21st Edition Model Risk
Master the governance and validation of models in a volatile market, where advanced technologies and regulatory pressures are causing a variety of challenges to model risk management teams
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How can you best validate and monitor AI and machine learning models without creating oversight biases for or against existing methods?
Avoiding “model validation arbitrage” is extremely important. ML / AI models might pass scrutiny where a traditional model would fail because of issues of low coefficient significance or high correlations. Fairly comparing different kinds of models requires a rethink of how we validate traditional models as well. Model developers also need to better understand when a data set is no longer “out of sample” because of the number of models that are being compared. These are just a couple small examples of the range of issues that must be considered.
In terms of our platform, (our conferences are intimate peer-led meetings where all speakers and delegates are senior executives from top financial institutions), how do you see it assisting you with overcoming the challenges you currently face?
I want to learn more about where FIs are in the process of adopting new model types and what processes they have put in place for model risk management. My sense is that a wide range of practice exists with little convergence yet on best practices.
What are your main areas of focus at the moment regarding model risk?
I think how to manage model risk for machine learning and climate impact models are particularly important and challenging.
How can you best utilize and manage the uncertainties inherited in climate change and ESG models?
We know that climate change scenarios and potential impacts are highly uncertain, and yet the cost of ignoring such issues can be quite high. Therefore, we need to take a confidence-weighted approach to respond to the risks we can quantify.
Ahead of the GFMI 21st Edition Model Risk conference we spoke with Dr Joseph Breeden, President of the Model Risk Managers' International Association (MRMIA.org). Dr. Breeden has been designing and deploying risk management systems for loan portfolios since 1996. He co-founded Deep Future Analytics in 2013, which focuses on portfolio and loan-level forecasting solutions for pricing, stress testing, LP valuation, and CECL. He previously founded Strategic Analytics in 1999 where he invented the modern approach to vintage forecasting and founded Prescient Models in 2011 where he merged vintage modeling with behavior scoring and is now part of DFA.
November 30- December 2, 2022
Chicago, IL
An interview with Dr. Joseph Breeden, President of the Model Risk Managers' International Association (MRMIA)
Dr. Breeden will be presenting the post-conference workshop during day two (12/2/2022) of the 21st Edition Model Risk conference!
Masterclass: Practical Model Risk Management for AI / ML, Climate Change / ESG, and Macroeconomic Adverse Selection
Outcomes:
- Understand emerging best practices in model risk management for AI and machine learning models
- Learn key issues in model risk from climate change
- Review how ESG regulations can impacts model risk
- Balance cost and benefit when designing model risk practices, especially in emerging areas
Why You Should Attend:
This session focuses on real-world experiences, implementable practices, and answers to specific questions from attendees. AI and machine learning models bring many new challenges and highlight areas previously ignored with traditional models. We discuss the unique risks of new modelling techniques, ways to mitigate those risks, and how to avoid MRM arbitrage. With climate change and ESG, we review the real underlying risks for lenders today and how those can be mitigated. The session finishes with a discussion macroeconomic adverse selection, how the environment of 2022 / 2023 brings models risks not seen since 2007-2009, how to identify the weaknesses, and how best to management those risks through volatile economic periods. The session thus provides suggestions to manage both current and emerging model risks.
For registration pricing and multiple attendee discounts, please contact:
Ria Kiayia
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