- Model Validation tasks
- Assist with / involve in reviewing / validating risk models (e.g. Retail / Non-retail scorecards / models, PD / LGD / EAD models, liquidity models, market risk VaR, FRS 9 etc.) implemented within the Bank to ensure that they are fit for purpose
- Preparing comprehensive model validation reports in accordance with the model risk management standards and internal model risk framework
- Communicate findings / reports to the model developers and follow-up on the status of corrective actions taken to ensure that model gaps and issues are adequately addressed
- Maintain proper documentation / audit trails, e.g. model log and relevant administrative / governance records
- Assist with / involve in preparing / establishing model risk management standards and internal model risk framework / standard operating procedures to ensure that they are up-to-date and comply with necessary regulatory standards and industry best practices
- Support the on-going technical research work such as developing / maintaining analytical template for data modeling and statistical tests, as well as to study in-depth various risk modeling concepts / methodologies, to improve robustness of validation performed
- Produce management dashboards to measure and track the Bank’s Risk Adjusted Return on Capital (RAROC) and other risk adjusted performance measures (RAPM) against established benchmarks.
- Provide analytic support to produce insights related to risk/capital charges and risk return of the Bank’s portfolios
- Assist in enhancing the RAPM methodology (for both pre and post deal components) to improve the accuracy of the Bank’s RAPM measurement
- Risk Management tasks
- Compiling Integrated Risk Management Dashboard for Group Risk Management Committee & Board of Directors meeting
- Support other ad-hoc tasks
- Quantitative skills in quantifying risk
- Strong analytical and problem solving skills with aptitude for logic
- Resourceful and adaptable in a changing environment
- Effective written and verbal communication
- Stakeholder management/engagement
- Knowledge in credit, ECL and pricing models
- Knowledge of key regulations e.g. BNM Guidelines, FSA, Basel II, Basel III, MFRS, etc.
- Familiarity with IRB requirements will be an advantage
- Data management / data mining
- SAS & SQL coding for data preparation and statistical analysis. R & Python will be an advantage.
- University Graduate with or Qualified Professional with at least 3 years experience in banking and financial industry, with exposure to statistics / mathematics / actuarial science / model validation.