Credit Risk Consultant - IRB Enhancements

Job Purpose:

My client is seeking an experienced Credit Risk Professional with expertise in IRB modelling and a strong understanding of regulatory frameworks to lead enhancements to their credit risk models. The successful candidate will collaborate closely with internal stakeholders across risk management, finance, and IT to implement improvements that strengthen the credit risk management practices.

Key Responsibilities:

• Lead the enhancement and refinement of the Internal Ratings-Based (IRB) approach to credit risk modelling, incorporating best practices and regulatory requirements.
• Develop and validate credit risk models, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD), to ensure accuracy and robustness.
• Conduct comprehensive reviews of data sources, methodologies, and assumptions underlying credit risk models, identifying areas for improvement, and implementing necessary enhancements.
• Collaborate with cross-functional teams to gather and analyse data, including historical credit performance data, economic indicators, and market trends, to inform model development and calibration.
• Stay abreast of regulatory developments and industry trends related to credit risk modelling and IRB frameworks and assess implications for [Your Building Society Name]'s risk management practices.
• Support regulatory interactions and examinations related to credit risk modelling and IRB implementation, including responding to inquiries and providing documentation as needed.
• Provide expertise and guidance to stakeholders across the organization on credit risk modelling techniques, assumptions, and results.

Experience Required:

• Extensive experience in credit risk modelling, with a focus on IRB approaches within the banking or building society sector.
• Strong understanding of regulatory requirements related to credit risk management, including Basel III/IV, IFRS 9, and local regulatory guidance.
• Proficiency in statistical analysis tools and programming languages (eg, SAS, R, Python) for data manipulation and modelling.