Development Strategy of Securities Investment Industry under the Background of Artificial Intelligence

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Abstract

The application of artificial intelligence technology in the field of securities investment is becoming the next hotspot of Internet finance. The purpose of this paper is to study the development strategy of securities investment industry based on the background of artificial intelligence. First of all, after understanding that there will be revolutionary changes in the field of securities investment, this paper studies three strategies for the development of securities investment industry: establishing the registration and filing system of securities investment intelligent agent, establishing the source code notarization system of securities investment intelligent agent and constructing the regulatory framework suitable for inclusive financial services. The research method of empirical analysis is adopted to obtain customer data through more than two different channels. The experimental results show that the research method of empirical analysis is adopted. According to the feedback of 108 companies' questionnaires, 55 companies have indicated that they have used artificial intelligence technology in investment consulting business, accounting for 50.93%. Of the remaining 53 companies that did not use AI technology, 28 said they had plans to launch related businesses. At present, artificial intelligence is widely used in the securities industry for customer portrait and account diagnosis, information service, and robot customer service. Its purpose is mainly to reduce customer service costs and expand the coverage of customer service. At the same time, it has begun to gradually layout investment tools to try to improve customer investment difficulties and improve customer service level.

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APA

Hu, G. R., & Liu, H. (2020). Development Strategy of Securities Investment Industry under the Background of Artificial Intelligence. In Journal of Physics: Conference Series (Vol. 1533). Institute of Physics Publishing. https://doi.org/10.1088/1742-6596/1533/3/032057

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