Quantifying Model Uncertainty with AI
By Jos Gheerardyn
A key challenge in model risk management is to quantify model uncertainty. This slide deck was used by Jos Gheerardyn in various courses on this topic. It highlights which machine techniques can be used to make quantification more efficient.
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 & 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, he 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 Gheerardyn holds a PhD in superstring theory from the University of Leuven, Belgium.
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