Fuzzy Mathematical Solution’s of Customer Relationship Management Financial Sector for current Economic Era

摘要

Today, many businesses such as banks, insurance companies, and other service providers realize the importance of Customer Relationship Management (CRM) and its potential to help them acquire new customers retain existing ones and maximize their lifetime value. At this point, close relationship with customers will require a strong coordination between IT and marketing departments to provide a long-term retention of selected customers. Drastic changes in communication technology are changing the way that traditional banking is done in current economic era. It has been given new shape of traditional banking. The resulting changes will have a great impact on financial sector. Firstly on the reset up of a financial sector network according to the focus of the market, secondly on the design of new products and on the development and the use of alternative distribution channels and finally on the customers’ switching behavior [3, 7, 9, and 13]. In this paper, we are exploring issues that put in the fundamentals of CRM for franchise’s network optimization and discuss mathematical solution for that. Financial Institution’s management team could use the findings of this study, in order to determine specific component in designing financial services and products, which would add in customers’ satisfaction and reliability. The proposed approach could have significant implications for enlarging the duration of the relationship among customer and financial institution and for maximizing their franchise performance [6, 9, and 12]. There are different issues relating to the reorganization of financial industry are examined. Specifically the performance of a franchise network, the online service’s as an alternative distribution channel and the duration of the relationship among customers (individuals or enterprises) are the three interrelated parties. Fuzzy optimization techniques and generalized linear models are used in order to determine financial products and services which are offered to financial clients through traditional and Internet channels, forecasting customers’ attitudes (adoption or rejection) to the new products and the time horizon of their cooperation with their sector [1,4, and 7].