Car-Insurance-Risk-Analysis-and-Premium-Optimization

A project analyzing car insurance claim data to optimize premiums and marketing strategies. Using statistical modeling, A/B testing, and machine learning, it identifies low-risk customers and assesses risks across demographics and locations to help AlphaCare Insurance Solutions improve acquisition and profitability.

The project structure is organized to support reproducible and scalable data processing, modeling, and visualization.

Project Structure

├── .dvc/
│   └── config                        # Configuration files for data version control
├── .vscode/
│   └── settings.json                 # Configuration for VSCode environment
├── .github/
│   └── workflows/
│       ├── unittests.yml             # GitHub Actions workflow for running unit tests
├── .gitignore                        # Files and directories to be ignored by Git
├── requirements.txt                  # List of dependencies for the project
├── README.md                         # Project overview and instructions
├── scripts/
│   ├── __init__.py
│   ├── data_processing.py            # Script for data cleaning and processing
│   ├── data_visualization.py         # Scritpt for different plots
│   ├── load_data.py                  # Scritpt extracting and loading dataset
│   ├── hypothesis_testing.ipynb      # Script for hypothesis testing analysis
├── notebooks/
│   ├── __init__.py
│   ├── eda_notebook.ipynb            # Jupyter notebook for eda analysis
│   ├── hypothesis_testing.ipynb      # Jupyter notebook for hypothesis testing analysis
│   ├── data_preprocessing.ipynb      # Jupyter notebook for data preprocessing
│   ├── model_training.ipynb          # Jupyter notebook for statistical model training
│   ├── README.md                     # Description of notebooks
├── tests/
│   ├── __init__.py
│   ├── test_data_processing.py          # Unit tests for data processing module
│   ├── test_hypothesis_testing.py       # Unit tests for hypothesis testing module
│   
└── src/
    ├── __init__.py
    └── README.md                     # Description of scripts

Installation

git clone https://github.com/epythonlab/Car-Insurance-Risk-Analysis-and-Premium-Optimization.git cd Car-Insurance-Risk-Analysis-and-Premium-Optimization

Create virtual environment

python3 -m venv venv # on MacOs or Linux source venv/bin/activate # On Windows: venv\Scripts\activate

Install Dependencies

pip install -r requirements.txt

To run tests

navigate

cd tests/ pytest # all tests will be tested