Bank Account Access Prediction

Predicting Bank Account Access in East Africa with Machine Learning

Motivation:

Financial inclusion remains a critical challenge in East Africa, with only 14% of adults in Kenya, Rwanda, Tanzania, and Uganda having or using a bank account. Traditional methods for assessing financial inclusion have limitations, hindering effective interventions.

Project Goal:

Develop a machine learning model to predict bank account access across East Africa, providing data-driven insights to policymakers and financial institutions for targeted initiatives and product development.

Technical Approach:

• Utilize diverse machine learning algorithms on a comprehensive dataset encompassing demographic, socioeconomic, financial access, and behavioral data.
• Implement feature engineering, cross-validation, and model tuning for optimal performance and generalizability.
• Ensure model explainability and interpretability to translate insights into actionable recommendations.

Expected Outcomes:

• Improve bank account access prediction accuracy compared to existing methods.
• Identify key factors driving financial inclusion and exclusion in each East African country.
• Inform targeted financial inclusion initiatives and product development strategies.
• Contribute to increased bank account access and financial well-being in the region.

Target Audience:

• Financial institutions operating in the region.
• Researchers and academics focused on financial inclusion.

Next Steps:

• Develop and refine the machine learning model.
• Analyze and interpret model findings.
• Disseminate insights and recommendations to policymakers and financial institutions.

Join the Project: To join our impactful project on GitHub, you can choose one of two options:

1. Clone the Repository:

git clone https://github.com/UDSM-AI/Bank-account-access-prediction.git

This command will create a local copy of the entire project repository on your system. Once completed, you can navigate into the newly created directory and start contributing!

2. Fork the Repository and Contribute:

git clone https://github.com/UDSM-AI/Bank-account-access-prediction.git my-fork-bank-account-access
cd my-fork-bank-account-access
git remote add upstream https://github.com/UDSM-AI/Bank-account-access-prediction.git

This approach creates a personal "fork" of the project where you can make changes and contributions without affecting the original repository. Once you're happy with your changes, you can create a pull request to share your work with the project maintainers for review and possible integration into the main repository.

Getting Started with Contribution:

• Review the project documentation: We'll have detailed documentation available within the repository itself, outlining contribution guidelines, coding standards, and specific areas where your skills are needed.
• Choose your area of contribution: Whether you're a data scientist, developer, or documentation expert, there are various ways to contribute. We encourage you to explore the codebase and identify areas where you can add value.
• Communicate and collaborate: Join our community through the project's GitHub discussions or dedicated communication channels to connect with other contributors and discuss ideas.

Remember:

• Follow the contribution guidelines: These will ensure your contributions are easily integrated and maintain a consistent codebase.
• Test your changes: Before submitting your work, ensure your code runs smoothly and adheres to the project's testing standards.
• Be open to feedback: We encourage constructive criticism and collaboration. All contributions will be reviewed carefully, and we'll work with you to improve your work before merging it into the main repository.

Let's join forces to predict bank account access and foster financial inclusion in East Africa! We're excited to welcome you to the UDSM AI Team 🐱‍🏍🎉!