Key Responsibilities
Model Development
- Versed in modelling techniques which includes Basel quantification requirements to guide strategic planning of models use and development.
- Develop robust, reliable, and stable models for retail portfolios (e.g., Application and Behavioural Scorecards, PD, LGD, EAD models), with thorough documentation and ensuring alignment to internal standards and full compliance with regulatory requirements where applicable.
- Review and guide and model development activities to ensure modelling accuracy and consistency.
- Apply appropriate modelling techniques, including machine learning methods, to deliver robust, reliable, and well-calibrated models.
- Lead end-to-end model development activities, ensuring timely, high quality delivery modelling projects and regulatory submissions.
- Support regional model development or review initiatives as and when required.
- Stay abreast of industry trends and advancements in risk modelling, identifying opportunities to integrate new approaches into data-driven risk management strategies.
Model Implementation
- Manage and ensure clear functional specifications is provided to guide model implementation.
- Lead User Acceptance Testing (UAT) to ensure models are deployed accurately.
- Perform model impact analysis, assess implications on business decisions and risk strategies, communicate implication and manage expectation across business and risk stakeholders.
Model Monitoring & Performance Management
- Review model performance reports, identify deterioration or shifts in model performance early and proactively propose solutions to address signs of deterioration.
Stakeholder Engagement
- Manage engagement with cross-functional teams including Business, Finance, Risk, Audit, and IT to ensure model development and implementation aligns with strategic objectives.
- Manage end to end model related discussions with internal validators, auditors, and regulators.
- Manage and collaborate closely with stakeholders to ensure high-quality regulatory model submissions, minimising errors and meeting timelines.
Job Specification
- Bachelor Degree or above in Economics, Finance, Math, Statistics, Actuarial Science, Data Science, Machine Learning Artificial Intelligent or equivalent.
- Professional Accreditation: CFA, FRM, Chartered Banker (added advantage)
- Minimum 5 years of experience in analytical and statistical modelling related roles (banking and insurance experience is a plus).
Technical/Functional skills
• Proficient in SAS Programming *(minimum 3 years)
• Proficient Python, PySpark Programming Language (added advantage)
• Ability to generate analytical insights to business problems.
• Quantitative modelling skills
• Present and communicate with clarity on the analytical solutions
• Deep understanding of Basel IRB modelling, internal credit underwriting, and regulatory risk frameworks.
• Hands-on experience with model development tools and techniques, including scorecard development, logistic regression, and machine learning algorithms etc.
Personal skills (Soft Competencies [Core/Leadership])
• Strong interpersonal skills.
• Excellent verbal and written communication skills in English.
• Effective communicator with the ability to explain complex modelling concepts to non-technical stakeholders.
• Demonstrated proactive and facilitation skills.
• Strong presentation and influencing skills
• Project management skills with the ability to manage multiple priorities and meet deadlines
