Analysis of Stochastic Reserving Models By Means of NAIC Claims Data

In the past two decades increasing computational power resulted in the development of more advanced claims reserving techniques, allowing the stochastic branch to overcome the deterministic methods, resulting in forecasts of enhanced quality. Hence, not only point estimates, but predictive distributions can be generated in order to forecast future claim amounts. The significant expansion in the variety of models requires the validation of these methods and the creation of supporting techniques for appropriate decision making. The present article compares and validates several existing and self-developed stochastic methods on actual data applying comparison measures in an algorithmic manner.