands (2015)95.144.493.9247.266.10
South Africa (2007)97.930.171.2103.650.0n.a.
South Sudan (2014)84.16.980.4183.835.9n.a.
Sri Lanka (2011)89.440.479.2193.625.18.5
St. Kitts and Nevis (2010)100.049.388.4183.241.1n.a.
St. Lucia (2010)100.024.597.7194.553.2n.a.
St. Vincent and the Grenadines (2010)98.656.566.3211.144.3n.a.
Sudan (2014)98.44.6100.0183.559.333.8
Suriname (2018)93.536.688.4241.543.13.3
Sweden (2014)n.a.35.551.583.971.23.4
Tajikistan (2013)75.614.691.8164.856.17.6
Tanzania (2013)73.716.696.2240.225.82.8
Thailand (2016)87.715.593.4320.140.533.8
Timor-Leste (2015)83.714.974.8235.149.20
Togo (2016)93.942.390.9226.131.49.7
Tonga (2009)100.054.395.4195.425.2n.a.
Trinidad and Tobago (2010)99.953.787.9139.533.6n.a.
Tunisia (2013)96.153.687.0251.536.36.6
Turkey (2013)78.740.228.9199.255.75.4
Uganda (2013)86.79.786.7161.842.09.2
Ukraine (2013)88.718.556.4160.537.711.2
Uruguay (2017)96.954.140.4241.948.14.2
Uzbekistan (2013)97.326.496.5175.774.77.7
Vanuatu (2009)96.045.891.2191.359.6n.a.
Venezuela, R.B. (2010)96.635.481.8265.946.5n.a.
Vietnam (2015)55.840.891.0216.050.05.6
West Bank and Gaza (2019)83.614.080.8182.867.514.2
Yemen, Rep. (2013)48.44.787.7281.547.716.3
Zambia (2013)86.18.890.6236.644.734.1
Zimbabwe (2016)92.47.882.0223.426.061.5
  • Notes

    * This indicator is computed using data from manufacturing firms only.

    Additional Notes

    1. Most surveys were administered using the Enterprise Surveys Global Methodology as outlined in the Methodology page, while some others did not strictly adhere to the Enterprise Surveys Global Methodology. For example, for surveys which do not follow the Global Methodology, the Universe under consideration may have consisted of only manufacturing firms or the questionnaire used may have been different from the standard global questionnaire. Data users should exercise caution when comparing raw data and point estimates between surveys that did and did not adhere to the Enterprise Surveys Global Methodology. For surveys which did not adhere to the Global Methodology plus Afghanistan 2008, any inference from one of these surveys is representative only for the data sample itself.
    2. Regional and "all countries" averages of indicators are computed by taking a simple average of country-level point estimates. For each economy, only the latest available year of survey data is used in this computation. Only surveys, posted during the years 2009-2019, and adhering to the Enterprise Surveys Global Methodology are used to compute these regional and "all countries" averages.
    3. Descriptions of firm subgroup levels, e.g. how the ex post groupings are constructed, are provided in the Indicator Descriptions (PDF, 710KB) document.
    4. Statistics derived from less than or equal to five firms are displayed with an "n.a." to maintain confidentiality and should be distinguished from ".." which indicates missing values. Also note for three growth-related indicators under the "Performance" topic, these indicators are not computed when they are derived from less than 30 firms.
    5. Standard errors are labeled "n.c.", meaning not computed, for the following:

           1) indicators for all surveys that were not conducted using the Enterprise Surveys Global Methodology and

           2) for indicator breakdowns by ex post groupings: exporter or ownership type, and gender of the top manager.
    6. Please cite our data as follows:

      Enterprise Surveys (, The World Bank.