Estimation of future discretionary benefits in traditional life insurance

Abstract

In the context of traditional life insurance, the future discretionary benefits (F DB), which are a central item for Solvency II reporting, are generally calculated by computationally expensive Monte Carlo algorithms. We derive analytic formulas for lower and upper bounds for the F DB. This yields an estimation interval for the F DB, and the average of lower and upper bound is a simple estimator. These formulae are designed for real world applications, and we compare the results to publicly available reporting data.