Description: These are Charts 1-4 from a presentation entitled 'Stochastic Immunization' From a session at a meeting of the Society of Actuaries held in San Diego, CA, June 22-23, 2000

Description: Using the recent West Africa Ebola outbreak as an example, the authors discuss several modeling approaches that can be useful for estimating pandemic risk.

Description: The next evolution of actuarial systems in the U.S. will likely be a move toward a single system solution. This article defines a single system solution and illustrates how models can be shared across actuarial functions, the potential benefits of a single system solution, and describes potential mitigation strategies to address typical actuarial concerns.

Description: With the adoption of the C-3 Phase 2 Project of the American Academy of Actuaries, it is now required that stochastic scenarios be developed for establishing reserves for variable annuities. This project has led to the idea of Principle-Based Reserving PBR where many of the same techniques will be used to set life insurance reserves. This article describes the choice of a Random Number Generator RNG to develop the random scenarios.

Description: 2003 Valuation Actuary Symposium, San Diego, CA. In this Teaching Session the instructor discussed the importance of making sure the correct inferences were drawn from stochastic testing exercises. Topics included: 1. Applying the assumption of a normal distribution. 2. Drawing inferences about, and creating confidence intervals around, a population mean. 3. Drawing inferences about, and creating confidence intervals around, tail percentiles. 4. Certifying anticipated mortality under XXX in a mathematically concise way.

Description: 2003 Valuation Actuary Symposium, San Diego, CA. This panel discussion provided an overview of the current risk-based capital RBC requirements for life insurers as well as insight into topical issues and potential changes to RBC. Discussion topics included: 1. Recap of RBC law and RBC calculation rules. 2. Modeling potential impact of alternative actions. 3. The tax impact of the factors. 4. Stochastic capital requirements for variable products. 5. The role of reinsurance and offshore solutions.

Description: Quantitative operational risk assessment is essentially based on stochastic scenario modeling of operational loss sequences. Given the lack of reliable historical data in most cases, mathematical methods should meet even stronger requirements in terms of results received and include specific features, namely: rare event analysis, uncertainty analysis and human factor analysis, etc. In this paper, the analytical-statistical simulation approach ASSA is considered as the most flexible approach to stochastic scenario loss sequence modeling and compared with Markov chain, fault/event tree and Monte Carlo, in terms of scenario loss sequence model adequacy and calculation cost. Probabilistic risk analysis software PRAISE and some applications are given. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.

Description: The Financial Reporting and Product Development Sections, along with the Committee on Life Insurance Research are pleased to make the following report available. Prepared by Bruce Rosner of Ernst & Young, the report summarizes the findings of a stochastic modeling efficiency study. With the help of twelve life insurance and annuity companies, the study tested six techniques for reducing the number of model points or scenarios required to achieve a given level of precision in stochastic actuarial modeling.

Description: This session from the 1995 SOA Boston Meeting discusses constructing and using a comprehensive, credible risk management system with a concentration on C-3 risk. It also covers an example of option adjusted spread analysis for a single premium deferred annuity SPDA. From the Record of the Society of Actuaries, Vol. 21, No. 4b.

Description: Panelists at this session of the SOA 1998 Maui II Spring Meeting present methods for scenario generation and establishing stochasitc models for pension plans.