Credit risk model managementView Agenda
Key reasons to attend
Learn how to build and maintain a framework to validate credit risk portfolio models
Understand the impact of Basel 3.1 amendments
Approach the guidelines and implications of artificial intelligence (AI) in credit risk modelling
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About the course
Join Risk Learning and faculty members on this interactive learning event examining the current outlook for credit risk model management.
Participants will learn how to validate credit risk models and stress-testing on credit risk portfolios. Sessions will also explore the developments in credit risk such as the impact of Basel 3.1 amendments, expected economic trends in 2023 and estimation and mitigation of uncertainty.
AI and machine learning application in credit risk modelling session will focus on utilising smaller data, likewise the participants will learn how to process profits in model risk management.
Flexible pricing options:
Early-bird rate: book in advance and save $200
3-for-2 group rate: book three delegates for the price of two and save more than $2,000
Season tickets: book a team of 10 or more and save up to 50%
- Evaluate model risk management and governance through different framework
- Conduct impactful general principles of model design in stress-testing
- Address the developments for credit risk modelling by adjusting to new regulations
- Identify credit risk modelling in post-IFRS 9 with Basel 3.1 amendments
- Implement the application of AI and machine learning using smaller data
- Conduct the integration of climate risk on the PD model curve
Who should attend
Employees whose job responsibilities may include but are not limited to:
Model risk management
March 20–22, 2023
Time zones: Emea / Americas
Start: 13:15 GMT / 08:15 EST
Finish: 17:00 GMT / 12:00 EST
Model risk management and government for credit risk
Credit risk model validation
Stress testing credit risk portfolios
COVID-19 impact on credit risk modelling
Developments for credit risk modelling
Credit risk modelling post-IFRS 9
Application of AI and machine learning in credit risk modelling
Integrating climate risk and credit risk
Model risk management processes for profit
July 17–19, 2023
Time zones: Emea / Americas
Lead quantitative specialist
Grigoris Karakoulas Risk Learning Faculty
This course is CPD (Continued Professional Development) accredited. One credit is awarded for every hour of learning at the event.
The Risk.net resources below have been selected to enhance your learning experience:
US Bank cautions on regulators’ TLAC proposal - Read article | Risk.net
Banks temper credit loss models by editing Covid narrative - Read article | Risk.net
Modeling credit risk in the presence of central bank and government intervention - Read article | Risk.net
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