Artificial intelligence (AI) has once again attracted the public’s attention in the past decade. Riding on the wave of big data revolution, the development of AI is much more promising than that 50 years ago. One example is ChatGPT (https://openai.com/blog/chatgpt/), which has quickly become a hot topic in the past several months and has brought back all kinds of discussion about AI and decision making. In this editorial, I would like to highlight several perspectives that may help us rethink about the implications of using AI for decision making especially for audit professionals.

Reference Format:
Tawei (David) Wang, 2022, Responsible Use of Artificial Intelligence, International Journal of Computer Auditing, Vol.4 No.1, Pages 1-3.
https://doi.org/10.53106/256299802022120401001

    Machine learning, a key subset of artificial intelligence, is expected to impact everyday life and business operations in the near future. Applications of machine learning have created opportunities and challenges for auditing. The technology enhances the ability to analyze big data to gain insight into performance of companies, a capability that improves audit quality. However, many repetitive auditing tasks, such as analyzing a company’s financial statements and source documents, can be automated. In other words, fewer entry-level accountants will be needed in the coming years (Julia & Thomas, 2017). The requirements for auditors will be understanding not only accounting but also technologies (i.e machine learning), a development that mandates accounting programs to evolve to equip students with such skills. Teaching with the Case method provides information through simulated real cases, but neither analysis nor conclusions, as an effective method to help students gain skills in applying technologies in accounting and auditing. This method also enhances other skills of students, such as critical thinking, communication, and group dynamics (Sandeep Puri, 2020). The present case has a large dataset created through a simulation of real Vietnamese small and medium enterprises (SMEs) data (available at https://www.wider.unu.edu) to represent the tax risk of SMEs. The first motivation of the case is to provide a resource available for taxation courses that are limited (Deb et al., 2021). The second motivation behind the teaching case arises from the requirement of the Association to Advance Collegiate Schools of Business (AACSB) International Standard A5 for accounting accreditation (AACSB, 2021), which requires learners to experience integrating real-world business strategies, information systems, and processes, and data management and data analytics tools (Peregrine Pathways, 2021). In this case, students will apply machine learning to find out what kinds of SMEs face more tax risk under the guidance of instructors. Students are also encouraged to answer questions of instructors and to find other models by themselves. By interpreting and comparing the results of models, students will learn that machine learning can do a lot but can not replace auditors in making value judgments. The remainder of the paper is divided into sections. The next section is the background of machine learning application to tax auditing. The third section provides the objectives of the teaching case. Teaching materials and the instruction of the case are presented in the fourth and the fifth section. The last section is the conclusion.

Reference Format:
Shi-Ming Huang | Huyen Thi Thanh Phan, 2022, Using Audit Command Language to Predict Tax Litigation Risk of Vietnamese SME Companies: A Teaching Case for Tax and AIS Courses, International Journal of Computer Auditing, Vol.4 No.1, Pages 4-22.
https://doi.org/10.53106/256299802022120401002

    We are living in an age of transformation. Audit firms are exploring new technologies to improve effectiveness and efficiency, thus improving audit quality. Among many technologies, Robotic Process Automation (RPA) is one of the most often mentioned technology because of its adaptability to audit procedures. The official definition of RPA is “A preconfigured software instance that uses business rules and predefined activity choreography to complete the autonomous execution of a combination of processes, activities, transactions, and tasks in one or more unrelated software systems to deliver a result or service with human exception management” (IEEE Corporate Advisory Group, 2017). An easier way to understand RPA is that to consider RPA as a software technology that designs, builds and deploys a software program, usually referred as a “robot” or “bot,” to interact with the computer application by mimicking human actions to complete specific task defined by the robot designer. RPA can automate human activities such as keyboard inputs, mouse movements, clicks, and computer screen reading. Combing these actions, a bot can perform many tasks a human can do on a computer.

Reference Format:
Shaoyu Liu, 2022, Robotic Process Automation (RPA) in Auditing: A Commentary, International Journal of Computer Auditing, Vol.4 No.1, Pages 23-28.
https://doi.org/10.53106/256299802022120401003

    ESG (Environmental, Social, and Governance) audits are becoming increasingly critical for companies to demonstrate their commitment to sustainable practices and responsible business operations. Consequently, there is a growing demand for professionals who possess ESG audit skills. Worldwide, there are several training courses available that cover ESG topics and aim to equip professionals with the necessary knowledge and skills to conduct effective ESG audits and help companies enhance their sustainability performance. These courses typically cover a range of topics, such as ESG reporting and assurance, stakeholder engagement, and sustainable investing strategies. Furthermore, the International Computer Auditing Education Association (ICAEA) local chapters offer several ESG audit training courses in their respective territories, adhering to the ICAEA CPE policy (ICAEA, 2023). The courses aim to provide practical hands-on experience in addition to theoretical knowledge. This paper will examine and report on the effectiveness and performance of these training courses in Taiwan and the Middle East.

Reference Format:
Sherry Huang | Ezz Hatab, 2022, ESG Audit Training Perspective in Asia, International Journal of Computer Auditing, Vol.4 No.1, Pages 29-36.
https://doi.org/10.53106/256299802022120401004