The lasso is applied in an attempt to automate the loss reserving problem. The regression form contained within the lasso is a GLM, and so that the model has all the versatility of that type of model, but the model selection is automated and the parameter coefficients for selected terms will not...

The iterated Bornhuetter-Ferguson loss reserving method generates an infinite sequence of reserve formulas, with the chain ladder and Bornhuetter-Ferguson formulas at opposite extremes. The sequence also contains the Benktander-Hovinen formula. Although the literature contains parametric...

This paper is concerned with the estimation of forecast error, particularly in relation to insurance loss reserving. Forecast error is generally regarded as consisting of three components, namely parameter, process and model errors. The first two of these components, and their estimation, are...

The paper is concerned with loss reserving at the individual claim level (also referred to as micro-reserving or granular reserving) in the context of workers compensation, or similar income replacement insurance. The individual claim reserve is constructed on the basis of detailed information,...

Stochastic loss reserving with dependence has received increased attention in the last decade. A number of parametric multivariate approaches have been developed to capture dependence between lines of business within an insurer's portfolio. Motivated by the richness of the Tweedie family of...