Credit risk model management

  • Quant and model risk
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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 for this interactive and technical learning event examining best practice for credit risk model management.

Participants will learn how to validate credit risk models and stress-test credit risk portfolios. This course will examine developments in credit risk such as the impact of Basel 3.1 amendments, expected economic trends in 2023 and mitigating uncertainty.

The AI and machine learning application in credit risk modelling session will focus on utilising smaller datasets and participants will learn best practice techniques in model risk validation and stress-testing.

Only until December 31, 2023:

  • Locked rate: $1,999.
    Book by December 31, 2023 and save $1000 (quote LOCK23 code)

Learning objectives

  • Evaluate model risk management and governance through different frameworks

  • 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: 

  • Credit risk

  • Risk modelling 

  • Risk management

  • Model risk management

  • Climate risk

  • Stress testing 

  • Machine learning


March 12–14, 2024

Timezones: Emea/Americas


  • Credit risk model validation

  • Stress-testing credit risk portfolios

  • Developments for credit risk modelling

  • Credit risk modelling post-IFRS 9

  • Application of artificial intelligence (AI) and machine learning in credit risk modelling

  • Integrating climate and credit risk

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This course is CPD (Continued Professional Development) accredited. One credit is awarded for every hour of learning at the event.

Pre-reading materials

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March 12–14, 2024

Online, Emea/Americas



Early-bird Price

Ends February 9
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