An Audit Risk Model Based on Improved BP Neural Network Data Mining Algorithm

Professional auditors provide audit services to businesses and they are key participants in enterprise development. Effective identification of audit risks can help auditors plan their audit work rationally and issue correct audit opinions. In the era of big data and the Internet, enterprises genera...

Full description

Saved in:
Bibliographic Details
Main Authors: Wenjia Niu, Lihua Zhao, Peiyao Jia, Jiankun Chu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Advances in Multimedia
Online Access:http://dx.doi.org/10.1155/2022/9977292
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832565741103087616
author Wenjia Niu
Lihua Zhao
Peiyao Jia
Jiankun Chu
author_facet Wenjia Niu
Lihua Zhao
Peiyao Jia
Jiankun Chu
author_sort Wenjia Niu
collection DOAJ
description Professional auditors provide audit services to businesses and they are key participants in enterprise development. Effective identification of audit risks can help auditors plan their audit work rationally and issue correct audit opinions. In the era of big data and the Internet, enterprises generate a large amount of data in their daily operations. For auditors, it is a great challenge to use data mining algorithms, machine learning, artificial intelligence, and other emerging technologies to identify high-quality audit data from the vast amount of data of audited enterprises. At the same time, some companies may falsify and modify their financial statements for their own benefit, which further increases the difficulty for auditors in conducting audits. Traditional auditing methods are costly and consuming and cannot meet standard auditing requirements. Therefore, this study applies computer data mining algorithms to construct an audit risk model that provides a reference for auditors to conduct big data analysis and mines valuable data, thereby improving the efficiency and accuracy of the audit process.
format Article
id doaj-art-b91b1c4d28354e8a8eff1c48c4caf4f0
institution Kabale University
issn 1687-5699
language English
publishDate 2022-01-01
publisher Wiley
record_format Article
series Advances in Multimedia
spelling doaj-art-b91b1c4d28354e8a8eff1c48c4caf4f02025-02-03T01:06:50ZengWileyAdvances in Multimedia1687-56992022-01-01202210.1155/2022/9977292An Audit Risk Model Based on Improved BP Neural Network Data Mining AlgorithmWenjia Niu0Lihua Zhao1Peiyao Jia2Jiankun Chu3Accounting DepartmentAccounting DepartmentAccounting DepartmentAccounting DepartmentProfessional auditors provide audit services to businesses and they are key participants in enterprise development. Effective identification of audit risks can help auditors plan their audit work rationally and issue correct audit opinions. In the era of big data and the Internet, enterprises generate a large amount of data in their daily operations. For auditors, it is a great challenge to use data mining algorithms, machine learning, artificial intelligence, and other emerging technologies to identify high-quality audit data from the vast amount of data of audited enterprises. At the same time, some companies may falsify and modify their financial statements for their own benefit, which further increases the difficulty for auditors in conducting audits. Traditional auditing methods are costly and consuming and cannot meet standard auditing requirements. Therefore, this study applies computer data mining algorithms to construct an audit risk model that provides a reference for auditors to conduct big data analysis and mines valuable data, thereby improving the efficiency and accuracy of the audit process.http://dx.doi.org/10.1155/2022/9977292
spellingShingle Wenjia Niu
Lihua Zhao
Peiyao Jia
Jiankun Chu
An Audit Risk Model Based on Improved BP Neural Network Data Mining Algorithm
Advances in Multimedia
title An Audit Risk Model Based on Improved BP Neural Network Data Mining Algorithm
title_full An Audit Risk Model Based on Improved BP Neural Network Data Mining Algorithm
title_fullStr An Audit Risk Model Based on Improved BP Neural Network Data Mining Algorithm
title_full_unstemmed An Audit Risk Model Based on Improved BP Neural Network Data Mining Algorithm
title_short An Audit Risk Model Based on Improved BP Neural Network Data Mining Algorithm
title_sort audit risk model based on improved bp neural network data mining algorithm
url http://dx.doi.org/10.1155/2022/9977292
work_keys_str_mv AT wenjianiu anauditriskmodelbasedonimprovedbpneuralnetworkdataminingalgorithm
AT lihuazhao anauditriskmodelbasedonimprovedbpneuralnetworkdataminingalgorithm
AT peiyaojia anauditriskmodelbasedonimprovedbpneuralnetworkdataminingalgorithm
AT jiankunchu anauditriskmodelbasedonimprovedbpneuralnetworkdataminingalgorithm
AT wenjianiu auditriskmodelbasedonimprovedbpneuralnetworkdataminingalgorithm
AT lihuazhao auditriskmodelbasedonimprovedbpneuralnetworkdataminingalgorithm
AT peiyaojia auditriskmodelbasedonimprovedbpneuralnetworkdataminingalgorithm
AT jiankunchu auditriskmodelbasedonimprovedbpneuralnetworkdataminingalgorithm