Credit risk model management
About the course
This course provides insights into the effective management of credit risk models, focusing on the latest Basel 3.1 and IFRS 9 requirements. Participants will deepen their understanding of key estimation techniques, learn best practices in stress-testing across portfolio types and explore strategies for adapting models to economic shifts.
Through discussions on AI applications in credit risk modelling and guidance on model validation, attendees will learn to enhance model accuracy and transparency. The course also covers essential governance practices, including risk appetite, policy development and adherence to evolving regulatory standards.
Subject matter experts will address the unique challenges posed by both high- and low- default portfolios, equipping participants with the skills to optimise risk frameworks and build resilience in today’s dynamic economic landscape.
Learning objectives
Examine the evolving landscape of model risk management
Leverage artificial intelligence (AI) and machine learning to improve model accuracy
Discuss estimation techniques for high- and low-default portfolios
Explore strategies for handling missing scoring data and ratings assessments
Investigate the challenges associated with low-default portfolios under stress
Discover best practices for developing a credit risk appetite
Who should attend
Employees whose job responsibilities may include but are not limited to:
- Credit risk
- Risk modelling
- Risk management
- Model risk management
- Machine learning
- Stress testing
Tutors
Grigoris Karakoulas
InfoAgora
President
Grigoris has over 26 years of experience in predictive modelling and risk management. He is the president and founder of InfoAgora that provides risk management consulting and more to financial services organisations. He is an adjunct professor in the department of computer science at the University of Toronto.
Prior to founding InfoAgora, Grigoris was working at CIBC as vice president of customer behavior analytics, responsible for customer decisioning and credit risk measurement solutions for adjudicating new customers and proactively managing existing ones. He has been a postdoctoral fellow in the Institute of Information Technology at the National Research Council. He is on the PRIMA subject matter boards for stress-testing and enterprise risk management and has published more than 40 papers in journals and conference proceedings. He holds a PhD in computer science.
Christian Marini
Prometeia
Partner and head of credit risk for international markets
Christian has a long experience as a leading consultant in the quantitative risk management modelling space, working in collaboration with primary financial and non-financial institutions as well as public companies, including local and central Banks. His expertise includes both technical knowledge in the development of credit risk methodologies and credit risk architecture systems, as well as commercial acumen gained in developing international markets within the risk management space.
Registration
November 10–12, 2026
Online
13:30 BST
$2499
Enquire about:
- Agenda and registration process
- Group booking rates
- Customisation of this programme
- Season tickets options
Accreditation
This course is CPD (Continued Professional Development) accredited. One credit is awarded for every hour of learning at the event.
Enquire now
Expand your learning
The premier meeting place for the risk community. Providing clarity and guidance on the fast-changing regulatory landscape of capital, credit and market risk, liquidity and derivates use.
Risk Journals deliver academically rigorous, practitioner-focused content and resources for the rapidly evolving discipline of financial risk management.
Risk Books are authored by leading professionals and academics. With over 150 books spanning 1,000s of chapters, our publications team is committed to connecting readers with these world class experts.
Regularly updated by our team analysts, journalists and producers, our glossary demystifies the terminology and acronyms used in risk management, risk transfer, policy, technology and innovation.