Most life insurance companies have spent significant time in unraveling PBR requirements. As these models are rolled off the assembly line, it becomes necessary to put a governance and validation framework. The validation becomes complicated as the model has three independent components and involves stochastic models. Additionally, experience studies become increasingly important and a rigorous process to do data analysis derive assumptions and govern these assumptions is required. Companies also need to create attribution reports to explain results from one time period to another. This session will discuss model governance, assumption governance, Model validation and analysis of results.
At the conclusion of this session, attendees will be able to: describe some of the validation approaches that can be used to validate PBR models; explain key governance concepts that apply specifically to PBR models and assumptions; and create analytic reports that can help users understand the movement in results.