Digital Banking Financial Business Innovation Research and Index Analysis Focused on Collaborative Filtering Recommendation

Abstract

Abstract Collaborative filtering recommendation is a technology that has rapidly appeared in information filtering and information systems in recent years. At present, it is widely used in commercial activities and has achieved very satisfactory results. The research of this article is based on the basic operating system method and the suggestion of the automatic recognition system (collaborative filtering recommendation), that is, customers purchase fixed deposits. Based on behavioral theory and new institutional arrangements, this article explores the influence and effect of the external development of external digital banks on the digital behavior of traditional commercial banks, and concludes that the development of digital banks has a positive impact on bank operations and product differentiation innovation. The economic pressure brought about by the development of digital banks first promoted the bank's product innovation, while the social pressure mechanism affected the bank's digital innovation in management and production. Social pressure has an impact on bank management and digital innovation. The improvement of financial business transparency and the diversification of financial products have also increased competition in the financial market. Accurately predicting customer preferences is crucial for financial business companies. The development of an effective classification model will not only help increase company profits, but also effectively reduce costs. In the user-based collaborative filtering system research algorithm, by establishing a time-series-based consumer network, determine the targeted influence relationship between users to find the neighbor set more accurately, and establish a time-series-based collaborative filtering algorithm to improve recommendation the accuracy of the algorithm.