A Python-powered automated risk assessment engine and Streamlit web application designed to evaluate loan applicants and streamline credit decision-making. The engine processes financial metrics to determine creditworthiness, assess risk levels, and output structured underwriting recommendations.
The application is hosted and available to test online at: 👉 credit-underwriting-engine Streamlit App
The repository contains the following core files:
underwriting_core.py: The underlying rule engine and logic that evaluates applicant creditworthiness.app.py: The frontend UI wrapper built using Streamlit.test_underwriting.py: Unit tests to validate scoring logic and financial math boundaries.requirements.txt: Python package dependencies required to run the engine.
Follow these steps to clone, configure, and execute the credit underwriting engine on your local machine.
git clone https://github.com
cd credit-underwriting-engineIt is highly recommended to isolate dependencies using a virtual environment:
# Create the environment
python -m venv venv
# Activate the environment (Mac/Linux)
source venv/bin/activate
# Activate the environment (Windows)
venv\Scripts\activateInstall all required packages listed in the requirements.txt file:
pip install -r requirements.txtLaunch the frontend dashboard interface locally:
streamlit run app.pyOnce running, navigate to http://localhost:8501 in your browser.
To verify the math, rule thresholds, and edge cases inside underwriting_core.py, execute the test suite using pytest:
# Install pytest if not already in requirements
pip install pytest
# Run the test file
pytest test_underwriting.py -vSRINIVASTA / Credit Underwriting Engine
Building the future of autonomous risk management.
- Lead Architect & Developer: Srinivasta
This project is licensed under the terms of the MIT License. See the LICENSE file for complete details.