Description: We develop a model based on causal mortality in order to better understand inequalities in life expectancy across socioeconomic circumstances.

Description: This paper talks about the Swedish pension system reform.

Description: This paper demonstrates the use of Quantile Regression in the development and understanding of conditional value at risk (VaR) models for enterprise risk management.

Description: This paper will focus on default distributions and why they are important.

Description: Interest rate changes and volatile equity returns have contributed to significant funding and expense volatility for defined benefit plans in recent years. This paper will describe the design of an option contract with payouts that are tied to the combined impact of interest rates and investment returns on the funding level of a defined benefit pension plan. Current derivatives used by plan sponsors can limit exposure to one of these risks; however, a derivative that combines these risks may provide more targeted protection to a plan sponsor at lower cost. This paper discusses several considerations in designing such a derivative. It will also briefly discuss pricing of the option. Finally, the difference in potential outcomes between plan funding with and without option ownership will be demonstrated. As an outcome of the design work, a new way to visualize pension risk that may be useful in sponsor accounting disclosures will be shown.

Description: This paper demonstrates that extreme value theory (EVT) can be used as a tool to model policyholder behavior in the extreme tail. This paper applies EVT to the study of variable annuity dynamic lapse behavior in the extreme tail. It illustrates a process whereby a company can fully model policyholder behavior, including the extreme tail, with existing data. No judgment about the extremal behavior is necessary.

Description: Recently researchers, practitioners, and regulators had intense debates about how to treat the data collection threshold in operational risk modeling. There are several approaches under consideration—the empirical approach, the “naive” approach, the shifted approach, and the truncated approach—for fitting the loss severity distribution. Since each approach is based on a different set of assumptions, different probability models emerge. Thus, model uncertainty arises. When possible we investigate such model uncertainty analytically, otherwise we use Monte Carlo simulations. For specific parametric examples we consider exponential and Lomax distributions which are special cases of the generalized Pareto family. Our primary goal is to quantify the effect of model uncertainty on risk measurements. This is accomplished by evaluating the probability of each approach producing conservative capital allocations based on the value-at-risk measure. These explorations are further illustrated using a real data set for legal losses in a business unit (Cruz, 2002).

Description: Contemporary ERM has moved from an event-based view of risk to a hierarchical, systems-based approach. In order to operationalize such an approach, a methodology is proposed in this paper that draws on phylogenetic approaches that have been successfully developed for biological evolution. The technique and process provide an insight into the lineage, pace and impact of external conditions on the evolution of risks. They also provide a unique and rational classification of risk in an enterprise that can be used to optimize risk management resources. An example of a fictitious insurance company is used to illustrate the approach. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.

Description: This article is a summary of the authors’ two other articles where they discuss pension systems and whether they do in fact distort retirement decisions.

Description: Wavelet models are used to analyze risk by time and frequency and provide richer information than time series models.