Decision making method for intelligent assistant investment advisory

Abstract

The invention discloses a decision making method for intelligent assistant investment advisory, which relates to the technical field of data processing. The method comprises the following steps: the portrait of a user is firstly built, wherein the user portrait comprises user basic information, user financial information, user investment information, user preference information and user industry information; an evaluation data set is extracted from sample data of the user basic information, the user financial information, the user investment information, the user preference information and theuser industry information; according to the evaluation data set and based on a collaborative filtering recommendation algorithm, a recommended product is provided for the user; and then, through an Internet worm mode, text information, picture information and video information are acquired, and based on natural language processing and an image recognition technology, a recommended product and advice are customized and pushed for the user, and the investment decision making is assisted for the user. Precision marketing and personalized service for the user can be realized, and the method has the advantages of low threshold, low cost, wide investment, easy operation, high transparency and personalized customization.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to an intelligent method for assisting investment consultants in decision-making. Background technique [0002] With the rapid development of mobile Internet technology, artificial intelligence and other technologies, as well as the rise of Internet finance, the intelligent investment advisory system has also developed rapidly. Using big data analysis, financial quantitative models and intelligent algorithms, according to the different needs of investors such as risk tolerance level, expected return target, investment style preference, etc., a series of intelligent algorithms, investment portfolio optimization and other theoretical models are used to provide users with investment advice , and dynamically monitor market changes, provide regular or irregular adjustments to asset allocation, and at the same time perform automatic rebalancing operations according to certain rule...

AI Technical Summary

Problems solved by technology

[0002] With the rapid development of mobile Internet technology, artificial intelligence and other technologies, as well as the rise of Internet finance, the intelligent investment advisory system has also developed rapidly. Using big data analysis, financial quantitative models and intelligent algorithms, according to the different needs of investors such as risk tolerance level, expected return target, investment style preference, etc., a series of intelligent algorithms, investment portfolio optimization and other theoretical models are used to provide users with investment advice , and dynamically monitor market changes, provide regular or irregular adjustments to asset allocation, and at the same time perform automatic rebalancing operations according to certain rules to improve the return on asset portfolios; however, robo-advisors lack industry standards and rules, and many are just to cater to Recommend products based on customer needs, lack of judgment on the market itself, and cannot help investors avoid risks

Due to the lack of supervision and risk control, the product content and operation methods are not transparent, and the rights and interests of customers cannot be protected in the event of losses