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Access to Credit Indicator


This indicator measures the level of financial inclusion in a country as measured by the number of bank branches and ATMs per 100,000 adults and the share of adults that have a financial or mobile money account.

Relationship to Growth & Poverty Reduction

The ability to access affordable credit is a critical element of private sector led growth, particularly for small businesses that often lack the initial capital needed to grow and expand and also for agricultural households, where expenditures on inputs precede the returns from harvest; it also increases a business or household’s ability to bear and cope with risk.1 Financial inclusion and access to both formal and informal financial instruments are crucial for rural and poor populations to be able to manage uncertain and uneven incomes and alleviate the costs of poverty while promoting inclusive growth.2 Improving credit access for small business and poor populations can have a substantial impact on agricultural development, poverty reduction, and broad-based economic growth.3


Indicator Institution Methodology

The Access to Credit composite indicator is calculated by taking the simple average of two indicators from the IMF and Findex, which have been normalized and ranked on equivalent scales:

  • Financial Institution Access (IMF): MCC uses the Financial Institution Access indicator from the IMF’s Financial Development Index. This indicator has two sub indicators: the number of bank branches per 100,000 adults from the World Bank’s FinStats, and the number of ATMs per 100,000 adults from the IMF’s Financial Access Surveys.
  • Share of adults with an account (Findex): From the World Bank’s Findex Database, MCC uses the share of the population (adults 15+) with an account. This survey counts both accounts with traditional financial institutions and mobile money.

MCC Methodology

MCC’s Access to Credit Score = [ 0.5 × Normalized IMF] + [ 0.5 × (Normalized Findex)]

This index draws on 2020 data from the Findex database (as well as 2021 data for those countries added to the dataset in the March 2023 update) and 2021 data published in 2023 by the IMF. Country scores are reported on the Scorecards as 2022 data. When one indicator is missing data, the other is used. Since each of the two sub-components of this index have different scales, MCC created a common scale for each of the indicators by normalizing them. Please see equations below. Both scales are then inverted so that a higher score corresponds to better performance.

MCC Methodology to Normalize IMF and Findex Data:

  • Normalized IMF = 1 – ((Maximum observed value – Country X’s raw score) ÷ (Maximum observed value -Minimum observed value))
  • Normalized Findex = 1 – ((Maximum observed value – Country X’s raw score) ÷ (Maximum observed value -Minimum observed value))

For example, to calculate a given country X’s score, MCC first finds the maximum and minimum value for that year. MCC then subtracts country X’s score from the maximum to get the numerator and subtracts the minimum from the maximum to get the denominator. MCC divides the numerator by the denominator to get the inverted normalized value. Next, MCC subtracts this quotient from 1, to get the normalized value for a country. Finally, MCC averages the normalized values for each source together. If either score is missing, the other is used, but if both scores are missing, the country is given an “N/A”.

In FY22 MCC revised its methodology for this indicator to expand the populations and concepts covered and to focus more on financial inclusion. As a result, the scores from FY22 are not comparable to scores from FY21 and earlier. For more information about how MCC is making these business climate indicators more inclusive, visit:

  • 1. Beck, Thorsten and Asli Demirgüç-Kunt. 2006. Small and medium-size enterprises: Access to finance as a growth constraint. Journal of Banking & Finance, 30(11): 2931-2943. Beck, Thorsten, Asli Demirgüç-Kunt, and María Soledad Martínez Pería. 2008. Bank Financing for SMEs around the World: Drivers Obstacles, Business Models, and Lending Practices. Washington, D.C.: The World Bank. Demirgüç-Kunt, Asli, Thorsten Beck, and Patrick Honohan. 2008. Chapter 2: Firms’ Access to Finance: Entry, Growth, and Productivity from Finance for All? Policies and Pitfalls in Expanding Access. Washington, D.C.: The World Bank. Diagne, Aliou, and Manfred Zeller. 2001. Access to Credit and Its Impact on Welfare in Malawi. Research Report 116. Washington, D.C.: International Food Policy Research Institute. Diagne, Aliou, Manfred Zeller, and Manohar Sharma. 2000. Empirical Measurements of Households’ Access to Credit and Credit Constraints in Developing Countries: Methodological Issues and Evidence. Food Consumption and Nutrition Division Working Paper No. 90. Washington, D.C.: International Food Policy Research Institute. Schiffer, Mirjam and Beatrice Weder. 2001. Firm Size and the Business Environment: Worldwide Survey Results. Washington, D.C.: The World Bank. Zeller, Manfred, Gertrud Schrieder, Joachim von Braun, and Franz Heidhues. 1997. Rural finance for food security for the poor: Implications for research and policy. Food Policy Review No. 4. Washington, D.C.: International Food Policy Research Institute. Afrin, S., Haider, M.Z. and Islam, M.S. (2017), “Impact of financial inclusion on technical efficiency of paddy farmers in Bangladesh”, Agricultural Finance Review, Vol. 77 No. 4, pp. 484-505.
  • 2. Collins, D., Morduch, J., Rutherford, S., & Ruthven, O. 2009. Portfolios of the poor: How the world’s poor live on $2 a day. Princeton: Princeton University Press; Kim, D. Yu, J. Hassan M. K. (2018). Financial inclusion and economic growth in OIC countries. Research in International Business and Finance. 34. 1-14; Jong-Hee Kim (2016) A Study on the Effect of Financial Inclusion on the Relationship Between Income Inequality and Economic Growth, Emerging Markets Finance and Trade, 52:2, 498-512, DOI: 10.1080/1540496X.2016.1110467; Kablana, A. S. K., & Chhikara, K. S. (2013). A Theoretical and Quantitative Analysis of Financial Inclusion and Economic Growth. Management and Labour Studies, 38(1–2), 103–133.; Van. L. T. Vo, A. T., Nguyen, N. T. & Vo, D. H. 2019. Financial Inclusion and Economic Growth An International Evidence. Emerging Markets Finance and Trade. 57(1).
  • 3. Ehiabhi Andrew Tafamel, 2019. “Analysis of the Effect of Microfinance Institutions on Poverty Reduction in Nigeria,” Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,”Dimitrie Cantemir” Christian University Bucharest, vol. 5(2), pages 114-119, June; Shah, P., & Dubhashi, M. 2015. Review Paper on Financial Inclusion-The Means of Inclusive Growth. International journal of business research, 1, 37-48; J. A. Prasansha Kumari, S. M. Ferdous Azam, & Siti Khalidah. (2019). The Effect of Microfinance Services on Poverty Reduction: Analysis of Empirical Evidence in Sri Lankan Perspectives. European Journal of Economic and Financial Research, 3(5).; Olaniyi, E. (2017). Back to the Land: The Impact of Financial Inclusion on Agriculture in Nigeria. Iranian Economic Review, 21(4), 885-903. doi: 10.22059/ier.2017.64086; Mohammed, J.I., Mensah, L., & Gyeke-Dako, A. 2017. Financial Inclusion and Poverty Reduction in Sub-Saharan Africa. African Finance Journal 19(1).