The Research On Commercial Bank’s CPM Based On Data Mining

Customer-focused customer relationship management (CRM) of commercial bank is currently one of the most popular research in commercial bank, successful customer relationship management can bring super profit to the bank. CRM, enterprise supply chain management and enterprise resource planning constitute the basic framework of enterprise informatization. The core of CRM is to manage customers who are the important strategic resources intensively by modern information technology and combine the information in CRM systems with corporate actual business processes. Then the corporate can achieve internal customer information resource sharing, continuously improve customer value, and bring super profit to the enterprise ultimately.CRM system which is based on data mining can give an accurate classification to customers by analysing and mining customers’ information. Data mining technology can track the customers’ consumption patterns and consumer tendencies, predict the profit that customers create. It also support commercial banks decision-making. As a consequence, how to effectively use data mining technology is the key to CRM of commercial banks. Therefore, this article takes CRM which based on data mining as the research object, especially the application of data mining to customer classification.Firstly, this thesis discusses related literature research, analyses the customer relationship management definition, connotation and core ideas, as well as the significance of commercial banks’ customer relationship management. Secondly, this article describes the definition of data mining and data mining process, which focuses on neural networks and decision tree technology of data mining. Finally, it applies the data mining technology to CRM of commercial bank and improves the customers classification by using neural networks and decision tree approach.The main content of this paper is the application of data mining to customer relationship management, including the establishing of the commercial banks’CRM systems based on data mining and the customer classification model based on decision tree approach by comparing the two methods of data mining and combing the characteristics of commercial banks. Then according to the implementation of customer classification model, this article evaluates the results of this model and finally divides the housing loan clients into five categories considering the results.