Description: This SOA report provides an overview and analysis of the mortality models, theories and trends contained in the papers presented at the past four international Living to 100 symposia.

Description: This paper investigates techniques for the assessment of model error in the context of insurance risk analysis.

Description: This report studies the various benchmarks for analyzing the option-adjusted spreads of the major fixed income asset classes of life insurance companies. In addition, this report analyzes the historical benchmark performance against default rates for the asset class being benchmarked.

Description: Authored by a MIB Solutions team of Tom Rhodes, Stuart Klugman, Marianne Purushotham and Stacy Gill, the report summarizes the results of a study on the application and adoption of credibility theory within the life insurance and annuity industry. In addition to the report, numerical examples related to the application of credibility to company mortality and lapse data are provided in the four Excel files. This excel spreadsheet is a numerical example relating to the application of Credibility for mortality. Please see the SOA website research section for the complete report on Credibility Theory Practices.

Description: Authored by a MIB Solutions team of Tom Rhodes, Stuart Klugman, Marianne Purushotham and Stacy Gill, the report summarizes the results of a study on the application and adoption of credibility theory within the life insurance and annuity industry. In addition to the report, numerical examples related to the application of credibility to company mortality and lapse data are provided in the four Excel files. This excel spreadsheet is a numerical example relating to the application of Credibility for mortality - Limited Fluctuation Method. Please see the SOA website research section for the full report on Credibity Theory Practices.

Description: This research project examines operational risk management practices and assess the viability of ORM as a formal discipline. A key goal of this initiative has been to determine whether the management of operational risk is feasible, and, if so, what issues need to be addressed in order to effectively implement ORM within a broader ERM context.

Description: The Required Minimum Distribution [RMD] Working Group of the SOA Taxation Section has completed research identifying considerations for actuaries and annuity insurers in determing the actuarial present value of additional benefits for computing the RMD under a deferred annuity contract. This is the Appendix I spreadsheet for determining the Actuarial Present Value of an annuitization bonus. Please see the SOA website research for the full report and other associated spreadsheets.

Description: The Stochastic Volatility, SV, model is used for capturing the empirical properties of financial time series. This paper overviews those properties and compares the SV model with the heavy-tailed error distribution Student t-distribution and the SV model with the normal error distribution. The Simulated Maximum Likelihood, SML, method is applied to estimate the parameters and the latent volatility.

Description: This paper discusses mathematical modeling and pricing of 'Stable Value' financial products offered to pension plan providers. These products target a risk-averse population of investors who have a significant preference for a stability of returns. The paper offers a quantitative methodology that reflects a decision making process applicable in the situation of incomplete markets where traditional arbitrage free arguments are invalid.

Description: There is a large literature on claims reserving. However most of the stochastic models are too complex and end up being a black box for practitioners. They also tend to be over parameterized, which has the effect that they tend to model historical observations very accurately, but they do not necessarily perform well when predicting future claims. This paper applies a Bayesian method that was developed for forecasting very short series with stable [seasonal] patterns. It is constructed on basic Bayesian concepts and leads to very simple prediction formulas. It is then compared with several other methods as to their predictive effectiveness. In so doing, it departs from the traditional ‘triangle-shaped’ framework for development data.