Recent technological advancements have accelerated the integration of AI and machine learning models into more and more processes. However, model risk must be effectively managed. If left unchecked, the consequences of model risk can be severe. AI and machine learning models require constant monitoring and effective validation – this is not only a regulatory requirement in many industries but also sound business practice.
On this webinar, Seph Mard, Head of Model Risk Management at DataRobot and Peter Simon, Financial Markets Practice Data Scientist at DataRobot will present the cornerstones of effective modern model risk management in the age of AI and machine learning. It provides:
- An overview of AI and machine learning
- A summary of the regulatory background and the machine learning model lifecycle
- An overview of the challenges and emerging best practices for the validation of models in an ever-changing world of AI and machine learning
