Teaching big data for accounting and auditing students in Vietnam universities

471 International Conference on Finance, Accounting and Auditing (ICFAA 2018) November 23rd, 2018 Hanoi City, Vietnam Teaching Big Data for Accounting and Auditing Students in Vietnam Universities Tran Quy Longa aNational Economics University Submission day: 30/10/2018 Review day: 10/11/2018 Acceptance day: 15/11/2018 Abstract Industrial revolution 4.0 has changed every aspects of the economy. In this study, the impacts of big data, one of the main industrial revolution 4.0 characteristics, on accounting and auditing activities will be examined. Big Data has become a tool to help accountants practice their careers with a more effective approach than the traditional tools. It has also created challenges for accountants with data asset valuation. This study also points out that accounting and auditing students should have big data knowledge and data analytic skills. Hence Big Data topics should be embedded in existing courses across accounting curricula and Vietnamese universities need to change their educational programs in order to adapt the employers’ demand. Keywords: Accounting curriculum, Big data, Data analytics 1. Introduction Industrial revolution 4.0 is going to bring about great changes in all fields and sectors, including accounting and auditing. According to Islam (2017), the first change in auditing and accounting is the introduction of sophisticated technologies and artificial intelligence that will be increasingly applied in accounting and auditing. These technologies not only improve the efficiency of existing accounting operations but can even replace traditional approaches. Intelligent software systems (including cloud computing) will support the use of outsourced services (including outsourcing services abroad). Furthermore, the use of social media through smart technology will improve cooperation between owners and the wider community. According to a study by ACCA published in 2016, accounting practice 472 will be reshaped by the trend of digital technology and the impact of digital technology on business. Intelligent software and systems will replace manual accounting and accounting, and these software and systems will automate the processing of accounting records. complex programming. Thus, an accountant will need to acquire knowledge of new models in business, transporting, and manufacturing. Even accountants must become experts in the use of new technologies. One of the major contents of the Industrial Revolution 4.0 is Big Data. Big Data is defined as a term used to refer to a very large set of data and is so complex that traditional data processing tools and applications cannot handle. The size of Big Data is increasing day by day, and so far it can be in the tens of terabytes to many petabytes for just one dataset. According to Bholat (2015), Big Data can be defined as data having one or more of the following characteristics: - The data is large, as they are usually reported on very detailed bases, for example the data set of each loan, of each securities account. - These data are constantly moving, because these data are updated regularly, collected and analyzed in real-time, meaning that they are analyzed at the time of the data generation. - These data differ in quality, meaning they may not be numbers, such as text or video, but may also be extracted from new sources such as social media, Internet search history or biometric sensor. Big Data contains a lot of valuable information that, if extracted successfully, it will help a lot for business, scientific research, anticipation of emerging diseases and even real- time traffic conditions, ... In the area of accounting, auditing, large data can be used in decision making, risk management, and data valuation. In this study, the effects of large data on accounting activity will be analyzed, thus indicating new requirements for training and research in the accounting field. 2. Impacts of Big Data on accounting and auditing First of all, the use of big data creates new requirements in accounting for company’s assets. According to ACCA (2013), Big Data is not just a business tool, used as a purely competitive advantage, but has become a business model. Today's profits are being built on large data. Internet companies such as Google are pioneers in making money from Big Data, and many other companies, working in many other fields, are following this trend. Telefonica has recently built a division called Dynamic Insights. This department uses the company's corporate data repository to create new services and revenue streams. ACCA recognizes that in the next 10 years, data will become an important source of wealth for the company, so it must be seen as a business asset, to be valued and to account. In the Dynamic Market study (2012), 20% of large companies classified data as an asset in their balance sheet, and with large companies with more than 10,000 employees, this rate is 30%. Consequently, this poses a requirement for accountants to be able to value the data. 473 Determining the value of data assets is a very difficult task. Tangible assets are increasingly important in the knowledge economy, but they tend to be hidden in reports and governance systems. The first challenge in pricing data is the issue of depreciation. The rapid increase in the value of old data quickly becomes obsolete, losing value as soon as new data becomes available. Another problem is that the value of the data varies with relevancy, and the relevance varies with the user. This makes it difficult to measure objectively the value of a dataset because it may be less important to one group, but it is worthwhile to another. Secondly, Big Data itself also becomes a tool to help accountants practice their careers with a more effective approach than the traditional tools. There is a huge opportunity in accountancy for using big data for real-time impacts and financial predictions. Accountants can incorporate big data into the financial performance measures they regularly provide to businesses. You could start by asking clients for their website’s analytics reports to develop deeper insights into the business. Accountants have access to an unprecedented amount of big data and there is an opportunity to use it for financial advantage. It can be used to increase operating efficiencies, assess risks and identify advantages and weaknesses through analysis. Rezaee and Wang (2017) have shown the influence of big data on accounting and auditing on financial accounting, management accounting, and auditing. According to two authors, there have been two main trends in the application of big data into financial accounting. Firstly, various data sources are being integrated into the accounting information systems such as text, video, audio data, customer purchase activity, Url tracking. Secondly, regarding the reasonable valuation, the emergence of data service companies that collect and evaluate data from different sources can minimize subjective assumptions in estimating and calculating the fair value of assets and capital. According to ACCA (2013), Big data also has the potential to improve the performance management system. For example, the finance and accounting department of a manufacturing company can obtain standard data from a financial services provider and compare the company's performance below the average. Companies can monitor employee phone calls, emails and other office activities such as web usage and clicks. By applying big data analysis techniques, traditional management can be transformed through the deployment of comprehensive monitoring and control systems. For example, using big data can help identify new motivational approaches and analyze the relationship between good management performance and previously unverified variables. For example, corporates can measure employee's enthusiasm by voice and phone conversations made on the company's device. They can also measure productivity by the number of emails sent by the manager and measure the customers' satisfaction by the customer's body language. In the area of auditing, auditors need to understand the big data to be able to track how their customers manage their data. With the new data analysis tools available, accountants can use large data to reduce auditing costs and increase profitability. For example, to verify the database with independent trading partners, the accountant can perform automatic validation instead of manual verification. Confirmation.com provides an example of an automated audit certification. The company provides safe audit 474 certification services to over 14,000 accounting firms, 100,000 auditors and 700,000 organizations. With large data, auditors can analyze both structured and unstructured data to identify potential abnormal transactions (eg, illegal disbursements), behavioral patterns (for example, payment split to overcome transaction limits), and trends (such as increased fraud transactions before a long holiday). As a result of the use of automatic data collection and analysis techniques to determine the error, the auditor may change the responsibility for error detection in the data to assess what error is worth investigating more. The ACCA report (2013) also shows that big data can be used in decision making and risk management. The increase in volume of both structured and unstructured information, combined with more sophisticated analytical tools, has facilitated greater data- driven decision making. Large data usage will aid in decision making in real time. The financial and accounting department of an enterprise can improve data flow both within the enterprise and outside organizations, saving costs, time and efficiency. Accountants and financial professionals can help maximize the value of the data by identifying the points at which the data can be shared most effectively with internal and external stakeholders. The timely exchange of data between departments can improve consistency and clarity and avoid situations where decision makers receive different answers to the same question or analyze the same sentence. asked twice. In addition, large data can be used in risk management with the use of data sources used in risk prediction is expanded, risk is determined in real time. From analyzing these impacts, ACCA also points out that big data is an opportunity for accounting and finance to play a more strategic role and help shape the future. Trained to collect and analyze data (structured and unstructured), the accounting and finance department can provide critical advice to management and business leaders. For example, accountants can use big data to find behavioral patterns in consumers and market. These patterns can help businesses build analytic model that, in turn, help them identify investment opportunities and generate higher profit margins. Accountants have access to an unprecedented amount of big data and there is an opportunity to use it for financial advantage. It can be used to increase operating efficiencies, assess risks and identify advantages and weaknesses through analysis. Accountants can use big data analysis to position themselves as strategic business partners instead of their more traditional accounting role. Finance departments are now using predictive analytics tools together with customer data to make forecasts. The IT department has traditionally managed big data; however, the marketing department is moving to position itself as the natural home of big data. Accountancy and finance professionals can bridge the gap between IT, marketing and the business that needs insight to maximize big data opportunities. 475 Table 1: Opportunities and challenges Big Data presents the accountancy and finance profession Area Opportunity Challenge 1. Valuation of data assets Helping companies value their data assets through the development of robust valuation methodologies Increasing the value of data through stewardship and quality control Big data can quickly ‘decay’ in value as new data becomes available The value of data varies according to its use Uncertainty about future developments in regulation, global governance and privacy rights and what they might mean for data value 2. Use of big data in decision making Using big data to offer more specialized decision-making support in real time Working in partnership with other departments to calculate the points at which big data can most usefully be shared with internal and external stakeholders Self-service and automation could erode the need for standard internal reporting Cultural barriers might obstruct data sharing between silos and across organisational boundaries 3. Use of big data in the management of risk Expanding the data resources used in risk forecasting to see the bigger picture Identifying risks in real-time for fraud detection and forensic accounting Using predictive analytics to test the risk of longer-term investment opportunities in new markets and products Ensuring that correlation is not confused with causation when using diverse data sources and big data analytics to identify risks Predictive analytic techniques will mean changes to budgeting and return on investment calculations Finding ways to factor failure- based learning from rapid experimentation techniques into processes, budgets and capital allocation Source: ACCA (2013) 3. Needs for changes in accounting and auditing education 3.1. Knowledge and skills related to big data that accounting students should have Under the influence of the industrial revolution 4.0, accounting students increasingly need to be equipped with the knowledge of digital technology such as cloud computing and the use of big data. The future of the accounting profession depends on embracing new forms 476 of data and revising accounting standards and practices to embrace both structured and unstructured data. Employers are seeking students with big data and analytics skill. As reported by ACCA (2016), knowledge of digital technology is an important capacity however this is an area where accountants also have many skills shortage. Especially with big data being increasingly applied in accounting and auditing activities, students in the field of accounting and auditing must be equipped with knowledge of data mining and new appropriate data analysis methods. First of all, students need the skill in data mining. Although the volume of information is extremely large, bias and representativeness persist in the data collected. This may reduce the quality of the data. For example, a huge amount of information is collected through social networks. However, this information only focuses on reflecting the characteristics of individuals or organizations that use social networks, while those who do not use social networking may have different characteristics. Therefore, data collected through social networks may be biased and non-representative. This will require additional information to adjust the statistics, and include this additional information in the overall data section to ensure the quality of the data source. Also from exploited data, there must be appropriate treatment methods. For example, statistical correction should still be carried out because information can be posted or repeated many times. Especially when an event occurs, the volume of information related to that event will be huge. Increasing this amount of information does not necessarily indicate a change in the demand for the economy. For example, when the emissions scandal in the auto industry happens, people will search for more car-related information. This comes from the anxiety and the need to observe the impact of this scandal on the auto market, and does not mean that people are increasing their demand for a car. 3.2. Teaching Big data in the accounting curriculum In order to meet the demand for change in training, the universities need to update their training programs in addition to new ones. Some emerging areas under the influence of the industrial revolution 4.0 that students in the field of accounting and auditing should be equipped with include: - Developing intelligent accounting system - The emergence of new models, needs and business services - Social media and its role in business and in information disclosure - Internet access - cost and connection quality - Applying cloud computing - Data mining and new analytical methods - Digital Publishing (Annual Report) - New ways to find new capital - Using technology to improve the quality of financial statements 477 At the present time, very few accounting and auditing institutes in Vietnam develop curricula for accounting students in line with the future needs of the 4.0 technology revolution in general and the need for knowledge of big data in particular. Therefore, Vietnamese universities may adopt big data accounting programs of foreign educational institutions and universities in order to apply to their current accounting and auditing curriculum. For examples, PricewaterhouseCoopers (2015) has developed recommendations for curriculum changes and include the following skills for undergraduate programs to learn big data accounting: - Learning of legacy technologies (Microsoft Excel and Access) - Understanding of structured and unstructured databases (SQL, MongoDB, Hadoop) - Obtaining and cleaning data - Introduction to data visualization (Tableau, SpotFire, Qlikview) - Univariate and multivariate regression, machine learning, and predictive tools - Early coverage of programming languages such as Python, Java, or R. The following skills are recommended for graduate programs: - Advanced statistics - Text mining, HTML scraping - Solving optimization problems - Data analytics internships, allowing students to solve real business issues. Gamage (2016) has also summarized Big Data topics that can be included within existing courses, as listed in table 2 Table 2: Big Data topics that can be included within existing courses Courses Topics Taxation Indirect tax and Big Data, tax value and non- tax value form data that is collected in the tax function, Visualize accounting data Forensic Accounting Big Data, Benford's Law, Financial Analytics, Data Analytics for Fraud, Anomaly Detection in Forensics and Security Auditing and Assurance Data Analytics in auditing, Mine new sources of data, Data integrity, Privacy, Safeguards, Cybersecurity, Design and evaluate IS controls, Manage IS risks and compliance, Overseeing fraud risk assessment Accounting Information Systems Business intelligence, Enterprise analytics Information search and retrieval, Data mining, familiarity with 478 Courses Topics languages such as XBRL, specialized software/reporting systems with decision support, ERP systems, Cybercrime, Data management issues Management Accounting Application of Big Data to competitor analysis, Big Data as a strategic resource Business Information Systems Advanced Databases, Information Retrieval, Advanced Data Mining Applications, Predictive Analytics for Decision Making, Big Data information management Business Statistics Data gathering techniques, Data exploration, Data summarisation, Data analysis, Data visualization, Communication of analytical findings Source: Gamage (2016) Universities in Vietnam might combine managerial accounting, finance, or information systems tracks, which allows accounting students to specialize in another area of interest. Data analytics could be incorporated into the information systems track or be a separate track of its own. The accounting department will have not the resources to teach these subjects. Consequently, the accounting department should coordinate with other departments, such as banking and finance department, information technology department, and so on. The Macquarire univesrsity (Australia) have suggested three noticable tips for teaching big data in accouting departments: Tools focus where students learn how to extract data using machine learning techniques and to conduct automated analysis using a new generation of tools beyond the spreadsheet, including (but not limited to) Microsoft Power BI, Google Spreadsheet and Fusion Tables. Text analysis tools help pinpoint emotional signals from word patterns and phrases to determine any hint of insider trading. By providing access to different tools, students can determine which are best suited for controls testing or visualising fraudulent claims. Non-financial large data sets are part of essential weaponry to develop big data accounting skills. Such data includes website data from Google Analytics or even video footage from a drone conducting an inventory of goods in one space. The data sets need not be big in terms of millions of rows of data - thousands of rows are adequate to teach the concepts. Building predictive data analytic skills through hands-on work, with tools and data to not only solve problems but explore large data sets to check first-hand for any useful discoveries amongst the data. For example, using big data instead of trend historical data and looking at each customer to predict whether the customer will pay or not is an ideal use case for introducing accounting students to predictive analytics. Vietnamese universities might consider these suggestions when they built up their own big data and accounting curriculum. 479 4. Conclusions Big data has a significant impact on accounting and auditing. By using non- traditional data such as URL tracking, body language, transaction history, and real-time data makes accounting operations more accurate and effective than the traditional approaches. Furthermore, big data also creates new requirements in accounting, specifically setting the requirements for data asset valuation. This makes the accountants and auditors need to be equipped with the knowledge of big data and data analysis skills. Currently, accounting training programs in Vietnamese universities do not have knowledge and skills related to big data. Consequently, Vietnamese universities and educational institutions need to update their curricula so that graduates can meet the needs of employers. Further research might be conducted to construct the accounting and auditing curricula with big data knowledge and data analytic skill included that appropriate with Vietnam markets. 5. References ACCA (2013), “Big Data: its power and perils” ACCA and IMA Report (2016), Professional accountants – the future: Drivers of change and future skills Bholat, D. (2015), ‘Big data and central banks’, Big Data & Society, 2(1), 2053951715579469 Islam, M.A. (2017), “Future of Accounting Profession: Three Major Changes and Implications for Teaching and Research”, Business Reporting, available online at https://www.ifac.org/global-knowledge-gateway/business-reporting/discussion/future- accounting-profession-three-major Gamage, P. (2016). Big Data: are accounting educators ready?, available online at https://researchbank.acu.edu.au/cgi/viewcontent.cgi?referer=https://www.google.com.vn/& httpsredir=1&article=1858&context=flb_pub Rezaee, Z., & Wang, J. (2017). Relevance of Big Data to Forensic Accounting Practice and Education: Insight from China. In International Conference on Accounting and Finance (AT). Proceedings (p. 103). Global Science and Technology Forum. PwC (2015) “What students need to succeed in a rapidly changing business world?” available online at https://www.pwc.com/us/en/faculty-resource