Application On The Techniques Of Data Warehouse And Data Mining In CRM Of The Bank

With the development of the banking business fast and increment of the service means rapidly, the competition between banks becomes more and more vigorous. Banking is a kind of special trade providing various financial products and services for customers. Therefore the customer is a very important resource for the bank. The value of customer is a direction to constitute a foundation and the future development of the bank. So to grow the customer's trustworthiness is a final target for setting up high-quality brand, promoting business development and increasing bank synthesizing competition ability. How to establish a set of complete system for processing customer relationship management (CRM) system becomes the focus for the modern banking world.Combining the evaluation of the client manager in one bank of Suzhou, this thesis integrates banking business data and establishes a private customer data warehouse. Then it constructs a small CRM experimental system and analyzes the private customer data of the bank on the techniques of data warehouse and data mining. It provides a platform for the analysis of customer data. And the system helps the bank's top managers and client managers to provide support decision-making function. It helps them to identify potential rules from millions of customers and mining high quality customer. Then the banker can make quality services to these customers. These customers will be gradually upgrading to be the VIP clients of the bank. And it can help the bank obtain more benefits.The thesis elaborates network architecture, system architecture and function architecture on the private CRM system in bank. It shows the detailed design of the data warehouse in the private CRM system. It also analyzes customer, account information, and performance evaluation, etc. By using decision tree algorithm, it attempts to make data mining on the training data. In the end, it generates the decision tree, classification rules and mining the high-quality of bank customers in the financial.