Abstract- Business intelligence (BI) technologies provide historical, current, and predictive views of business operations. Data mining is the core BI. This study uses data mining techniques to analyses historical data of banking system. These techniques including K-means method, fuzzy c-means clustering method, self-organizing map and expected maximization clustering algorithm are used to choose the best clustering algorithm to segment customers into groups. Then the Dominance-Based Rough Set Approach is applied to provide a set of rules to classify customer in bank system. The induced rules can provide recommendations of behaviors that increase the risk in financial processes. Keywords: K-means, Fuzzy c-mea