Credit Risk Modelling and Portfolio Optimization

• Build statistically robust application and behavior scorecards; develop PD, LGD, and EAD models
• Design loss‑forecasting frameworks (vintage, roll‑rate/Markov, survival/hazard, GLM/GBM) at segment and portfolio levels.
• Engineer features from bureau, internal behavioral, transaction, device, and alternative data with rigorous data QC.
• Calibrate and back test models; perform stability monitoring (PSI/CSI), discrimination (KS/AUC), and calibration tests.
• Implement explain ability (reason codes/SHAP), bias/fair‑lending checks, and challenger/benchmark models.
• Align models to accounting and capital frameworks (IFRS 9 or CECL; Basel PD/LGD/EAD concepts).
• Development of credit card portfolio optimization data models to drive spends and engagement
• Portfolio Spends Growth – Targeting basis segments/persona, merchants, campaign recommendation to drive cross border

SKILLS & EXPERIENCE <...