Description: "This video discusses the importance of identifying model risk in actuarial work. It explains the potential adverse outcomes due to inaccuracies or errors in models and emphasizes the need for actuaries to regularly review and manage these risks. It provides a step-by-step guide on how to identify model risk, making it a valuable resource for actuaries at all career stages.

Description: The purpose of this discussion is to introduce a few additional points and discuss how different assumptions will alter the results in some cases.

Description: This presentation estimates several models of interest rates, including seven without and four with regime shifts.

Description: This abstract describes a paper that investigates how to best choose a model from a flexible set of regime-switching models where the individual regimes are not constrained to be from the same distributional family.

Description: This article discusse key considerations to account for while planning for and executing the initial actuarial model handoff from development to production.

Description: Modeling experience sharing by David Yu who leads the retirement product and asset model development team within Prudential Financial

Description: Abstract of Research Project on Interest Rate Risk

Description: Argues that the financial and statistical data on loan restructuring practices collected within the last two years, since the 2008 collapse of the housing market, could be evaluated by actuaries and become a base for improving the existing models and developing new ones.

Description: Presentation at the 41st Actuarial Research Conference held on August 10-12, 2006 in Montreal, QC. This paper considers the problem of extending regime-switching models for asset returns to the situation with multiple asset markets. The conditional tail expectation CTE is highly sensitive to the assumed dependence structure between the regime models for the different markets. A Monte Carlo simulation is used to illustrate the cost of misspecification. The authors find that the model most commonly used by practitioners is worse than all of the alternatives that they investigate.

Description: In reaction to a spate of model conversion activity and rising acceptance of model risk management techniques, many companies have, or are in the process of centralizing their modeling function to accommodate both governance and efficiency demands. These operating model changes have produced a wide range of questions and issues, such as division of labor, roles and responsibilities, selection of tasks to keep decentralized, among others. This session will frame a series of key considerations around modeling function consideration, and share lessons learned with the audience.