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| title: ECL Risk Analyzer | |
| emoji: 💹 | |
| colorFrom: red | |
| colorTo: red | |
| sdk: docker | |
| app_port: 8501 | |
| tags: | |
| - streamlit | |
| - credit-risk | |
| - gemini | |
| - finance | |
| pinned: false | |
| short_description: AI ECL analyzer using Streamlit and Gemini. | |
| # 🧮 ECL Risk Analyzer | |
| **ECL Risk Analyzer** is a Streamlit-based web app that automates **Expected Credit Loss (ECL)** analysis and provides **AI-driven recommendations** on credit decisions. | |
| ### 🔍 Features | |
| - Upload loan datasets (CSV format). | |
| - Compute key credit metrics: | |
| - **PD** – Probability of Default | |
| - **LGD** – Loss Given Default | |
| - **EAD** – Exposure at Default | |
| - **ECL** – Expected Credit Loss | |
| - Visualize segment-level performance with interactive charts. | |
| - Get AI recommendations (via **Gemini 2.5 Flash Lite**) to: | |
| - Increase interest | |
| - Reduce disbursement | |
| - Maintain current policy | |
| - Role-based access: | |
| - **Analyst:** Run and review segment analyses. | |
| - **CRO:** Audit all analyst reports and view trends. | |
| ### 🧠 Tech Stack | |
| - **Frontend:** Streamlit | |
| - **AI Engine:** Gemini API | |
| - **Database:** SQLite (via SQLAlchemy) | |
| - **Hosting:** Hugging Face Spaces (Docker SDK) | |
| ### 🚀 Quick Start | |
| 1. Upload your loan dataset (CSV). | |
| 2. Select a segmentation column (e.g., loan intent, area, or occupation). | |
| 3. View computed ECL metrics and charts. | |
| 4. Choose a segment to get AI-based recommendations. | |
| ### 📊 Example Output | |
| | Segment | PD | LGD | EAD | ECL | Action | | |
| |----------|----|-----|-----|-----|--------| | |
| | Medical | 0.278 | 0.255 | 78M | 5.5M | Increase Interest | | |
| ### 🛠️ Customization | |
| Modify `/src/streamlit_app.py` to: | |
| - Adjust prompts or logic. | |
| - Change chart styles. | |
| - Extend user roles or security. | |