Intelligent Financial Decision Support System Based on RPA Financial Robot and Artificial Intelligence

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Publicat a:The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings (2024)
Autor principal: Tang, Weiyun
Altres autors: Cao, Hongtao, Ye, Shengfan, Lu, Yang, Chen, Fei
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The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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LEADER 00000nab a2200000uu 4500
001 3156623461
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024 7 |a 10.1109/PEEEC63877.2024.00175  |2 doi 
035 |a 3156623461 
045 2 |b d20240101  |b d20241231 
084 |a 228229  |2 nlm 
100 1 |a Tang, Weiyun  |u Shanghai Urban Construction Vocational College,Shanghai,China,201415 
245 1 |a Intelligent Financial Decision Support System Based on RPA Financial Robot and Artificial Intelligence 
260 |b The Institute of Electrical and Electronics Engineers, Inc. (IEEE)  |c 2024 
513 |a Conference Proceedings 
520 3 |a Conference Title: 2024 International Conference on Power, Electrical Engineering, Electronics and Control (PEEEC)Conference Start Date: 2024, Aug. 14 Conference End Date: 2024, Aug. 16 Conference Location: Athens, GreeceThis paper studies the construction and application of intelligent financial decision support system (DSS) which combines RPA (Robotic Process Automation) financial robot and artificial intelligence (AI) technology. This paper expounds the functional module design of intelligent financial DSS in detail, including financial data automatic processing, intelligent data analysis and prediction, risk early warning and management, decision support and system management module. Through the system architecture design, the system is divided into data layer, business logic layer and presentation layer to ensure the stability and efficiency of the system. In the process of system implementation, advanced technologies such as Windows 10 operating system, Visual Studio Code development environment, Python back-end development language, Flask Web framework and PostgreSQL database are adopted. RPA financial robot realizes the automatic collection and arrangement of financial data through UiPath tools, while AI technology uses TensorFlow and other libraries for in-depth analysis and prediction of data. The system testing stage includes functional testing and performance testing, which verifies the stability and reliability of the system. The research results show that the combination of RPA financial robot and AI technology can provide enterprises with more efficient and accurate financial management and decision support services. Through the functions of automatic processing of financial data, intelligent analysis and prediction, risk early warning and decision support, the system has significantly improved the financial management level and decision efficiency of enterprises. The research in this paper not only enriches the application theory of RPA and AI in the financial field, but also provides useful reference for the financial management practice of enterprises. 
653 |a Design analysis 
653 |a Data base management systems 
653 |a Financial management 
653 |a Operating systems 
653 |a Data analysis 
653 |a Decision support systems 
653 |a Artificial intelligence 
653 |a Support services 
653 |a Early warning systems 
653 |a Windows (computer programs) 
653 |a Functional testing 
653 |a Robots 
653 |a Python 
653 |a Stability 
653 |a Modules 
653 |a Visual programming languages 
653 |a Electrical engineering 
653 |a Economic 
700 1 |a Cao, Hongtao  |u Shanghai Urban Construction Vocational College,Shanghai,China,201415 
700 1 |a Ye, Shengfan  |u Shanghai Wu Yuan Rord Kindergarten,Shanghai,China,200031 
700 1 |a Lu, Yang  |u Shanghai Communications Polytechnic,Shanghai,China,200431 
700 1 |a Chen, Fei  |u Shanghai Urban Construction Vocational College,Shanghai,China,201415 
773 0 |t The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings  |g (2024) 
786 0 |d ProQuest  |t Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3156623461/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch