dodoucode/financial-inclusion-gambia

# The Gambia Financial Inclusion Gap ## Problem Statement Despite growing mobile money adoption in the Gambia, a large share of adults still have no formal financial account at all, no bank account, no mobile money, nothing. This project uses Excel, SQL, and Power BI to clean and analyze individual level survey data from the World Bank's Global Findex 2025 database for the Gambia, identifying which factors, gender, income, education, location, and phone ownership, most strongly predict financial exclusion. The goal is to help a bank, mobile money provider, NGO, or policy team prioritize outreach toward the groups most likely to be left out of the formal financial system. ## Data Source Individual level microdata from the World Bank's Global Findex 2025 database, Gambia country file (1,008 respondents), downloaded from the World Bank Microdata Library. This is real survey data collected specifically in the Gambia, not adapted or localized from another country. Six fields on stated reasons for financial exclusion (too far, too expensive, lack of documentation, and similar) were included in the codebook but came back completely empty for every respondent in this release, so they were dropped from the analysis. The codebook is included in this repo so anyone can verify this. ## Approach - Cleaned the raw survey export in Excel, using Power Query to trim 199 columns down to the 14 that mattered for this analysis, and built readable labels (Yes/No, Female/Male, Rural/Urban) from the raw numeric survey codes using the official Findex codebook - Loaded the cleaned data into MySQL and ran a series of queries measuring exclusion rates by gender, income quintile, education, location, and mobile phone ownership, plus a breakdown of who relies on a bank account, mobile money, or both - Connected Power BI directly to the MySQL database and built an interactive dashboard, rebuilding the exclusion rate logic as DAX measures rather than importing static numbers ## Dashboard …