End-to-end Canadian Credit Risk & PD modeling project using public Canadian lending data, ML models, SHAP explainability, Streamlit UI, and Power BI dashboard.
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Updated
Jan 2, 2026 - Jupyter Notebook
End-to-end Canadian Credit Risk & PD modeling project using public Canadian lending data, ML models, SHAP explainability, Streamlit UI, and Power BI dashboard.
Enterprise-grade RAG system for OSFI regulatory documents, combining governed LLM Q&A, audit logging, and compliance-aware AI for Canadian financial institutions.
AML & Transaction Monitoring analytics for Canadian BFSI — SQL detection rules (structuring, layering, rapid movement), threshold tuning, Isolation Forest anomaly detection, and FINTRAC compliance reporting (STR/LCTR/EFTR). Built with PostgreSQL, Python, and Jupyter. Aligned to PCMLTFA · OSFI B-8 · FATF 40.
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