An empirical study for ranking insurance firms using a hybrid of data envelopment analysis and neural network

One of the primary concerns with data envelopment analysis arises when the number of inputs and outputs increases. In such a case, required computations will become time consuming and there is a concern on developing some hybrid methods to increase the capability of this method. In this paper, a combination of data envelopment analysis and multi-layer neural network is proposed, in a case study, for predicting the performance of Alborz insurance subsidiaries in large cities in Automobile insurance firms. This research can be used in the future databases for performance prediction. On the other side, these results can aid Alborz insurance in its future investments as well as the performance index usage.