Baraka-Malila/Financial-Inclusion-In-Africa

Financial inclusion in East Africa mainly Kenya, Uganda, Tanzania and Rwanda. Financial Inclusion in Africa Project Overview The Financial Inclusion in Africa project seeks to predict the likelihood of an individual possessing a bank account based on various demographic and financial service data. This analysis focuses on enhancing understanding of financial accessibility in four East African countries: Kenya, Rwanda, Tanzania, and Uganda. Objectives Predictive Analysis: Utilize machine learning techniques to estimate the probability of bank account ownership. Data-Driven Insights: Explore demographic factors and financial service usage that influence financial inclusion. Model Evaluation: Assess the model's performance by training on 70% of the dataset and testing on the remaining 30%. Data Description The primary dataset comprises demographic information and financial service usage statistics from approximately 33,600 individuals across East Africa. This data has been sourced from multiple Finscope surveys conducted between 2016 and 2018, which are known for their comprehensive insights into the financial behaviors and attitudes of individuals in the region. Key Features Demographic Information: Age, gender, education level, and employment status. Financial Service Usage: Access and usage of banking services, mobile money, and other financial products. Dataset Access You can find more information about the surveys and download the dataset using the following link: Zindi Financial Inclusion in Africa Data Project Files Financial_Inclusion_In_Africa.ipynb: Jupyter notebook containing the analysis and model training code. Starter_Notebook.ipynb: Initial notebook with setup and preliminary analysis. Train.csv: Dataset used for model training. Test.csv: Dataset used for model testing. Sample_submission.csv: Example submission file to demonstrate the expected output format. Variable_Definitions.csv: Comprehensive definitions for all variables utilized in the datasets. How to Use This Repository Clone the repository to your local machine. Ope …