Business Function

Risk Management Group works closely with our business partners to manage the bank's risk exposure by balancing its objective to maximise returns against an acceptable risk profile. We partner with origination teams to provide financing, investments and hedging opportunities to our customers. To manage risk effectively and run a successful business, we invest significantly in our people and infrastructure.

This role is to develop, maintain, and support the implementation of credit risk methodologies and PD, LGD and EaD models for the wholesale portfolios, in compliance with internal standards and relevant regulations, including those relating to MAS and HKMA.

Responsibilities

• Develop, implement and maintain Probability of Default (PD), Loss Given Default (LGD) and Exposure at Default (EaD) models and credit risk methodologies for Corporates, Financial Institutions, Specialized Lending, and Wealth Management portfolios, for regulatory (eg. IRB) purposes.
• Prepare and maintain clear and detailed documentation of model developments and reviews.
• Liaise with and support the monitoring and implementation teams on ongoing model monitoring and model implementation into various risk systems, providing model specifications and testing system functionality prior to deployment.
• Lead the internal models' approval and governance processes, providing detailed explanations and justification of modelling decisions and assumptions and addressing potential issues, particularly those relating to Model Validation and Internal Audit's reviews.
• Support external models' approval and governance processes, providing necessary explanations, justifications and analyses, particularly those relating to regulatory/supervisors' assessments and external auditors reviews.
• Liaise with business and product management to provide risk analytics solutions for enhancing the credit risk-return tradeoff.
• Research, propose and develop enhancements of existing models, to improve accuracy, risk discrimination, forward-looking capability and responsiveness to economic environment, considering the evolution in the relevant regulatory environment, academia and industry.
• Work closely with other analytics teams within the bank on the bank's other analytics agenda, such as in the quantification of climate risk and in the AI/ML agenda.
• Develop self and others in the team for improving efficiency and drive transformation.

Requirements

• Advanced knowledge of Python and Pyspark is a must. Knowledge of R will be an added advantage.
• Previous experience in the development, monitoring and maintenance of credit risk models including PD, LGD, and EAD models for wholesale portfolios is desired.
• Good understanding of statistical / econometric / modelling theory and technical applications in the area of credit risk.
• Good understanding of the Basel Accord, MAS and HKMA Supervisory Requirements.
• Good knowledge of credit process and business products.
• Excellent communication and writing skills.
• Previous experience in climate risk modelling is an added advantage.

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We offer a competitive salary and benefits package and the professional advantages of a dynamic environment that supports your development and recognises your achievements.