Proceedings of the 2022 International Conference on Computer Science, Information Engineering and Digital Economy (CSIEDE 2022)

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Risk Identification Method of Enterprise AccountingInformation Fraud Based on Weighted Association Rule Algorithm

Authors
Jianhong Li1, Tong Yao2, *
1Sichuan University Jinjiang College, Meishan, Sichuan, 620860, China
2Sichuan Tourism University, Chengdu, Sichuan, 610100, China
*Corresponding author.
Corresponding Author
Tong Yao
Available Online 30 December 2022.
DOI
10.2991/978-94-6463-108-1_72How to use a DOI?
Keywords
association rule algorithm; Accounting fraud; Fraud risk identification
Abstract

In order to reduce the financial risks existing in enterprises, this paper studies the risk identification of enterprise accounting information fraud with weighted key algorithm. Based on the study of fuzzy association rules, this studyanalyzes the financial risks of enterprises, puts forward an analysis model of enterprise financial risks based on fuzzy association rules mining algorithm, andmakes a qualitative analysis of enterprise financial crises, so as to predict enterprise financial risks and provide reference for enterprises to avoid risks. Comparing the correlation algorithm with the linear regression model, the result shows that the prediction error rate of the linear regression model is higher thanthat of the correlation algorithm model. Class I misjudgment rate is 40% higher,class II misjudgment rate is flat, overall misjudgment rate is 20% higher, and accuracy linear regression is 20% lower than correlation algorithm. It can be seenthat the misjudgment rate of the correlation algorithm model is low, the predictionaccuracy is high, and the discrimination and prediction ability of the linear regression model is poor, which proves the effectiveness of the application of thecorrelation algorithm in this paper.

Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 International Conference on Computer Science, Information Engineering and Digital Economy (CSIEDE 2022)
Series
Advances in Computer Science Research
Publication Date
30 December 2022
ISBN
10.2991/978-94-6463-108-1_72
ISSN
2352-538X
DOI
10.2991/978-94-6463-108-1_72How to use a DOI?
Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jianhong Li
AU  - Tong Yao
PY  - 2022
DA  - 2022/12/30
TI  - Risk Identification Method of Enterprise AccountingInformation Fraud Based on Weighted Association Rule Algorithm
BT  - Proceedings of the 2022 International Conference on Computer Science, Information Engineering and Digital Economy (CSIEDE 2022)
PB  - Atlantis Press
SP  - 647
EP  - 655
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-108-1_72
DO  - 10.2991/978-94-6463-108-1_72
ID  - Li2022
ER  -