Research on the Construction of Intelligent Expert System

The Core Platform of Big Data Governance and Wealth Management in the Digital Transformation of Securities Companies

DOI

10.2991/assehr.k.210915.040How to use a DOI?

Keywords

Financial big data, FinTech, Wealth management, Intelligent expert system

Abstract

In recent years, how to carry out the digital transformation of securities companies is the core research issue of both academia and industry. Starting with the basic problems such as financial big data governance and the related system platform construction, this paper gradually clarifies and discusses the misunderstanding, development positioning, and design points that exist in the process of FinTech construction by securities companies. On this basis, this paper starts from the wealth management business of securities companies and systematically proposes methods and processes for artificial intelligence technology to be embedded in related businesses in terms of the needs of the company and customers, product design, and implementation architecture, etc., to realize the FinTech-enabled digital transformation of securities companies. Finally, based on the perspective of top-level design and data-driven, this paper defines the connotation of the intelligent expert system. From key nodes such as model design, technology application, and risk control, we also propose policies to promote the development of digital management of securities companies. In addition, this paper also looks forward to the future development of the intelligent expert system.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Huimin Li
PY  - 2021
DA  - 2021/09/16
TI  - Research on the Construction of Intelligent Expert System
BT  - Proceedings of the 2021 International Conference on Modern Management and Education Research (MMER 2021)
PB  - Atlantis Press
SP  - 176
EP  - 182
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.210915.040
DO  - 10.2991/assehr.k.210915.040
ID  - Li2021
ER  -