Integrating Data Mining and Knowledge Management to Improve Customer Relationship Management in Banking Industry (Case Study of Caspian Credit Institution)

Banks and financial - credit institutions by customer relationship management database analysis can manage to identify customers and allocate resources to profitable customers in a better manner. This study aims to find an index for customers, using customer characteristics to identify significant profitable customers of banking system. In this way we will be able to provide them with more adequate facilities. To do so, mix method of fuzzy clustering and imperialist competitive algorithm has been applied to accomplish customer data clustering; then Fuzzy C-Means and criteria of sum of intra – cluster distances were used to evaluate the method. Results display minimum and maximum as 39.270153 and 53.100917 respectively which at least are 6000 units less than the compared method. This indicates advantage of the suggested method compare to the other.