Table of Contents
Risks, Volume 6, Issue 2 (June 2018)
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Cover Story (view full-size image) We have designed a stochastic simulation machine that allows the user to generate a synthetic [...] Read more. We have designed a stochastic simulation machine that allows the user to generate a synthetic insurance portfolio of individual claims histories. This simulation machine is based on neural networks to incorporate individual claims feature information and is calibrated using real non-life insurance data. The simulated individual claims histories enable the user to back-test classical aggregate claims reserving methods—such as the chain-ladder method—as well as to develop new claims reserving methods which are based on individual claims histories. This simulation machine may provide a common ground and publicly available (synthetic) data for research in the field of claims reserving. View this paper.