Practitioner-grade IFRS 9 expected-credit-loss engine: PD term structures, three-stage SICR waterfall, EBA macro overlays and a Vasicek/ASRF point-in-time PD. Parallel Python + Excel with a methodology deck.
End-to-end credit risk analytics in Python: calibrated PD, LGD, IFRS 9/CECL ECL engine, macro stress testing, and early-warning delinquency monitoring — synthetic-data demonstration portfolio.
IFRS 9 Expected Credit Loss model on a 10,000-loan UK SME portfolio - PD/LGD/EAD, SICR staging, 3-scenario macro overlay. R, Python, Excel. AUC 0.77.
Calibrated XGBoost Probability-of-Default model for a loan portfolio — ADASYN imbalance handling, Monte Carlo PD/ECL, SHAP explainability, and a full validation & monitoring suite (AUC, Gini, KS, PSI).
IFRS 9 expected credit loss engine on 1.35M real loans: PD, LGD, EAD, three-stage staging, and probability-weighted macroeconomic scenarios
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