Artificial Neural Networks in insurance loss reserving

Abstract

In this paper we analyse insurance data using Artificial Neural Networks (ANN)[1]. In particular, we use ANN for the problem of Loss Reserving. Loss reserving is the practice of estimating the future payments for the claims which have occurred on an insurance portfolio. A difficulty in forecasting future payments is that the time series of payments often depends on influences that are not observable in the historical data. For example, claims cost inflation may depend on future events such as legislative change and changes in judicial attitudes. Because of this, it is often necessary to supplement ANNs with separate forecasts which account for the expected changes in the future claims environment.