Forecasting in an Extended Chain-Ladder-Type Model

Reserving in general insurance is often done using chain‐ladder‐type methods. We propose a method aimed at situations where there is a sudden change in the economic environment affecting the policies for all accident years in the reserving triangle. It is shown that methods for forecasting nonstationary time series are helpful. We illustrate the method using data published in Barnett and Zehnwirth (2000, pp. 245–321). These data illustrate features we also found in data from the general insurer RSA during the recent credit crunch.