According to number of surveys, the Artificial Intelligence comes with substantial benefits and the expectations are very high. But do these come for free?

AI models come with number of chalenges and expose us to risk that we take decissions based on inaccurate models or that we use these models for purposes there were not designed for. The process of managing of this risk is in the financial world refered to as Model Risk Management.

Financial institutions have been relying on models to support their decision-making for decades; therefore, managing the life cycle of models and model risk management are not new topics.  In recent times, however, the discipline of model risk management has become more formalized and rigorous, and in particular the recent industry & technology developments in the Artificial Intelligence & digitalization areas push also other companies to build new models and more complex ones in order to streamline and automate their decisions. This requires companies to put an extra compliance and governance effort into management of their models and of the model risk embedded there. 

 

In order to address the above, companies around the world are increasingly looking for skilled Model Risk Management professionals to tackle these challenges. A number of leading firms have already established dedicated Model Risk Management units with a clear task to get the Model Risk under control. Managing model risk requires a broader perspective and should not rely solely on Model Validation activities, which is the more traditional approach, but involve tools such as Model Governance, Model Risk Profile & Appetite, analysis of Model Risk Concentrations & Exposure, etc.

You can register to the training by following the link below.

https://prmia.org/Shared_Content/Events/PRMIA_Event_Display.aspx?EventK…