Big Data Mining Algorithm for Optimal Generation of Intelligent Financial Business Portfolio Investment Decision

In the current research process of artificial intelligence, cloud computing and other technologies, many useful derivative technologies have emerged, which have promoted the rapid development of the world economy and finance. Among them, intelligent services analyze and judge the surface and hidden needs of users, and actively use a safe and efficient technology to meet various needs of users. If people want to get the surface and hidden needs of users, they need to use data mining algorithms. Then the big data analysis algorithm was used to analyze and picture the user data searched by data mining. Big data is a new technology that can analyze massive data. At the same time, intelligent finance is also making rapid progress. Intelligent finance is an intelligent financial work mode formed by combining the traditional financial mode with Internet of Things, intelligent services and other technologies. The intelligence in this mode not only represents the individual optimization of a certain financial link or process, but also is a revolutionary new financial model. This paper is just to explore the application of big data mining analysis algorithm in intelligent financial business portfolio investment decision optimization, and propose to combine some algorithms of big data analysis and data mining with intelligent financial model, and carry out experimental analysis to determine that the integration of big data has improved the working efficiency of the original intelligent financial business portfolio investment decision model by about 35.3%. Although the current security and intelligent service theory in intelligent finance is still not perfect, the integration of big data can effectively make up for some of the shortcomings.