Applying Mahalanobis –Tagouchi System in Detection of High Risk Customers –A case-based study in an Insurance Company

The organizations use all appropriate tools to improve their service to the customers. Thedetection of especial customers and the forecast of their behavior undoubtedly can play animportant role in improvement of service. In this paper, a new statistical method called theMahalanobis Taguchi system has been used for this purpose. This method is used for theanalysis of real data of an insurance company and five big cities in Iran are considered. Thereare seven initial factors which is important in the occurrence of accidents and losses. Thesefactors are reduced to four. Customerʹs behavior is analyzed case by case by the Mahalanobis–distance concept. In fact with using this new method, demand of customers case by case wasanalyzed and it is an important outcome in analyzing behavior of customers. Devising ways toprevent the accidents and damages will need the recognition of Customerʹs behavior. The neuralnetworks method is used to recognize the high–risk customers, and the results of this method arecompared with the results of Mahalanobis–Taguchi system. The results show that Mahalanobis–Taguchi system with its abnormality scale has a great capability in recognizing high-riskcustomer. To recognize the customer by the Mahalanobis Taguchi system is more accurate incomparison with the neural networks method.