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

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Detaylı Bibliyografya
Yayımlandı:	The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings (2024)
Yazar:	Tang, Weiyun
Diğer Yazarlar:	Cao, Hongtao, Ye, Shengfan, Lu, Yang, Chen, Fei
Baskı/Yayın Bilgisi:	The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Konular:	Design analysis Data base management systems Financial management Operating systems Data analysis Decision support systems Artificial intelligence Support services Early warning systems Windows (computer programs) Functional testing Robots Python Stability Modules Visual programming languages Electrical engineering Economic
Online Erişim:	Citation/Abstract
Etiketler:	Etiketle Etiket eklenmemiş, İlk siz ekleyin!

Diğer Bilgiler
Özet:	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.
DOI:	10.1109/PEEEC63877.2024.00175
Kaynak:	Science Database