Individual RBNS Loss Reserving in Discrete Time Model

In this paper, we investigate the RBNS reserving problem in a discrete time model. The individual RBNS reserving is evaluated with the unknown quantities in the RBNS reserve replaced by their estimates. The parameters related to the settlement delay are estimated using the method of maximum likelihood and the weak convergence of the estimates are studied. The conditional means in the RBNS reserve are estimated by the Watson-Nadaraya estimate. Moreover, the weak convergence of the aggregate RBNS reserving computed by the chain ladder algorithm are also studied. Simulation studies in finite sample case show that the individual method has smaller MSE compared to the the aggregate method.