Design of Digital and Intelligent Financial Decision Support System Based on Artificial Intelligence

被引:3
|
作者
Jia, Tiejun [1 ]
Wang, Cheng [1 ]
Tian, Zhiqiang [1 ]
Wang, Bingyin [1 ]
Tian, Feng [1 ]
机构
[1] Shenhua Grp Zhungeer Energy Co Ltd, Ordos 017000, Inner Mongolia, Peoples R China
关键词
Artificial intelligence - Decision support systems - Finance - Surveys;
D O I
10.1155/2022/1962937
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The quality of financial decision-making is very important to the future development of an enterprise, but it is often affected by the completeness of useful information for decision-making and the subjective factors of decision makers, and is often unstable. With the development of computer technology, the financial decision support system came into being, which improved the quality of financial decision to some extent. However, although the existing financial decision support system has achieved dataization to a certain extent, it still faces problems such as artificial leadership, insufficient intelligence, and poor decision-making efficiency, and cannot fully meet the needs of decision-makers. The explosion of artificial intelligence technology in recent years has provided potential improvements to financial decision support systems. In this article, we conduct a detailed analysis of the deficiencies in the current financial decision support system, build the mechanism and implementation path of the financial decision support system under artificial intelligence, and design a digital and intelligent financial decision support system. At the same time, we apply the proposed financial decision support system to the financial practice of X enterprise. Through the questionnaire survey, it is found that through the comprehensive application of artificial intelligence technology, the new system has a higher degree of intelligence than the existing system, and its construction can effectively improve the timeliness and accuracy of financial decision-making, while reducing the cost of financial decision-making. It is conducive to promoting the integration of management accounting and financial accounting.
引用
收藏
页数:7
相关论文
共 50 条
  • [41] Clinical Decision Support by Artificial Intelligence
    Zwack, Laura
    Weber, Yvonne
    Sippel, Christoph
    Guenyak, Goekhan
    [J]. INTERNIST, 2019, 60 : S9 - S9
  • [42] Artificial Intelligence for Clinical Decision Support
    Zubair, Raheel
    Francisco, Gina
    Rao, Babar
    [J]. CUTIS, 2018, 102 (03): : 210 - 211
  • [43] ARTIFICIAL INTELLIGENCE AND DECISION SUPPORT SYSTEMS
    Wilson, L.
    Jacobs, P.
    Espinoza, A.
    Dodier, R.
    Young, G.
    Branigan, D.
    Eom, J.
    Chen, D.
    Mosquera-Lopez, C.
    El Youssef, J.
    Pinsonault, J.
    Leitschuh, J.
    Castle, J.
    [J]. DIABETES TECHNOLOGY & THERAPEUTICS, 2023, 25 : A3 - A3
  • [44] Refined group learning based on XCS and neural network in intelligent financial decision support system
    Li, Jung-Bin
    Chen, An-Pin
    [J]. ISDA 2006: SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, VOL 2, 2006, : 925 - +
  • [45] Artificial intelligence-based clinical decision support in pediatrics
    Ramgopal, Sriram
    Sanchez-Pinto, L. Nelson
    Horvat, Christopher M.
    Carroll, Michael S.
    Luo, Yuan
    Florin, Todd A.
    [J]. PEDIATRIC RESEARCH, 2023, 93 (02) : 334 - 341
  • [46] Artificial Intelligence-Based Decision Support in Laboratory Diagnostics
    Scherrer, Alexander
    Helmling, Michael
    Singer, Christian
    Riedel, Sinan
    Kuefer, Karl-Heinz
    [J]. OPERATIONS RESEARCH PROCEEDINGS 2021, 2022, : 229 - 235
  • [47] Artificial intelligence-based clinical decision support in pediatrics
    Sriram Ramgopal
    L. Nelson Sanchez-Pinto
    Christopher M. Horvat
    Michael S. Carroll
    Yuan Luo
    Todd A. Florin
    [J]. Pediatric Research, 2023, 93 : 334 - 341
  • [48] Digital Design of Smart Museum Based on Artificial Intelligence
    Wang, Bin
    [J]. MOBILE INFORMATION SYSTEMS, 2021, 2021
  • [49] Intelligent Decision Support for Energy Management: A Methodology for Tailored Explainability of Artificial Intelligence Analytics
    Panagoulias, Dimitrios P.
    Sarmas, Elissaios
    Marinakis, Vangelis
    Virvou, Maria
    Tsihrintzis, George A.
    Doukas, Haris
    [J]. ELECTRONICS, 2023, 12 (21)
  • [50] Intelligent decision support systems in construction engineering: An artificial intelligence and machine learning approaches
    Waqar, Ahsan
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2024, 249