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