An institutional-grade quantitative risk modeling web application that automates Basel III/IV Internal Ratings-Based (IRB) credit portfolio metrics and macroeconomic scenario stress testing using Python and Streamlit.
🚀 Live Enterprise Application Dashboard: https://regrisk-basel4-engine-8puk8gjfsxaf5nadh6m5ex.streamlit.app/
This application delivers automated regulatory capital adequacy modeling, serving core risk-monitoring and compliance requirements across Financial Risk Advisory, Corporate Banking, and Quantitative Capital Management practices.
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Basel IV IRB Capital Engine: Formulates regulatory Asset Correlation (
$R$ ), Maturity Adjustments ($b$ ), and Capital Requirements ($K$ ) utilizing corporate exposure metrics mapped against a strict 99.9% credit confidence interval. - SME Corporate Asset Adjustments: Automatically integrates regulatory size-discount correlation factors based on annual turnover matrices to model Mittelstand (DE) / KMU (CH) credit risk bands accurately.
- Systemic Macroeconomic Stress Tester: Simulates distressed asset parameter shifts (PD/LGD scaling multipliers) to model portfolio capital resilience against real estate shocks and credit crunches.
- Interactive Credit Data Grid: Features an integrated data editor with multi-column filtering to track and isolate high-risk corporate credit concentrations.
- Data Engineering & Pipelines:
Python,Pandas,NumPy - Statistical Distributions:
SciPy (stats.norm) - Interactive Visualizations:
Plotly (graph_objects) - Enterprise Dashboard UI:
Streamlit (Custom CSS & Corporate Theme Config)
To run the quantitative analytics environment locally on your machine, clone this repository and execute the setup pipeline:
# Install core regulatory risk dependencies
pip install -r requirements.txt
# Launch the enterprise analytical web interface
python -m streamlit run app.py