Description: The academy generator is widely applied in actuarial practice. Initially confined to regulatory reserving, companies are increasingly using the AAA/SOA generator over an ever widening range of applications testing the limits of the academy generator's intended function. The session will give a brief overview of the academy generator and the asset classes it can be used to model. It will also analyze the statistical properties of the academy scenarios and discuss the scenarios relative to standard validation criterion. Some of the challenges that actuaries face in using this framework will be reviewed and options for addressing these challenges will be offered.

Description: Model Risk Management continues to be an evolving area for insurers to be considering. This has grown from both internal and external forces and may require a different format to previous model risk frameworks held by insurers. Furthermore, there are a number of trends emerging that we believe will drive an increased focus on insurer’s model risk management frameworks such as technology automation, ever increasing data sources, and the use of predictive models. Risk management and the development of models is an area where insurance companies have performed well in the past. It is expected that frameworks currently exist within companies; the governance, documentation, validation and control of model risk are likely to be well established practices. The challenge that insurers must consider is how well these have been adopted throughout the company for all models used to make business decisions and if the same level of rigor has consistently been applied. Regulation in a high-velocity actuarial environment will to be a challenge that actuaries must spearhead and must be proactive in guiding rule making to ensure continued innovation while putting data security and risk management first.

Description: The goal of this paper is to study how a full-range tail dependence copula would be useful in assessing tail risks in a regression setting.

Description: This is presentations slides summarizing the many concepts presented in the research paper. “When Black Swans Aren’t: Holistically Training Management to Better Recognize, Assess, and Respond to Extreme Events”, by Guntram Fritz Albin Werther and Thomas Herget.

Description: This paper recommends the practical application of new portfolio risk/return measurements to achieved and back tested stock portfolio performance. This new risk measurement process addresses the issue of infinite variances empirically observed in most stock return distributions. From 2007 Enterprise Risk Management Symposium, M-AS07-1.

Description: Enterprise risk management ERM is for the measurement and the management of all significant risks of the business holistically irrespective of types and sources. The study offers significant advances in the current debate on the performance of enterprise risk management, in particular, minimizing the existing gap between the academic understanding and practitioners’ experience on the topic.

Description: The paper argues that Risks Evaluation at its core is a psychological process that can lead to the special type of chaos described in modern Chaos Theory. It will argue that quantification and scientific modeling does not exempt risk assessment from the potential for deep biases. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.

Description: Essays advocating for incentive compensation linked to the level of risk in an organization.

Description: Some of the uncertainties related to catastrophe models are explored, leading to the suggestion that the actuary is well suited to understand and use these in the context of an ORSA exercise. Part of the essay collection "Risk Metrics for Decision Making and ORSA"

Description: When using models a company can develop blind spots to risks. This article explains how to recognize the weaknesses in the models by recognizing the markets response to the innovation within the insurance product. Part of the essay collection "Risk Metrics for Decision Making and ORSA"