Description: This paper presents an introduction to collective risk theory. In collective risk theory one seeks to investigate directly the risk enterprise as a whole. Primary interest is focused not upon the gains, losses, or claims from individual policies but upon the amount of total claims or the total gain arising from all the policies in the portfolio considered. Followed by several discussion papers submitted.

Description: This paper introduces a rich stochastic modeling framework for understanding risks in multiple-decrement contracts. The example in the paper is a 20-year Term insurance contract. Not only are mortality and lapsation considered stochastic, but the parameters governing them are. For example, mortality risk is composed of four risk elements, including error generated in the underwriting process, volatility around the best estimate, catastrophic events that impact mortality, and the trend in mortality improvement or deterioration. When stochastically modeled, the relative contribution and risk profile of each risk element can be evaluated. Generating stochastic mortality results provides a distribution of results that an organization faces and the severity and incidence of the tail events.

Description: The April 2016 Issue of The Modeling Platform

Description: From a session at the Spring meeting of the Society of Actuaries held in San Antonio, Texas, June 14-15, 2004 This session discusses emerging capital and reserve requirements on Variable annuities with guaranteed benefits and the effect that hedging/capital management strategies can have.

Description: Panelists discuss economic capital, capital modeling, and hedge modeling, especially for guaranteed living benefits [GLBs] on variable annuities. Session 34PD of the 2005 Valuation Actuary Symposium.

Description: This session presents a summary of actuarial and potential uses of stochastic modeling for health actuaries. Three case studies are presented: rating health plan reimbursement provisions, developing claim liabilities, and defining appropriate reinsurance levels. From the Record of the Society of Actuaries, Volume 30, No. 1, Session 18

Description: This session covers stochastic modeling processes currently in use and explores others that may be beneficial to health actuaries. From the Record of the Society of Actuaries, Vol. 31, No. 2, Session 76

Description: This article presents a case study that examines the implication of using real-world interest rate scenario generators with a block of fixed deferred annuities. We contrast cash flow testing results based on New York 7 deterministic scenarios to stochastic scenarios generated with the Academy Interest Rate Generator , as well as an alternative economic scenario generator designed explicitly to capture the risk of a persistently low interest rate environment and the transition to a rising interest rate environment.

Description: This article provides an overview of the different types of real world interest rate scenarios that practitioners use in the life insurance industry and explores different approaches to building those generators.

Description: This paper illustrates a current approach to capital allocation, referred to herein as Tail Contribution Analysis TCA, using it to evaluate the impact of changes in an insurer’s operations by allocating capital to individual lines of business. It then highlights a common problem in the implementation of the procedure arising from reserve volatility and briefly notes the failure of the methodology to account for a firm’s changing levels of risk under various strategies. Finally, it introduces an alternative method for analyzing business segments and strategies called Economic Profit Analysis EPA. We will discuss EPA’s key feature, “volatility replication,” an intuitively appealing process of building investor expectations and capital market information into the risk-and-return measurements used to evaluate strategic decisions. Finally, we will illustrate the benefit of using EPA in overcoming the problems of TCA and thereby providing concise reliable information for business decision making.