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This paper introduces yet another stochastic model replicating chain-ladderestimates and furthermore considers extensions that add flexibility to themodeling. In its simplest form, the proposed model replicates thechain-ladder's development factors using a GLM model with averaged hazard ratesrunning in reversed development time as response. This is in contrast to theexisting reserving literature within the GLM framework where claim amounts aremodeled as response. Modeling the averaged hazard rate corresponds to modelingthe claim development and is arguably closer to the actual chain-ladderalgorithm. Furthermore, since exposure does not need to be modeled, the modelonly has half the number of parameters compared to when modeling the claimamounts. This lesser complexity can be used to easily introduce modelextensions that may better fit the data. We provide a new R-package,$\texttt{clmplus}$, where the models are implemented and can be fed withrun-off triangles. We conduct an empirical study on 30 publicly availablerun-off triangles making a case for the benefit of having $\texttt{clmplus}$ inthe actuary's toolbox.

Replicating and extending chain-ladder via an age-period-cohort structure on the claim development in a run-off triangle