Head of Wholesale Risk Modeling

Job Description:

The main objective of this role is to lead a team responsible for developing and maintaining wholesale risk models, as well as collaborate with the Head of Risk Analytics and Capital Management to ensure effective risk governance and best practices.

Key Responsibilities

• Establish and scale a new Centre of Excellence (CoE) for Wholesale Rating Models from scratch
• Provide strategic leadership and contribute to the development of best practices in model development and validation
• Maintain awareness of latest regulatory and industry updates, including Basel guidelines, IFRS 9, local regulations, and rating agency methodologies, and incorporate them into model design considerations
• Independently research and develop innovative solutions to enhance model performance

Stakeholder Engagement

• Develop and deliver presentations to Senior Management and Board-level committees
• Engage with multiple stakeholders across the credit lifecycle: Limit Management, Collateral Management, RAROC, Customer Rating
• Review financial spreading logic in newly developed credit lifecycle systems
• Ensure governance and audit readiness through proper model documentation and transparent development practices

Technical & Delivery Responsibilities

• Design and implement an end-to-end process for development, validation, and lifecycle management of Wholesale Rating Models
• Develop and validate a range of models, including Corporate/Wholesale Rating Models, such as Large Corporate, Mid Corporate, SME, Sovereign, FI, HNWI, Project Finance, and Specialized Lending
• Explore new approaches for rating model development for low default portfolios
• Master Rating Scale (MRS) calibration

People Management

• Build, mentor, and lead a team of modelers and consultants
• Drive capability building and continuous learning within the team through training, peer reviews, and knowledge sharing

Wholesale Model Monitoring

• Determine the goals of model monitoring, considering factors like accuracy and other relevant metrics based on the model purpose
• Determine the expected performance of the respective models on historical data
• Implement monitoring tools to continuously assess model performance, including input data quality and predictions
• Communicate the model performance to relevant stakeholders to ensure prompt attention to potential problems
• Regularly review and improve the model performance process based on feedback, changes in underlying data, and evolving business requirements

Credits & Climate Analytics

• Develop statistical climate risk models, integrate economic and social data to understand how climate risks may impact
• Develop different climate scenarios based on various emission pathways and climate change projections, assessing the potential impact of each scenario on identified financial risks
• Based on statistical models, develop adaptation strategies to mitigate relevant risks
• Establish a system for continuous monitoring of climate date and update climate risk models regularly
• Incorporate existing and potential future policies and regulations related to climate change into model development
• Involve stakeholders in the meeting process to ensure a comprehensive understanding of local conditions, priorities, and concerns

Required Skills & Qualifications

• Strong foundation in Statistics and Mathematics, with hands-on experience in developing and validating Wholesale Rating Models (PD, LGD, EAD) and a deep understanding of model lifecycle best practices
• Proficiency in strong programming languages such as R and Python, with expertise in data analysis and visualization using Excel and PowerPoint. Knowledge of other relevant tools or platforms (e.g., SAS, SQL, visualization tools, workflow automation tools) would be an advantage
• Hold a degree in Statistics, Mathematics, Computer Science, Quantitative Finance, Economics, Engineering, or a related field
• Passionate about risk management and advancing the science of credit risk modeling. Excellent communication skills, both written and spoken, with fluency in English. Ability to convey complex technical concepts clearly to both technical and non-technical stakeholders

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