Description: This paper develops the binomial version of the Lee-Carter model and provides a comparative study of simulation strategies for assessing risk in mortality rate predictions and associated estimates of life expectancy and annuity values in both period and cohort frameworks.

Description: We propose an age-shift model to modify the LC model and deal with the problem of parameters. The proposed method attains smaller estimation errors with respect to mean absolute percentage error or mean square error. We also apply the proposed age-shift model to the mortality rates of these four countries to evaluate the longevity risk in annuity products by measuring life expectancy.

Description: This paper describes the process one goes through as a project manager in implementing an ERM dashboard. The purpose of the dashboard is to provide the management of the organization with a top-of-the-house view of all risk types in an integrated manner.

Description: Paper examines the asset allocation behavior of state and local pension plans.

Description: Paper presents a conceptual approach that could improve the security of retiree benefits while reducing the variability of employer contributions and improving the long-term prospects of the plan as a whole.

Description: The current financial model put forth as the market value of public sector pension benefit liabilities is simply the expected cash flows of the accumulated benefit obligation, as defined for current private sector financial reporting, discounted using a risk-free yield curve. This model is in serious need of an overhaul. This monograph addresses this issue.

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 paper develops an option pricing model that takes cost of capital concepts as its foundation rather than dynamic replication. The resulting model, called the 'C' measure in this paper, is related to the family of Affine Jump Diffusion models that are well known in the finance literature, so it is fairly easy to understand and implement. We argue that this is a reasonable model to use for estimating equity implied volatilities that are beyond the five- to 10-year horizon that can typically be observed in today‘s capital markets. The paper concludes with a short discussion of how to grade from observable market data to the 'C' measure.

Description: In this paper, we formulate the Capital Allocation problem as an optimization problem in which we seek the mix of business that maximizes an insurance company’s Expected Net After Tax Income subject to a constraint on the Tail Value at Risk TVAR. Using the method of Lagrange multipliers, we demonstrate that the returns on the respective TVAR contributions, so-called RORAC, are equal across all lines of business when the mix of business is optimal. Although the discussions in this paper center on the TVAR, the conclusions hold true for any conditional expected value measure. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.

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.