The Evolution of Enterprise Model Risk Management

"Model risk management is the art of handling the inherent uncertainty related to mathematical modelling. We create algorithms for many different reasons. In the past, most models were built to study the evolution of dynamical systems (e.g. a credit risk model or a valuation model). Models were often created via a first-principles approach with analytical tractability in mind. Nowadays, ML models are everywhere, impacting both our individual behaviour and changing the dynamics of entire societies."

- Jos Gheerardyn, CEO and co-founder, Yields.io


White Paper: 
The Evolution of Enterprise Model Risk Management

Author: Jos Gheerardyn

In this paper, the following topics will be covered:

What are the key challenges in model risk management today. 

How can these challenges be addressed with technology?

About The Author

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.

What are the most important technology requirements?

How to apply these insights to concrete examples such as workflow automation and model inventory structure. 

Jos Gheerardyn, CEO and Co-founder of Yields.io

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The Evolution of Enterprise Model Risk Management