Job Description:
In conjunction with models and scorecards, and the bank’s credit risk management frameworks, build and maintain models for onboa..
Job Description:
In conjunction with models and scorecards, and the bank’s credit risk management frameworks, build and maintain models for onboarding, assessment, ongoing monitoring and reporting of exposures for the Bank. This also includes the usage of AI/ML and incorporating of alternative data into such models.
Manage the model risks for all scorecards, segmentation, loss forecasting and IRB models including validation, monitoring, managing through limitations and compliance to the Model Risk Management Framework
Collaborate across functions, enable embedded financing, implement credit models in the various lending platforms / ecosystems that the Bank will engage itself in.
Conduct both regular and ad-hoc portfolio data analysis on post lending accounts to identify the associated credit risks and problems and make appropriate recommendations on risk mitigation.
Monitor the performance of the bank’s loan portfolios to ensure they comply with regulations and bank-wide credit risk strategies, policies and manuals.
Solicit and analyse market related information on the practice or trend of retail and corporate risk management, and make recommendations to Senior Management for procedural reviews.
Review and validate credit decision process and credit modelling, and identify areas for improvements. Drive automation initiatives and be relentless about reducing manual work-arounds
Work closely with business, product teams, data scientists (where appropriate), to drive key initiatives to achieve business needs that are within risk appetite.
Oversee regular tracking on MIS and key performance metrics of all scoring models, loss forecasting models and risk segmentation models.
Key contributions also towards ICAAP, IWST, Regulatory Reporting, ECL modelling and regular fine-tuning of the same.
Job Qualification:
Degree or above with major in Mathematics, Statistic or Financial Engineering etc.
Minimum 10 years relevant experiences from credit risk analytics and/or modelling in banking. SEA market know-how will be a plus
Hands-on experience in the end-to-end development/validation of credit risk models
Sound knowledge of Basel, IFRS9, MAS requirements in relation to models
Good understanding of credit products in wholesale / SME segment
Good stakeholder management and presentation skills
Proficient in SAS, SQL and other analytical tools (R, SPSS, Python)
CFA or FRM certification will be a plus
Self-initiated, excellent analytical skills and be able to handle multiple-tasks under tight schedules
Articulate; Good command of written and spoken English.
Meticulous, organised and able to produce documentation of high quality with clear and concise messaging.
Self-assured and able to interact well with various working levels
