peter-ngamau/Financial-Inclusion-In-Kenya

10-year analysis of M-Pesa adoption and financial exclusion across Kenya's 47 counties using CBK open data and FinAccess Survey — Python, SQL Server, and Power BI. # Kenya Financial Inclusion & Mobile Money Analytics > An end-to-end data analytics project exploring M-Pesa adoption, financial inclusion trends, and unbanked population segments across Kenya's 47 counties — built using **Python · SQL Server · Power BI**. --- ## Project Overview Kenya is one of the world's most remarkable mobile money success stories. Since M-Pesa launched in 2007, the country has gone from 67.5% of its population being financially excluded to just 9.9% today. Yet millions of Kenyans — particularly in rural counties, older age groups, and lower income segments — still lack access to formal financial services. This project analyses **10 years of CBK (Central Bank of Kenya) mobile money data** and **7 waves of the FinAccess Household Survey (2006–2024)** to answer four core questions: 1. How has M-Pesa transaction value and adoption grown from 2015 to 2024? 2. Which counties are the most and least financially included — and why? 3. Which demographic groups (by age, gender, income, education) are most at risk of exclusion? 4. Is there a measurable relationship between agent network density and financial inclusion? --- ## Key Findings - **M-Pesa transaction value grew 7× in 10 years** — from KES 1,238 Billion in 2015 to KES 8,700 Billion in 2024 - **Mobile money now represents 57.6% of Kenya's GDP** — among the highest ratios in the world - **Tana River County has the highest exclusion rate at 37.6%** — compared to Nyandarua at just 2.6% - **People with no formal education are 4.6× more likely to be excluded** than the national average - **Agent density and inclusion are positively correlated (r = 0.55)** — counties with more agents per 1,000 people consistently show higher inclusion rates - **The 2020 COVID-19 pandemic accelerated digital adoption by 41% in a single year** — the largest single-year jump in the dataset --- ## 🗂️ Project Structure ``` Financial_Inclusion_Kenya/ │ ├── Data/ │ ├── Raw/ # Original . …