REQUIREMENTS

• Proven experience in IFRS 9, ECL modeling, credit risk modeling, and regulatory reporting.
• Strong expertise in PD/LGD/EAD modeling, macroeconomic overlays, and stress testing.
• Hands-on experience with SAS (SAS Risk Management / SAS IFRS 9 modules) and Excel-based calculators.
• Experience in system integration via APIs for risk and finance data flows.
• Knowledge of statistical modeling, machine learning, and quantitative risk techniques.
• Strong programming skills in Python, R, or SQL (preferred).
• Excellent analytical, problem-solving, and communication skills.

KEY RESPONSIBILITIES

• Develop and implement ECL framework covering both collateralized and non-collateralized exposures.
• Define and document the approach for computing ECL, including Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), and discounting methodologies.
• Research, compare, and evaluate at least 3 different ECL modeling approaches (e.g., Vintage Analysis, Roll Rate Models, Transition Matrix, Monte Carlo Simulation) to recommend the most suitable model.
• Design and deliver a recommended ECL model aligned with regulatory and IFRS 9 standards.
• Build an ECL Calculator/Template (Excel-based prototype) with capability for automation and scalability.
• Integrate ECL solution with SAS, IFRS 9 solutioning tools, and APIs for seamless system connectivity and reporting.
• Work closely with Risk, Finance, and IT stakeholders to ensure model validation, governance, and compliance.
• Provide support in regulatory reporting, model documentation, and audit requirements.