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
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 at financial institutions and mobile money.
MCC’s Access to Credit Score = [ 0.5 x Normalized IMF] + [ 0.5 x (Normalized Findex)]
This index draws on 2017 data from the Findex database and 2019 data from the IMF. Country scores are reported on the Scorecards as 2019 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 https://www.mcc.gov/blog/entry/blog-101921-financial-inclusion.