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Model Risk and Machine Learning

Model Risk and Machine Learning

Thought Leadership Webinar: In this webinar, Jos Gheerardyn will discuss the various types of model risk that are specific to machine learning models and artificial intelligence applications. He will also highlight how these new techniques can be used to make model risk management more efficient.


Presented By:
Jos Gheerardyn
Co-founder/CEO, Yields.io

September 11, 2019

10:00 a.m. - 11:00 a.m. EDT
2:00 p.m. - 3:00 p.m. GMT

Session Length:
60 minutes


About This Webinar

The introduction of machine learning and artificial intelligence presents both opportunities and challenges to financial institutions. Opportunities because more advanced analytics allow for increased profitability, better client support, and improved risk management. Challenges because more complicated analytics inevitably lead to heightened model risk. In the first part of this webinar, we will explain how the existing model risk frameworks that institutions have developed to deal with classical models can be expanded to face the particular challenges of ML algorithms. This will include dealing with more complicated datasets, handling bias, and improving the explainability of these algorithms. In the second half of the webinar, we will discuss the application of machine learning in model risk management as we will show how these novel algorithms can be used to improve our understanding of model failure. We will, for instance, show how ML can be used to generate smarter (stress) scenarios and how it can be leveraged to quantify model risk more accurately. 

The main conclusion of this talk will be that due to the abundance of ML solution providers and the introduction of AutoML (i.e., software tools to create machine learning algorithms automatically), the very fact of using ML and AI will soon cease to be a differentiating factor. What will matter is how institutions manage these models. Only with proper governance will an institution be able to quickly evolve its modelling approach in order to adapt to changing market trends and to capture the value of ML sustainably. This evolution parallels what happened in software development already a few decades ago and will transform model risk management from a cost center into a value driver.

About Our Experts  

  Yields.io co-founder and CEO Jos Gheerardyn has built the first FinTech platform that uses AI for real-time model testing and validation on an enterprise-wide scale. A zealous proponent of model risk governance and strategy, Jos is on a mission to empower quants, risk managers. and model validators with smarter tools to turn model risk into a business driver.

Prior to his current role, Jos has been active in quantitative finance both as a manager and as an analyst. Over the past 15 years he has been working with leading international investment banks as well as with award-winning start-up companies. He is the author of multiple patents applying quantitative risk management techniques to imbalance markets. Jos holds a PhD in superstring theory from the University of Leuven (Belgium).

Continued Risk Learning Credits: 1

PRMIA Continued Risk Learning (CRL) programs provide you with the opportunity to formally recognize your professional development, documenting your evolution as a risk professional. Employers can see that you are not static, making you a highly valued, dynamic, and desirable employee. The CRL program is open to all Contributing, Sustaining, and Risk Leader members, providing a convenient and easily accessible way to submit, manage, track and document your activities online through the PRMIA CRL Center. To request CRL credits, please email learning@prmia.org.

  Membership Type Price  
  Sustaining, Corporate, and RIM Members $ FREE  
  Contributing Member $ 35  
  Non Member $ 75  

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9/11/2019 10:00 AM - 11:00 AM
Thought Leadership Webinar
Online registration not available.

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