The synthetic autoregressive model for the insurance claims payment data: modeling and future prediction

Abstract

Time series play a vital role in predicting different types of claims payment applications. The future values of the expected claims are very important for the insurance companies for avoiding the big losses under uncertainty which may be produced from future claims. In this work, we define a new size-of-loss synthetic autoregressive model for the left skewed insurance claims datasets. The synthetic autoregressive model model is assessed due to some simulations experiments. The optimal parameter is also artificially determined. The insurance claims data is modeled using the synthetic autoregressive model.