Establishment and Implementation of Securities Company Customer Classification Model Based on Clustering Analysis and PCA

In the paper, advanced data mining technology is applied to the analysis of customers' historical exchange data in the customer classification model of securities exchange. The accuracy and effectiveness of the results is remarkably improved. The process involves using data warehouse to achieve the storage of massive customer transaction data, the construction of the fundamental indicator system, the selection of the indicators using PCA and the construction of the customer classification model using K-means clustering algorithm. The application of these technologies significantly improves the accuracy and effectiveness the customer classification indicators, enabling the results closer to the mettle of the customers and basically solving the key points and difficulties in the suitability management.