Description: This article explains why stochastic modeling is becoming more pervasive, and describes a specific stochastic application with metrics to measure results.

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: 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: This paper first derives the fair participation rate based on a fair value of the equity-indexed annuity EIA. Then using risk measures, a new participation rate is obtained, based on the tail loading of the hedging error distribution. Risk management strategies reducing risk related to the hedging error are also presented. A detailed numerical analysis is performed for a point-to-point EIA.

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.

Description: In this paper we give new general criteria for the weak convergence of one-dimensional distributions of generalized risk processes and describe the class of possible limit laws under an infinite growth of stochastic portfolio size and stochastic intensity of insurance payment.

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: In order for actuaries to play a valuable role in the realm of enterprise risk management ERM, they must provide value-added advice and quantitative analyses. In this paper, the authors use stochastic simulation technology to present a risk metric for defined benefit pension plans that provides improved measures of the plan’s solvency and provides a tool for pension plan managers to determine the value of risk mitigation activities.

Description: This paper is Part 1 of a two-part submission. Part 2, “An Alternative Approach to Capital Allocation,” discusses using risk-replicating techniques that directly calculate the cost of capital. Such techniques can be used as a substitute for capital allocation. This paper expands upon current capital analysis by introducing a practical approach that considers the objectives of all stakeholders of an insurance company in setting appropriate capital targets.

Description: This paper analyzes the optimal retention level with a portfolio of insurance risks, and premiums invested in risk-free and risky assets. Optimality is defined here as maximizing expected utility of terminal payout.