OliyadTeshome/SmartRisk-Insurance-Analytics

A predictive analytics and risk modeling toolkit for auto insurance in South Africa. # SmartRisk-Insurance-Analytics **A predictive analytics and risk modeling toolkit for auto insurance in South Africa** ## Business Context AlphaCare Insurance Solutions (ACIS) aims to optimize auto insurance premiums and attract low-risk customers using data-driven insights. This project provides a modular toolkit for risk profiling, A/B hypothesis testing, and predictive modeling tailored to the South African market. ## Problem Statement How can ACIS leverage data science to accurately profile risk, test business hypotheses, and predict optimal premiums to maximize profitability while minimizing risk exposure? ## Project Structure ``` SmartRisk-Insurance-Analytics/ │ ├── data/ # Raw and processed datasets ├── dvc_storage/ # DVC-tracked data files (README) ├── notebooks/ # Jupyter notebooks for EDA, modeling, and reporting (README) ├── src/ # Python modules (data processing, modeling, etc.) (README) ├── scripts/ # CLI scripts for each stage (README) ├── tests/ # Unit tests for key modules (README) ├── reports/ # Results, visuals, deliverables ├── configs/ # YAML/JSON config files ├── docs/ # Documentation ├── workflow/ # Automation scripts (Makefile, bash, etc.) └── README.md # Project overview ``` ## Installation 1. Clone the repository: ```bash git clone github.com cd SmartRisk-Insurance-Analytics ``` 2. Set up a virtual environment and install dependencies: ```bash python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate pip install -r requirements.txt ``` ## How to Run - **Scripts:** - EDA: `python scripts/run_eda.py --config configs/eda_config.yaml` - A/B Testing: `python scripts/run_ab_tests.py --config configs/ab_test_config.yaml` - Regression: `python scripts/train_regression.py --config configs/regression_config.yaml` - Premium Model: `python scripts/train_premium_model.py --config configs/pr …