Patterns and changing trends among several excess-type layers on the same business tend to be closely related. The changes in trend often occur at the same time in each layer. Therefore a good model for the changing trends in the ground-up data will often be a good model for the various layers. As might be expected, after adjusting for the trends, the corresponding values in each layer are still generally correlated. These relationships among layers should be taken into account when reserving or pricing excess layers.
We describe a framework within which such relationships can be explicitly incorporated and taken account of when reserving or pricing several excess layers. This framework allows for reserving and pricing for multiple layers with changes in trends in the same periods, correlations between layers, and possibly equal trends or trend changes across layers.
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