About the role
AI summarisedThis role involves developing and maintaining retail credit risk models for a bank, including PD, LGD, and EAD models for regulatory capital and IFRS 9. The analyst will work on model monitoring, validation, and improvement, ensuring compliance with MAS and Basel guidelines.
BusinessFull-timeGeneral
Key Responsibilities
- Develop, validate, and maintain retail credit risk models (PD, LGD, EAD) for regulatory capital and IFRS 9 purposes.
- Conduct model monitoring and performance tracking, identifying areas for improvement.
- Prepare documentation for model development, validation, and governance.
- Collaborate with risk, finance, and business teams to support model implementation and usage.
- Ensure compliance with regulatory requirements (MAS, Basel) and internal risk policies.
- Analyze large datasets to identify trends and insights for model enhancement.
- Support ad-hoc risk analytics and reporting requests.
Requirements
- Bachelor's or Master's degree in Statistics, Mathematics, Economics, Finance, Engineering, or a related quantitative field.
- At least 2-5 years of experience in credit risk modelling, preferably in retail banking.
- Strong proficiency in SAS, Python, or R for statistical modelling and data analysis.
- Experience with SQL for data extraction and manipulation.
- Knowledge of regulatory frameworks (Basel, MAS) and IFRS 9 standards.
- Familiarity with machine learning techniques and their application in credit risk.
- Excellent analytical and problem-solving skills.
- Strong written and verbal communication skills.
- Ability to work independently and in a team environment.
- Experience with model validation or audit is a plus.