At this presentation we will introduce stochastic loss reserving for General Insurance based on the Gaussian distribution. Basic properties of the Gaussian distribution make its application to loss reserving beneficial. These properties allow for flexible data handling and generate various predictions. A set-up of the parameters will be presented that makes it possible to model past and future loss periods integrally. Based on this parameter set-up two specific loss reserving models will be discussed. First, a model for the combined analysis of paid and incurred runoff tables. Second, a model for the analysis of multiple, possibly dependent, runoff tables within a portfolio. The results of the application of these methods to an exemplary portfolio will be discussed.
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