Financial corporation and banks are sort of organization that due to specialty of their work, are very needy to customer management process ; and data mining is one of the best available tools for them to asses definition and behavior forecast of their customers.
Data mining is improving very fast and due to presence of vide range of data using computer is essential. Nets & powerful algorithms are used to emplace of manual analysis to derive knowledge & information from data.
In this paper: “Mellat Bank” and its information bank of different division has been evaluated after data extraction from information bank and noise distortion , k means algorithm and fuzzy - k - means algorithm standard test of cluster's compression were used for customer clustering in groups. Determination of optimum number of clusters is done by applying cluster quality assay function. Afterward was used to determine the quality of gained clusters. Then the value of each cluster was determined through FRM model. At the end of project for clusters analysis and define appropriate strategy for each cluster; the pyramid of customer value was used.