Core Technology Optimization of Intelligent Financial Technology Based on Collaborative Filtering Algorithm in Big Data Environment

Abstract

With the improvement of people’s economic level, people pay more attention to financial investment. At present, the financial industry provides customers with a variety of investment services, but it has always been unable to provide targeted services for customers. Based on this, this paper studies the optimization of intelligent financial technology core technology based on collaborative filtering algorithm in the big data environment. On the basis of a simple analysis of the application of financial core technology and the research status of collaborative filtering algorithm, this paper constructs an application model of intelligent financial collaborative filtering algorithm. In view of the shortcomings of collaborative filtering algorithm, it uses user-based clustering algorithm to improve the collaborative filtering algorithm. According to the frequency of customers’ access to financial products, the attention model is established and simulated. The results show that the collaborative filtering optimization algorithm used in this paper can reduce the absolute error of recommendation and improve the accuracy.