The Application Of Data Mining Technology In Commercial Bank Customer Relationship Management

At present,the impact of Internet finance on traditional banks,banks' services and products are becoming more and more transparent,and the gaps are shrinking.At the same time,the life cycle of products is also shortening,and traditional commercial banks are facing tremendous pressure.The focus of competition among banks is also changing.From product to customer competition,whoever seizes the customer will master the market and be able to stand firm in the increasingly fierce market.The needs of customers are also different due to different populations.Banks can not innovate products or services according to the diversified needs of customers in the long-term development,or stay in the traditional strategic thinking development mode,and will gradually be eliminated by the wave of modern development..In the information age,it is especially important to strengthen customer contact with customer information and transaction information.For the future development of banks,the ability to use big data to develop customer information and value is a major direction for their development in the future,which must depend on relevant technologies.Among them,data mining technology can solve this problem very well.This paper takes the application of data mining technology in bank customer relationship management as the main content of the research.1.Process the customer information of the bank.Firstly,we extract the information we want from the bank's various systems through ETL extraction technology.Secondly,based on the perspective of customer value,we construct a specific model based on the purpose of refining the customer's value and improving the product,service quality and measures of the commercial bank.Then,based on the daily consumption behavior of customers,they are clustered to different types.Afterwards,the transfer of customers is studied,and the probability of transfer is studied by Markov chain.Finally,the previous research Five links of customer consumption patterns and types have established idle loop control.2.Customer relationship management is very important for commercial banks.This study can improve this system.The customer's model was built in the research,and the data mining technology was used,which not only improved the accuracy,but also optimized the system performance and improved the bank's work efficiency.In addition,this paper designed and implemented the system.When introducing the system,the first discussion of its requirements,followed by a brief description of its overall design planning objectives,and then its framework structure was analyzed.Finally,the functions are implemented,and finally the function is successfully tested.