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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Customised Solutions

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Working with the portfolio of expert tutors and’s editorial team, we can develop and deliver a customised learning to make the most impact for your team, from initial assessment to final review. 

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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 2024 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.

Pricing options:

  • Early-bird rate: save up to $800 per person by booking in advance (refer to the booking section for the deadline)
  • 3-for-2 rate: save over $2,000 by booking a group of three attendees (applicable to this course)
  • Subscriber reward: save 30% off the standard rate if you are a subscriber (use code SUB30)
  • Season tickets: save over $1,000 per person by booking 10 or more tickets (available on selection of courses)

*The 30% subscriber reward discount is applicable only to current subscribers. If this criteria is not met, we reserve the right to cancel the booking and issue an invoice for the correct rate. Discounts cannot be applied to already registered participants.

Learning objectives

  • Evaluate model risk management and governance through different frameworks
  • Address the developments for credit risk modelling by adjusting to new regulations
  • Identify credit risk modelling in post-International Financial Reporting Standard 9 with Basel 3.1 amendments
  • Conduct impactful general principles of model design in stress-testing
  • Implement AI and machine learning using smaller datasets
  • Conduct the integration of climate risk on the probability-of-default 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


July 16–18, 2024

Live online. Timezones: Emea/Americas


  • Credit risk model validation
  • Developments for credit risk modelling
  • Credit risk modelling post-IFRS 9
  • Stress-testing credit risk portfolios
  • Application of artificial intelligence (AI) and machine learning in credit risk modelling
  • Integrating climate and credit risk

View detailed agenda


Grigoris Karakoulas


InfoAgora Inc

View bio

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. 


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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July 16–18, 2024

Online, Emea/Americas


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Enquire about:

  • Agenda and registration process
  • Group booking rates
  • Customisation of this programme
  • Season tickets options

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