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The Present and Future of Stock Market Information: Ubiquitous Data and Artificial Intelligence

Securities Times reporter Zhou Sha

With the rapid emergence of emerging technologies in recent years, artificial intelligence and big data have become topics that everyone pays close attention to and talks about. The financial industry is a digital-based trading industry. Artificial intelligence and big data are profoundly affecting the analysis and decision-making of the financial industry.

In order to discuss new development trends, Hang Seng Juyuan and Data Po jointly held a theme salon of "Application and Prospect of Intelligent Information" in Shenzhen on April 20, Hang Seng Ju Yuan, Securities Times Data Po, Hang Seng Yunji, and many securities firms. The heads of the Information Technology Department, Online Finance Department, and Product Department gathered to discuss the application, layout, and development of artificial intelligence in the securities field.

1

Application and development of artificial intelligence in investment consulting

Facing the massive data of markets, channels and users, how does artificial intelligence technology play a role in the field of securities investment and consultation? How to make data intelligence applicable in investment decisions.

Xu Hongjun, deputy general manager of Hang Seng Juyuan, pointed out that smart investment advisors are undoubtedly the most sought-after fintech outlet. Brokers are expecting that artificial intelligence technology can play a huge role in the field of securities investment advisory. In the initial stage, it also faced difficulties such as obvious individual characteristics of investor accounts, complex types, particularly large amount of data calculation, and poor accuracy analysis. Although various securities firms have tried one after another, so far they have not achieved much breakthrough. How to make artificial intelligence technology play a role in the field of securities investment and consultation, what is to be solved is to increase the openness of data in vertical fields, understand the scenarios in which artificial intelligence capabilities can be implemented and the corresponding process, and integrate AI into the decision-making process.

1.1

Application and development of artificial intelligence in stock market information

How to cut into stock market news from artificial intelligence? How to mine stock market data and information to satisfy investors' stock selection needs?

Luo Feng, the person in charge of Data Po pointed out that valuable data content in the market is relatively scarce, and there is no stock market data information production line for continuous mining and systematic production. Especially in the context of the strict regulation of the stock market, information produced from data can reduce subjective judgment risks. New information discovered by data robots can provide users with scarce external transaction value information and meet investors' stock selection needs.

DataBao has made some attempts in the development of intelligent information business. DataBao has written more than 3,000 manuscripts per month in robot writing, and its production covers common 13 types of stock market data. DataBao is also the first new media in China that embeds robot writing directly into WeChat. Click on the robot on the menu bar, and the articles that jump out are all manuscripts written by robots. At the same time, data treasure also develops data tools. Data treasure develops some common needs of stock market users into tools, such as stock popularity rankings, chip concentration inquiry, continuous capital inflow inquiry, etc., to make small programs to open up micro-signals. This is helpful to bring new information of transaction value to investors and meet the needs of investors in stock selection.

2

Application and development of intelligent question answering in the financial field

The rapid development of artificial intelligence has enabled the machine to simulate human functions to a large extent, and realize batch humanized and personalized services. In the online market that is full of competition for traffic and increasingly fierce competition, intelligent Q & A will become an important factor in deciding to communicate with customers and discover their financial needs.

Xu Fan, product manager of Hang Seng Juyuan Intelligent Xiaofan, mentioned that the design concept of intelligent question answering is to grasp the weakness of human nature, to be user-centered, to help users filter information, and to provide users with a one-stop solution to make intelligent question answering a financial Investment assistant.

Focusing on the field of securities brokers, investment-based intelligent question and answer, intelligent robots, and interactive components, for users, for different questions, intelligent question and answer products will output information in the form of different components to solve information asymmetry or acquisition. The problem of inaccurate information; at the same time, it helps C-end users to continue to be familiar with and understand the relevant logic of the capital market, investment target products and investment concepts.

3

How to make data-driven decisions more refined

The main line of the entire financial business front-end scenario is composed of "understand customers-match customers and products-personalized services-iterative optimization". The refined operation with big data as the core has gradually become the consensus in the industry. Learn to use data analysis to figure out where users come from, what they are interested in, how to stimulate users, make decisions based on data, and provide personalized services for different customers. .

Hang Xiao Yunji product manager Chen Xiao pointed out: The basis of precise operation is the cleaning of big data and the establishment of a user portrait system. Based on the customer's natural attributes, assets, transactions, user behavior, and other various data sources, analyze the customer's investment behavior and the investment needs behind it, and label the characteristics of brokerage customers for business scenarios such as diagnosis, operation, assistance, and recommendation Use, to form the basis of thousands of people and thousands of faces, to promote the development of online and offline business of securities firms.

4

How to build a scientific financial knowledge map

How to build a knowledge map in the entire field of finance, use the knowledge map based on association relationships to break through the limitations of existing relational databases, and make data play a greater value in the financial industry.

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