Collective Reserving using Individual Claims Data
Scandinavian Actuarial Journal 2021 https://www.tandfonline.com/doi/full/10.1080/03461238.2021.1921836
Posted: 19 May 2020 Last revised: 11 May 2021
Date Written: April 22, 2020
The aim of this paper is to operationalize claims reserving based on general insurance individual claims data. We design a modeling architecture that is based on six different neural networks. Each network is a separate module that serves a certain modeling purpose. We apply our architecture to individual claims data and predict their settlement processes on a monthly time grid. A proof of concept is provided by benchmarking the resulting claims reserves with the ones received from the classical chain-ladder method which uses much coarser (aggregated) data.
Keywords: claims reserving, general insurance, individual claims data, micro-level reserving, neural networks, IBNR claims, RBNS claims, chain-ladder method, over-dispersed Poisson model
JEL Classification: G22, C22, C25, C45, C51, C53
Suggested Citation: Suggested Citation