Banks and financial institutions have been using models for decades, for example to manage risks or to calculate prices. Hence, there has always been the risk that an incorrect model specification or the incorrect use of a model lead to a decision coming along with negative consequences, such as financial losses.

To measure and mitigate Model Risk, banks have established extensive and complex Model Risk Management (MRM) approaches. However, with the increasing use of Artificial Intelligence (AI) and Machine Learning (ML), a comprehensive adaptation of this Model Risk approach becomes essential.

Despite a wide range of undisputed benefits, AI/ML approaches come along with their own specific inherent risks that are not yet adequately addressed in the existing Model Risk Management frameworks.

In this webcast the speakers will present the challenges/ risks and regulatory requirements in using AI/ML and how the Model Risk Management Framework should be adapted to mitigate those risks. In addition, we would like to focus on "Fair Machine Learning" in detail and discuss challenges and solutions based on practical examples.