To establish and maintain a robust modelernance frameworks, policies, and procedures consistent with regulatory requirements and industry best practices. This includes documentation standards, model inventory management, and approval workflows.
To lead the model development and validation of all models used across various business functions, including credit risk, market risk, liquidity risk, fraud detection, pricing, and customer segmentation.
Conduct thorough assessments of model conceptual soundness, data quality, implementation accuracy, and performance via statistical testing.
Provide guidance on model selection, development methodologies, and validation techniques.
Develop and implement risk mitigation strategies, such as model recalibration, scenario analysis, stress testing, and model limitations disclosure.
Requirements :
Bachelor’s / Advanced (Master or higher) Degree in Statistics, Applied Mathematics, Operations Research, Economics, Engineering or other quantitative discipline.
Good understanding of retail banking / small business / consumer finance products and business lifecycle ( sales, underwriting, portfolio management, marketing, collection etc.).
9 years’ in-depth experience in hands-on Statistical Modelling and / or model validation preferably in the retail banking space.
Proficient in statisticalputing tools and packages like SAS / R / SQL etc.
Strong analytical skills and understanding of quantitative and statistical techniques.
Experience in directly interacting with Business and exposure to international markets will be a plus.
Good understanding of market risk measures, concepts and regulatory rules.
Good knowledge of MAS regulatory guideline and regulatory reporting requirement ( MAS759, MAS760, MAS610 etc).