The Solvency II directive asks insurance companies to derive their solvency capital requirement from the full loss distribution over the coming year. While this is in general computationally infeasible in the life insurance business, an application of the Least-Squares Monte Carlo (LSMC) method...

The least-squares Monte Carlo method has proved to be a suitable approximation technique for the calculation of a life insurer's solvency capital requirements. We suggest to enhance it by the use of a neural network based approach to construct the proxy function that models the insurer's loss...

Under the Solvency II regime, life insurance companies are asked to derive their solvency capital requirements from the full loss distributions over the coming year. Since the industry is currently far from being endowed with sufficient computational capacities to fully simulate these...

In this article, we test a linear Gaussian space model and the Kalman filter ARMA(2,4) model to estimate logarithmic monthly returns of UK general and life insurance companies. This fact motivates us to use state space model that will reveal to us the final one – step ahead values of the...

This paper assesses the risk of a mass lapse event in life insurance. The rarity of the event and the complexity of policyholder behavior, make the risk assessment of such a scenario difficult. Using a simulation study, we evaluate how different estimation methods can assess the scenario when...

A variable annuity is a popular life insurance product that comes with financial guarantees. Using Monte Carlo simulation to value a large variable annuity portfolio is extremely time-consuming. Metamodeling approaches have been proposed in the literature to speed up the valuation process. In...