favouregberike/modeling-financial-exclusion-africa

Using World Bank Global Findex data to identify demographic and structural patterns associated with financial exclusion across African populations. # Modeling Financial Exclusion Drivers in Africa **Live Demo →** ## Project Overview Financial inclusion is a critical driver of economic participation, poverty reduction, and sustainable development across Africa. Despite the rapid growth of digital finance and mobile money services, millions of people remain excluded from formal financial systems. This project applies data science and machine learning techniques to analyze financial exclusion patterns across African populations using the World Bank Global Findex dataset. The objective is to identify the demographic and structural factors most associated with financial exclusion and model exclusion intensity across countries and population groups. Using exploratory data analysis, feature engineering, predictive modeling, and model explainability techniques, this project generates data-driven insights that can support governments, fintech companies, development organizations, and financial institutions in improving access to financial services. --- # Business Problem Financial exclusion limits access to: - savings, - credit, - insurance, - digital payments, - and economic opportunities. Understanding which populations are most financially excluded and why is essential for designing effective financial inclusion strategies. This project uses machine learning to uncover the strongest predictors of financial exclusion and evaluate how factors such as gender, age, urbanization, and digital finance adoption influence access to financial services across Africa. --- # Objectives The objectives of this project are to: - Analyze demographic patterns of financial exclusion - Identify key barriers to banking access - Examine digital financial adoption trends - Engineer features from socioeconomic indicators - Build predictive machine learning models - Evaluate feature importance and model explainability - Generate actionable business and policy insights --- # Dataset The dataset used in this project is the Wor …