lewis-munyi / financial-inclusion

The objective of this project is to create a machine learning model to predict which individuals are most likely to have and use a bank account. Use the link provided below to access the application.

Financial Inclusion

Financial Inclusion remains one of the main obstacles to economic and human development in Africa. For example, across Kenya, Rwanda, Tanzania, and Uganda only 9.1 million adults (or 13.9% of the adult population) have access to or use a commercial bank account.
Traditionally, access to bank accounts has been regarded as an indicator of financial inclusion. Despite the proliferation of mobile money in Africa, and the growth of innovative fintech solutions, banks still play a pivotal role in facilitating access to financial services. Access to bank accounts enable households to save and facilitate payments while also helping businesses build up their credit-worthiness and improve their access to other finance services. Therefore, access to bank accounts is an essential contributor to long-term economic growth.

View Demo · Report Bug · Request Feature

Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Contributing
5. License
6. Contact
7. Acknowledgements

About The Project

The objective of this project is to create a machine learning model to predict which individuals are most likely to have or use a bank account. The models and solutions developed can provide an indication of the state of financial inclusion in Kenya, Rwanda, Tanzania and Uganda, while providing insights into some of the key demographic factors that might drive individuals’ financial outcomes.

Built With

• Python 3

Getting Started

To get a local copy up and running follow these simple steps.

Prerequisites

This project requires that you have at least some little programming background. It also requires having the following installed on your OS.

• Python 3
• Pip
• A text editor such as VS Code or Sublime Text

Installation

1. Clone the repo

   git clone https://github.com/grivine-19/Financial-Inclusion.git

2. Change into the project directory

   cd ./Financial-Inclusion

3. Create and activate a python virtual enviroment if you have venv installed. This step is recommended but is not compulsory.

   venv name

4. Install Python packages

   pip install -r requirements.txt

Usage

Run the app using

streamlit run ./app.py

For more examples, please refer to streamlit's Documentation

Contributing

We are currently accepting contributions. To make your contribution:

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Grivine Ocheing' - @Grivine_O

Project Link: https://github.com/grivine-19/Financial-Inclusion

Acknowledgements

• Jacklyne Betty - Industry consultunt
• Lewis Munyi - ML Engineer