hirem

A hierarchical reserving model for reported non-life insurance claims. Traditional non-life reserving models largely neglect the vast amount of information collected over the lifetime of a claim. This information includes covariates describing the policy, claim cause as well as the detailed history collected during a claim’s development over time. We present the hierarchical reserving model as a modular framework for integrating a claim’s history and claim-specific covariates into the development process. Hierarchical reserving models decompose the joint likelihood of the development process over time. Moreover, they are tailored to the portfolio at hand by adding a layer to the model for each of the events registered during the development of a claim (e.g. settlement, payment). Layers are modelled with statistical learning (e.g. generalized linear models) or machine learning methods (e.g. gradient boosting machines) and use claim-specific covariates. As a result of its flexibility, this framework incorporates many existing reserving models, ranging from aggregate models designed for run-off triangles to individual models using claim-specific covariates. This connection allows us to develop a data-driven strategy for choosing between aggregate and individual reserving; an important decision for reserving practitioners. We illustrate our method with a case study on a real insurance data set and deduce new insights in the covariates driving the development of claims. Moreover, we evaluate the method’s performance on a large number of simulated portfolios representing several realistic development scenarios and demonstrate the flexibility and robustness of the hierarchical reserving model.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element


References in zbMATH (referenced in 1 article , 1 standard article )

Showing result 1 of 1.
Sorted by year (citations)

  1. Crevecoeur, Jonas; Robben, Jens; Antonio, Katrien: A hierarchical reserving model for reported non-life insurance claims (2022)