MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM Ho Chi Minh University of Banking DUONG THUY HANG APPLYING AUDIT DATA ANALYTICS IN FINANCIAL STATEMENT AUDIT: A CASE STUDY AT AASC GRADUATION THESIS MAJOR IN ACCOUNTING CODE: 7340301 Ho Chi Minh City, 2022 MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM Ho Chi Minh University of Banking DUONG THUY HANG APPLYING AUDIT DATA ANALYTICS IN FINANCIAL STATEMENT AUDIT: A CASE STUDY AT AASC GRADUATION THESIS MAJOR IN ACCOUNTING CODE: 7340301 SUPERVISOR DANG DINH TAN (PhD) Ho Chi Minh City, 2022 i ABSTRACT Big Data (BD) and Data Analytics (DA) are hot topics in many fields today. Enterprises with strong development strategies such as economic groups and large companies are interested in implementing and applying them to their operation processes, and the audit field is no exception. However, to apply them in practice, it is necessary to carefully consider and calculate the potential positives and negatives of BD and DA. In the article, the author summarizes some key features of the application of data analysis and big data in auditing financial statements, and points out the benefits and challenges for business auditing when applicable.
Thereby, the author discusses solutions to reduce challenges when applying DA and BD for auditing firms in modern financial statement audits. Keywords: Audit data analytics, data analysis, financial statement audit ii DECLARATION OF AUTHENTICITY I declare that all materials presented hereinafter are my own work based on my best knowledge during university and with the support of my supervisor Dang Dinh Tan (PhD). This thesis is guaranteed to be free from plagiarism, in which any cites or quotes are fully acknowledged in the references. At any time, I am responsible for my works if it is shown that I have violated this declaration of authenticity.
Ho Chi Minh City, June 2022 Duong Thuy Hang iii ACKNOWLEDGEMENTS First and foremost, I would like to thank my supervisor, Dang Dinh Tan (PhD), for his excellent direction, assistance, and attention to this thesis. This would not have been possible without his unending encouragement and support. Second, I would like to express my heartfelt gratitude to all instructors at Banking University of Ho Chi Minh City for their tremendous efforts in giving me a solid foundation of knowledge in both academic and professional life. Last but not least, I would like to express my heartfelt gratitude to my loving family and friends for their unending patience, support, and faith in me that has enabled me to reach this point.
This would not have been feasible without their constant encouragement. Ho Chi Minh City, June 2022 Duong Thuy Hang iv TABLE OF CONTENTS ABSTRACT. i DECLARATION OF AUTHENTICITY. iii TABLE OF CONTENTS.
iv LIS OF ABBREVIATIONS. vii LIST OF TABLES AND FIGURES. viii CHAPTER 1: INTRODUCTION. The necessity of the topic.
General, specific objectives and research questions. Research objects and research scopes. The research methodology. Contribution of the research.
Structure of the thesis .4 CONCLUSION OF CHAPTER 1. 6 CHAPTER 2: PRIOR STUDIES ON THE APPLICATION OF AUDIT ANALYTICS .11 CONCLUSION OF CHAPTER 2. 14 CHAPTER 3: THEORETICAL PERSPECTIVES. Concept of audit data analytics.
Purpose of audit data analytics. Auditor‟s approach to developing specific data analysis tools. Reliability of audit data analytics. Risks associated with the application of audit data analytics.
Applying audit data analytics in financial statement audit. Applying audit data analytics in the audit planning phase. Applying audit data analytics in the audit implementation phase 24 3. Applying audit data analytics in the audit reporting phase .27 CONCLUSION OF CHAPTER 3.
28 CHAPTER 4: RESULTS AND DISCUSSIONS. Apply some new audit analytics techniques to two client cases of this audit firm accrual 2021. Interviewing results on the advantages, opportunities and challenges of applying those new audit analytics techniques in the context of the audit firm39 4. The opportunities and challenges .41 CONCLUSION OF CHAPTER 4.
44 CHAPTER 5: CONCLUSION AND RECOMMENDATIONS. Training on data analytics skills for audit staff. Support for auditing firms to apply big data and data analytics in professional practice. Auditing firms need to consider carefully before investing in big data and data analytics.
54 APPENDIX A: The process of implementing a typical contract at AASC Auditing Firm. 58 APPENDIX B: Illustrative Data of Company A for the year 2021. 64 APPENDIX C: Illustrative Data of Company B for the year 2021. 69 vii LIS OF ABBREVIATIONS Abbreviations Full meaning ADA Audit data analytics BD Big data CPS Cyber Physical Systems DA Data analytics Deloitte Deloitte Touche Tohmatsu ERP Enterprise resource planning EY Ernst & Young FAO Fast Accounting Offline FPT Financing Promoting Technology GL General ledger HDP Hortonworks Data Platform IoT Internet of Things IT Information technology KPMG Klynveld Peat Marwick Geordeler NFD Non-financial data PwC PricewaterhouseCoopers TP Bank Tien Phong Bank VACPA Vietnam Association of Certified Public Accountants viii LIST OF TABLES AND FIGURES Figure 1: PwC‟s „Halo for Journals‟ .18 Figure 2: Ending G/L account balances as of 2021 compared to 2020 (in million VND) .32 Figure 3: Changes in ending G/L account balances as of 2021 compared to 2020 (%) .33 Figure 4: Monthly Debit amount of A/R in 2020, 2021 (in million VND) .34 Figure 5: Monthly transactions in 2020, 2021 .36 Figure 6: Monthly total amount of transactions in 2020, 2021 (in million VND).36 Figure 7: Outliers of transaction amounts by month in 2021 .37 Figure 8: Number of transactions by week day and month in 2021 .39 Table 1: The Balance sheet of company A between 2020 and 2021 .32 Table 2: Ten largest transactions in July 2021 of Company B.
The necessity of the topic The analysis is a highly effective audit procedure because it takes little time and is low cost, but it can provide evidence of the uniformity and general plausibility of the data, and at the same time, it helps not to get too involved in the transactions. Specifically, analytical procedures are used in all three phases of the audit process to gather evidence to conclude the reasonableness or anomaly of the data. Although numerous scholarly articles have been written on the future of DA in accounting, relatively little empirical scholarly research has been conducted addressing the issues presented in this article. However, several scholarly articles present specific research questions to be addressed in DA.
For example, Wang and Cuthbertson (in press) interviewed a practitioner with more than 30 years of experience developing analytical tools for internal and external auditors. They identified eight categories of research questions that scientists can address, including the role of DA in risk analysis, what procedures should be performed, the impact of testing 100% of the population, whether external data should be used, the role of DA use by internal auditors, the interpretation of DA results, the consequences of DA use, and whether the profession needs a DA framework. Similarly, Leonard Combs, PwC U. Chief Auditor and Leader of Auditing Services, Methodology & Tools reports: “Data analytics is changing both the way we conduct our audits and what those audits deliver.
It allows us to extract and analyze ever-larger data sets. Further use of data analytics will allow us to deliver effective audits more efficiently” (PwC 2017). Current reality shows that many auditors who apply this procedure are stereotyped, rigid, and do not bring into full play the effect of analytical procedures in finding and detecting fraud and material misstatement in the report financial statement. While data analytics can successfully address some assertions, it does not eliminate the necessity for other audit methods to address the risk of a significant 2 misstatement as a whole.
Such techniques include tracing back to the underlying source documents, which is required to resolve other accusations (e., occurrence and rights and obligations). As a result, the auditor must perform procedures to address the risk of a significant misstatement as a whole. After completing the internship period at AASC Auditing Firm, the researcher has gained knowledge and experience in the financial statement audit process, especially new data analysis techniques. Realizing the need to minimize the risk of errors on the financial statement and optimize the efficiency for users, the author chooses the topic name "Applying audit data analytics in financial statements audit: A case study at AASC" as graduation thesis.
General, specific objectives and research questions General objectives: Currently, in Vietnam, this topic is also being interesting and applied by many organizations and units. However, there are not many articles or in-depth studies on the potential benefits and difficulties for auditing firms in Vietnam when applying BD and DA in the audit of financial statements. Therefore, in this article, the author synthesizes and analyzes the characteristics and opportunities, challenges of the application of DA and BD in financial statement audit at AASC Auditing Firm with the desire to contribute a more multi-dimensional view of the financial statements. Besides, this study provides insight into how firms‟ leadership and engagement partners and managers perceive the prospects and impediments to audit data analytic (ADA) use.
Specific objectives: Research on the project application process through 2 case studies when auditing financial statements at AASC and conducting in-depth interviews with auditors in AASC: - Review and explore opportunities and challenges of applying DA, thereby drawing lessons from experience and specific perspectives to apply to audit activities at other auditing firms. 3 - Analyze the preliminary balances in all the accounts in the company's general ledger to identify unusual changes from the previous year. - Use the results of the analysis to decide whether changes were needed in the planned nature, timing and extent of the following: Other risk assessment procedures, focused on particular accounts and related assertions. Further audit procedures to be performed in response to assessed risks, including tests of controls and substantive procedures.
- To obtain understandings about all transactions occurred in 2021 - To find outliers of transaction amounts in 2021 - To identify risk of frauds in 2021 Research questions: To achieve the research objectives, the following questions need to be well answered: Q1: How does the firm currently perform analytical procedures and audit analytics in the audit process? Q2: What are the advantages/opportunities and challenges for the firm in applying audit data analytics? 1. Research objects and research scopes The research subject are two manufacturing and trading companies whose financial statements are audited by AASC Auditing Firm. The research scope: - Cross section dimension: The study is limited to an enterprise audited by AASC and conducted in Ho Chi Minh City. - Time series dimension: a 2-year period from 2020 to 2021 is selected, in which secondary data is collected from financial statements of two manufacturing and trading companies.
The research methodology The thesis uses observational and descriptive method to collect primary and secondary information at AASC. Moreover, the author uses the theoretical research method and empirical method to search, analyze, process information, and describe the statistical methods, and practical experience through real work. Data sources: In this thesis, the author uses two sources of data, which are primary data and secondary data. - Primary data: Those data were collected by interview method during the research period at AASC, in order to identify the advantages, opportunities and challenges of applying new audit analytics techniques in the context of the audit firm.
- Secondary data: That information and knowledge collected from internal AASC documents and customer's accounting data (in Excel). Contribution of the research Firstly, the thesis has systematized the theoretical basis necessary for further studies on ADA. Especially, many previous findings related to BD and DA in large audit firms were collected to provide a more thorough perspective on this regard. Secondly, the thesis has pointed out new data analysis techniques compared to current ones to apply to improve audit quality.