Advisor, Model Risk Management

This role exists to ensure the Bank’s critical models work as intended, stand up to regulatory scrutiny, and do not create hidden risk.
Success is measured by clear validation conclusions, closed model risk issues, regulator‑ready documentation, and models that are usable, explainable, and controlled in production.

• Independent validation conclusions for key models across IRB, IFRS 9, Stress Testing, and AI/ML/GenAI, with clear pass/fail criteria, limitations, and required remediation.
• A practical Model Risk Management framework that is actually applied: clear lifecycle controls, model inventory, risk tiering, approvals, and change governance.
• Early identification and escalation of material model risks, before they become regulatory or financial issues.
• Actionable recommendations that improve model robustness, explainability, and compliance — not academic critique.
• Regulator‑ready evidence: validation reports, issue logs, and documentation that can be defended in audits and inspections.
• Strong alignment between Modeling, Data, Risk, Finance, Business, and Technology, so governance does not block delivery.

• Independently review and challenge

IRB models (PD, LGD, EAD) used for Basel capital

IFRS 9 ECL models, including macro assumptions and overlays
Stress Testing & macro models
AI/ML/GenAI models used in material business decisions

• Assess model risk related to data quality, assumptions, methodology, stability, performance, and explainability.
• Own model risk issues end‑to‑end: definition, severity, remediation tracking, and closure.
• Advise stakeholders on what must change to make models compliant, defensible, and sustainable.

• Minimum 10 years in risk modeling, model risk management, or independent model validation.
• Hands‑on experience delivering or validating IRB, IFRS 9, and/or AI/GenAI models in a banking environment is a significant advantage.