Analysis on The Effectiveness of Augmented Artificial Intelligence Implementation in Preventing Fraudulent Financial Statement by Utilizing Beneish M-Score Model

K. Deniswara, M. Jonathan, Archie Nathanael Mulyawan, Irvan Santoso
{"title":"Analysis on The Effectiveness of Augmented Artificial Intelligence Implementation in Preventing Fraudulent Financial Statement by Utilizing Beneish M-Score Model","authors":"K. Deniswara, M. Jonathan, Archie Nathanael Mulyawan, Irvan Santoso","doi":"10.1145/3572647.3572695","DOIUrl":null,"url":null,"abstract":"This study aims to analyze the effectiveness of augmented artificial intelligence implementation, which is PwC's GL.ai, in preventing fraudulent financial statement by utilizing Beneish M-Score model. The population of this study is all PwC Indonesia's clients that are listed in Indonesia Stock Exchange for the period of 2017-2021. Purposive sampling is used as sampling procedure and paired sample t-test, effect size statistic, along with statistic descriptive test are applied as the data analysis methods of this study, By utilizing Beneish M-Score model as a proxy to calculate the likelihood of manipulation in companies’ financial statements, this study concludes that the implementation of augmented artificial intelligence, namely PwC's GL.ai is an effective treatment to prevent the probability of fraudulent financial statement from occurring.","PeriodicalId":118352,"journal":{"name":"Proceedings of the 2022 6th International Conference on E-Business and Internet","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2022 6th International Conference on E-Business and Internet","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3572647.3572695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This study aims to analyze the effectiveness of augmented artificial intelligence implementation, which is PwC's GL.ai, in preventing fraudulent financial statement by utilizing Beneish M-Score model. The population of this study is all PwC Indonesia's clients that are listed in Indonesia Stock Exchange for the period of 2017-2021. Purposive sampling is used as sampling procedure and paired sample t-test, effect size statistic, along with statistic descriptive test are applied as the data analysis methods of this study, By utilizing Beneish M-Score model as a proxy to calculate the likelihood of manipulation in companies’ financial statements, this study concludes that the implementation of augmented artificial intelligence, namely PwC's GL.ai is an effective treatment to prevent the probability of fraudulent financial statement from occurring.
基于Beneish M-Score模型的增强型人工智能实施在防止财务报表舞弊中的有效性分析
本研究旨在分析增强人工智能实施的有效性,即普华永道的GL.ai,利用Beneish M-Score模型防止欺诈性财务报表。本研究的人口是普华永道印度尼西亚在2017-2021年期间在印度尼西亚证券交易所上市的所有客户。本研究采用有目的抽样作为抽样程序,并采用配对样本t检验、效应量统计以及统计描述性检验作为数据分析方法,利用Beneish M-Score模型作为代理计算公司财务报表被操纵的可能性,本研究得出增强人工智能的实施,即普华永道的GL.ai是防止虚假财务报表发生概率的有效处理方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信