Insurance Modeling and Stochastic Cash Flow Scenario Testing:

With the proposed RBC requirements for variable annuities with guarantees (so called C3 Phase II) requiring stochastic testing, there should be a lot of interest in the approaches to reducing the number of runs. This article provides strategies to reduce number of runs in stochastic insurance modeling as well as cash flow testing when the interest scenarios are stochastic. Three interest rate sampling algorithms and a computer software program SALMS that performs sampling are introduced. Introduction One of the greatest challenges of stochastic insurance modeling for large insurance businesses is the run-time. Using a complete stochastic asset/liability model to analyze a large block of business is often too time consuming to be practical. Efficient stochastic modeling can be achieved by applying effective interest rate sampling algorithms that are presented in this article. The algorithms were tested on a simplified asset/liability model as well as a commercial asset/liability model using assets and liabilities of Aetna Insurance Company of America (AICA) in 1999. Another methodology using the New York 7 scenarios is proposed and could become an enhancement to the Model Regulation on cash flow testing, thus requiring all companies to do stochastic cash flow testing in a uniform, non-onerous manner. A beta version PC software (SALMS) designed to perform interest rate sampling algorithms in this article is available to modelers upon request.