Artificial intelligence is an important emerging technology in the accounting industry. Fear and hype associated with artificial intelligence and its impact on accounting and auditing jobs have pervaded the professional fields of accounting and auditing. It is important to develop AI competency in accountants and auditors. This paper presents a teaching case for a professor or lecturer to use for teaching machine learning to accounting students. The case is based on openly available data from the China Stock Market & Accounting Research database and aims to teach students how to predict the future audit report type of a China ST listed company. Through case teaching, students can learn skills related to computer-assisted auditing tools and machine learning (such as ACL) develop the confidence to apply artificial intelligence in their education and future work.
{"title":"Application of Machine Learning in Auditing Teaching: A Case Study of Predicting the Audit Report Type of China ST Listed Companies","authors":"Shi-Ming Huang Shi-Ming Huang, Chang-ping Chen Shi-Ming Huang, Tzu-ching Wong Chang-ping Chen","doi":"10.53106/256299802020120201003","DOIUrl":"https://doi.org/10.53106/256299802020120201003","url":null,"abstract":"\u0000 Artificial intelligence is an important emerging technology in the accounting industry. Fear and hype associated with artificial intelligence and its impact on accounting and auditing jobs have pervaded the professional fields of accounting and auditing. It is important to develop AI competency in accountants and auditors. This paper presents a teaching case for a professor or lecturer to use for teaching machine learning to accounting students. The case is based on openly available data from the China Stock Market & Accounting Research database and aims to teach students how to predict the future audit report type of a China ST listed company. Through case teaching, students can learn skills related to computer-assisted auditing tools and machine learning (such as ACL) develop the confidence to apply artificial intelligence in their education and future work.\u0000 \u0000","PeriodicalId":396733,"journal":{"name":"International Journal of Computer Auditing","volume":"17 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116560810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.53106/256299802020120201001
Cindy Durtschi Cindy Durtschi, Tawei (David) Wang Cindy Durtschi
Accounting programs are now being encouraged to incorporate data analytics into their programs. This article will provide suggestions on how to set up a data analytics program in a school of accountancy, answer why it is important to incorporate data analytics within accounting programs, and nally how to create a well-integrated curriculum.
{"title":"The Development of Accounting Data Analytics Curriculum","authors":"Cindy Durtschi Cindy Durtschi, Tawei (David) Wang Cindy Durtschi","doi":"10.53106/256299802020120201001","DOIUrl":"https://doi.org/10.53106/256299802020120201001","url":null,"abstract":"\u0000 Accounting programs are now being encouraged to incorporate data analytics into their programs. This article will provide suggestions on how to set up a data analytics program in a school of accountancy, answer why it is important to incorporate data analytics within accounting programs, and nally how to create a well-integrated curriculum.\u0000 \u0000","PeriodicalId":396733,"journal":{"name":"International Journal of Computer Auditing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126041037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper provides a machine-learning experimental process for a real-world corporate financial bankruptcy case: Chunghwa Picture Tubes, Ltd., in Taiwan in 2019. The teaching case addresses major topics in financial bankruptcy analytics to enable business students to learn how to analyze leveraged finance and distressed debt and to predict bankruptcy. It is a science, technology, engineering, and mathematics (STEM) teaching case with a project-based learning method. The learning goal of the teaching case is to inspire and encourage students through planned teaching activities. Students start by thinking through problems or situations and establishing a machine-learning project using computer-assisted audit technique (CAAT) software. After students conduct a self-directed project, the student can use the new knowledge to develop a new bankruptcy-case analysis.
{"title":"Teaching Case – Predicting the Probability of Company Bankruptcy with CAATs","authors":"Shi-Ming Huang Shi-Ming Huang, Yu-Ting Huang Shi-Ming Huang, Li-Kuan Wang Yu-Ting Huang","doi":"10.53106/256299802020120201002","DOIUrl":"https://doi.org/10.53106/256299802020120201002","url":null,"abstract":"\u0000 The paper provides a machine-learning experimental process for a real-world corporate financial bankruptcy case: Chunghwa Picture Tubes, Ltd., in Taiwan in 2019. The teaching case addresses major topics in financial bankruptcy analytics to enable business students to learn how to analyze leveraged finance and distressed debt and to predict bankruptcy. It is a science, technology, engineering, and mathematics (STEM) teaching case with a project-based learning method. The learning goal of the teaching case is to inspire and encourage students through planned teaching activities. Students start by thinking through problems or situations and establishing a machine-learning project using computer-assisted audit technique (CAAT) software. After students conduct a self-directed project, the student can use the new knowledge to develop a new bankruptcy-case analysis.\u0000 \u0000","PeriodicalId":396733,"journal":{"name":"International Journal of Computer Auditing","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132753045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.53106/256299802019120101004
Mohamed A. Wahdan Mohamed A. Wahdan, Manar Hassan Mohamed A. Wahdan
This paper explores how can a knowledge–based system (KBS) be used in auditing especially when the task requires using professional judgments. It concerned with modeling, implementing and evaluating a KBS called Materiality EXpert (MEX). MEX can assess the level of planning materiality and performance materiality as professionals act. Knowledge used to build MEX is acquired from literature, international standards on auditing, and experienced auditors using questionnaire as well as unstructured and structured interviews. MEX was evaluated by 34 auditors from different audit firms in Egypt including international audit firms. The evaluation results acquired from experienced auditors in Egypt indicated that MEX successfully executes the task of assessing the level of planning materiality and performance materiality. Moreover, MEX is efficient, effective, and acceptable from auditors for assessing the level of planning materiality and performance materiality.
{"title":"Automatic Assessment of Materiality: A Knowledge-based Approach","authors":"Mohamed A. Wahdan Mohamed A. Wahdan, Manar Hassan Mohamed A. Wahdan","doi":"10.53106/256299802019120101004","DOIUrl":"https://doi.org/10.53106/256299802019120101004","url":null,"abstract":"\u0000 This paper explores how can a knowledge–based system (KBS) be used in auditing especially when the task requires using professional judgments. It concerned with modeling, implementing and evaluating a KBS called Materiality EXpert (MEX). MEX can assess the level of planning materiality and performance materiality as professionals act. Knowledge used to build MEX is acquired from literature, international standards on auditing, and experienced auditors using questionnaire as well as unstructured and structured interviews. MEX was evaluated by 34 auditors from different audit firms in Egypt including international audit firms. The evaluation results acquired from experienced auditors in Egypt indicated that MEX successfully executes the task of assessing the level of planning materiality and performance materiality. Moreover, MEX is efficient, effective, and acceptable from auditors for assessing the level of planning materiality and performance materiality.\u0000 \u0000","PeriodicalId":396733,"journal":{"name":"International Journal of Computer Auditing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128269395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.53106/256299802019120101001
Tawei Wang Tawei Wang, Shi-Ming Huang Tawei Wang
We broadly define computer auditing as any audit practices that may rely on information technology (IT). Such skill has long been argued and considered to be an important capability for both external and internal auditors for more than two decades though its applications were relatively limited in the past. In recent years, with the advance of information technology, what auditors can achieve with IT has dramatically changed. For example, auditors are now be able to perform both descriptive and predictive analyses, process both numeric and textual data, and apply such capability from assertion testing to compliance and risk assessments. This evolving capability has also brought the new term “audit analytics” to practices. Specifically, analytics focuses more on the business decisions and processes while the traditional computer auditing is mainly about audit. This improved capability and expanded scope have attracted a lot of attention with a wide range of applications. For instance, the PCAOB’s new strategic plan (PCAOB 2018 ) has highlighted that “[i]nnovations in data analytics and technology have great potential to improve the efficiency and effectiveness of financial reporting and the audit process” (p.9). Audit firms and internal audit functions have also engaged in the development and the use of analytics in external and internal audit processes (e.g., Forbes 2018; Deloitte 2016; KPMG 2016), which have potentially changed the role of internal auditors to internal consultants.
{"title":"Computer Auditing: The way forward","authors":"Tawei Wang Tawei Wang, Shi-Ming Huang Tawei Wang","doi":"10.53106/256299802019120101001","DOIUrl":"https://doi.org/10.53106/256299802019120101001","url":null,"abstract":"\u0000 We broadly define computer auditing as any audit practices that may rely on information technology (IT). Such skill has long been argued and considered to be an important capability for both external and internal auditors for more than two decades though its applications were relatively limited in the past. In recent years, with the advance of information technology, what auditors can achieve with IT has dramatically changed. For example, auditors are now be able to perform both descriptive and predictive analyses, process both numeric and textual data, and apply such capability from assertion testing to compliance and risk assessments. This evolving capability has also brought the new term “audit analytics” to practices. Specifically, analytics focuses more on the business decisions and processes while the traditional computer auditing is mainly about audit. This improved capability and expanded scope have attracted a lot of attention with a wide range of applications. For instance, the PCAOB’s new strategic plan (PCAOB 2018 ) has highlighted that “[i]nnovations in data analytics and technology have great potential to improve the efficiency and effectiveness of financial reporting and the audit process” (p.9). Audit firms and internal audit functions have also engaged in the development and the use of analytics in external and internal audit processes (e.g., Forbes 2018; Deloitte 2016; KPMG 2016), which have potentially changed the role of internal auditors to internal consultants.\u0000 \u0000","PeriodicalId":396733,"journal":{"name":"International Journal of Computer Auditing","volume":"359 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114841098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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