Handbook of Big Data and Analytics in Accounting and Auditing

The chapter aims to discuss impact of data visualization on auditors’ analytical procedures and propose practical approaches to address audit efficiency through data visualization techniques. To ensure that efficient presentation of data improves audit efficiency and effectiveness, it is essential that auditors are aware of and effectively apply data visualization techniques in auditing. This chapter presents more profound data visualizations applications in audit procedures that can assist auditors in finding data discrepancies for improving audit risk management through insight development capacity. Further, this chapter considers numerous data visualization analysis tools that audit professionals can use in their specific audit procedures. Finally, this chapter provides avenues for future research in audit data analytics and recommends future research that will allow auditors to realize how technology-driven data visualization tools interact with the audit's standard features.

There are many potential factors that are causing challenges in using emerging technologies in accounting and auditing in developing economies. This study focuses specifically on the transitional emerging economy of Vietnam and just some of the factors are discussed that have been identified as limiting the implementation and usage of emerging technologies in accounting and auditing. To focus on this aim, prior literature was used to collate, summarize, and analyze studies, which broadened the usual goal of directed content analysis, which is to extend theory. The strategy of selecting relevant articles (both academic and from practice) to be reviewed, consisted of a combination of the main concepts of the challenges in using emerging technologies in accounting and auditing. As research relating to emerging technology is still gaining prominence, where necessary, online searching for supplementary information were accessed from the websites of accessible sources such as the ‘Big Four’ audit firms and professional accounting bodies. We report that in this developing economy, in the Vietnamese context, there are some major challenges we believe are significantly related to emerging technology adoption and usage in the accounting and auditing fields.

We develop a new methodology for computing environmental, social, and governance (ESG) ratings using a mode of artificial intelligence (AI) called machine learning (ML) to make ESG more transparent. The ML algorithms anchor our rating methodology in controversies related to non-compliance with corporate social responsibility (CSR). This methodology is consistent with the information needs of institutional investors and is the first ESG methodology with predictive validity. Our best model predicts what companies are likely to experience controversies. It has a precision of 70–84 per cent and high predictive performance on several measures. It also provides evidence of what indicators contribute the most to the predicted likelihood of experiencing an ESG controversy. Furthermore, while the common approach of rating companies is to aggregate indicators using the arithmetic average, which is a simple explanatory model designed to describe an average company, the proposed rating methodology uses state-of-the-art AI technology to aggregate ESG indicators into holistic ratings for the predictive modelling of individual company performance.

Predictive modelling using ML enables our models to aggregate the information contained in ESG indicators with far less information loss than with the predominant aggregation method.

This chapter analyses the potential impact of Artificial Intelligence on the opportunities to measure ESG, and the climate in which regulations of ESG disclosures are being set. To date, while many ratings agencies provide estimates of overall corporate ESG scores, the scoring systems lack accuracy. Several problems with the current ESG rating approach are identified and the prospect of using Artificial Intelligence to resolve them is discussed. In concluding the chapter, the use of Artificial Intelligence to predict deficient sustainability reporting practices caused by behavioral issues relating to incentives to improper sustainability reporting is identified.

This chapter examines environmental aspects of ESG and risks and opportunities for using big data (BD) and artificial intelligence (AI) to capture these in ESG ratings. It starts by outlining the difference between relative and absolute sustainability and what this means for delivering on globally agreed upon targets, such as the Sustainable Development Goals. We then look at what the state-of-the-art climate and Earth System science has to offer investors interested in absolute environmental sustainability. Next, we discuss the risks associated with a blurring of concepts relating to sustainability and materiality, and examine and contrast conventional ESG rating procedures with new approaches informed by BD and AI to understand what this new generation of tools can offer investors interested in sustainability. We note a current misalignment between stated ambitions of investors, and the ability to deliver on stated goals through the use of current ESG metrics and ratings. We therefore finish with suggestions for how to better align these and how those interested in ESG can become more ‘sustainability savvy’ consumers of such ratings.

Bookkeeping and accounting is a prevalent feature of small organizations, which has changed face quite substantially with the advent of personal computers and, later, the Internet. The emergence of digitalized accounting procedures has taken place in a nexus of different types of actors (e.g., software developers, accountancy firms and the businesses themselves), regulatory frameworks (e.g., bookkeeping laws and accounting standards) and technical frameworks (e.g., standards for software interactions with banks and tax authorities). Altogether, this has made the paths taken in this process to be largely national. In general, this process of digitalization is largely undocumented and untheorized in research despite its profound impact on practice. Against this backdrop, this chapter has a descriptive and forward-looking approach, documenting the case of how Swedish bookkeeping practices of small organizations became digitalized, which can work as a reference case for comparisons with other national contexts.

This chapter presents a descriptive literature review-based research on cloud accounting that published during 2013–2019 to make a comprehensive analysis of the current discourse and impact of cloud accounting in China. This chapter is organized to answer three questions: (a) how cloud accounting a new business model in China, (b) how does cloud accounting influence the business in China and (c) what the accountant’s perspective in China is on emerging accounting technology. By comparing the cloud accounting with traditional accounting, we answered the first question. In the second question, this chapter explains from the perspective of opportunity and risks. In the third question, this chapter analyzes perspectives from accountants on accounting discipline and accounting work. All the influence and characters of cloud accounting mentioned in this chapter are all based on Chinese social and institutional background. This chapter promotes the exploration and innovation of the basic theory of accounting informatization and provides a theoretical basis for Chinese enterprises to use cloud accounting.

There is an increasing need to recognize the opportunity of blockchain technology beyond cryptocurrencies, such as bitcoin, and instead consider its potential as a technology forming part of the tax regulatory framework. We consider the potential for blockchain technology to play a digital infrastructure role for corporate tax loss compliance in Australia: a “RegTech” solution. In doing so, we identify the key features of blockchain and key use cases across numerous business sectors, then examine the role and function of blockchain in the context of corporate tax losses, where complex carry forward rules (e.g. continuity of ownership, business continuity tests) apply to avoid the erosion of government revenues. We find that in theory, blockchain could enable key efficiencies in tax compliance of corporate tax losses; however, the complexity and discretion within tax law creates real barriers for an effective blockchain solution. We conclude that blockchain offers an ability to track and flag resource allocation to broad, high level elements of the corporate tax compliance. It therefore offers potential for the greater digital ecosystem; however, it does not offer a solution in isolation. As the world progresses towards increased digitalization, this use case highlights the need for continual reflection of complex regulations and high levels of discretion, whilst balancing taxpayer rights, equity and fairness. Through digitalization, we may see increasing simplification for innovations to thrive and digitalization to meet the needs of a digitalized economy.

This chapter discusses aspects of data sources for budgeting and forecasting. It provides empirical evidence on the preference for data sources for a sample of experienced managers in the context of sales predictions. The authors show that managers still have strong preferences for traditional accounting data sources relative to non-traditional data sources. These preferences change between levels of education. Furthermore, the credibility (and not their use) of social media positively influences the preference for non-traditional data sources. These findings indicate that non-traditional data sources appear to coexist and become complementary to traditional accounting sources and do not substitute them.

With world’s population projected to grow to 9.7 billion in 2050, the demand for food and water will increase drastically. When population increases it also raises consumption and waste, managing waste can be more challenging. If urgent actions not taken, global waste is expected to increase by 70%; to an estimated 4 billion tons by 2050, projected by the World Bank. Further, the link between humanity’s impacts on ecosystems and biodiversity, and the rise of emerging and certain diseases, such as the novel coronavirus (COVID-19) shows the severity. This chapter seeks to further understand and explore how the use of emerging technologies such as the Internet of Things, Big Data Analytics and Artificial Intelligence can accelerate the progress on the 17 UN Sustainable Development Goals (SDGs). Brief case studies based one documentary evidence are presented to capture how technologies can create solutions in the areas of smart waste management, water management, and agriculture and farming. Since IoT has offered the opportunity to digitize many operations that can bring many benefits, it can help combat climate change and protect the environment. For instance, IoT can be used to develop smarter and more effective ways of managing and reducing waste. IoT could also impact the sustainability of the planet in different areas, such as water use, water efficiency and harvest productivity. The technologies discussed provide the opportunity to drive success and accelerate the progress of attaining many of the SDGs such as SDG 2, 3, 6, 9, 11, 12, 13, 14, 15.

As transparency and accountability demands around Environmental, Social, and Governance (ESG) risk control and reporting increase, pressure is mounting on organizations to act as good corporate citizens. One avenue to meet these challenges is to integrate ESG risks into Enterprise Risk Management (ERM) in order to improve control and reporting. The aim of this chapter is to examine ESG risk integration by focusing on: (1) How ESG risk is integrated with control, i.e. incorporated into strategic and operational decision-making; and (2) How ESG is integrated into reporting, i.e. incorporated into financial and sustainability reports. Our analytical framework conceptualizes integration as a technical-social process, which has three integrating dimensions and five integrating components. We use a qualitative approach and conduct short case studies in four ESG leading Swedish organizations. The study finds that social processes are important in ESG integration and lead to increased integration on the cognitive dimension. Findings also show how technical processes support social processes, however the use of Artificial Intelligence (AI) in ESG risk management in the organizations is low, as is internal audits role in promoting ESG risk control effectiveness and reporting quality. As this is a nascent area that connects risk management, management control, and financial accounting concepts, future research should engage with leading organizations to better understand the relationships between these concepts to advance theoretical development and create practical insights useful for practitioners.

Digitalization has become increasingly important over the years because of the potential opportunities and advantages it offers, both in terms of organizations’ management and performances and various stakeholder relationships. If integrated with management accounting systems, these benefits—derived from the implementation and use of digital tools—can increase. However, it is argued that there is still a long way to go, especially in the public sector. There is no clarity about the degree of digitalization and whether public sector organizations are prepared to implement digital tools in their management control systems (MCS). Therefore, this chapter, through a systematic literature review, aims to clarify how the implementation of digital tools influences the MCS of public sector organizations. The literature review reveals few studies on such topics for the public sector, which has a greater need of quantitative and qualitative studies. Furthermore, although the internal and external benefits associated with the use of digital tools in MCS are recognized, such tools seem to have an unexpressed potential in the public context. This chapter also adds to the knowledge of both practitioners and academics as it unveils a lack of innovative technical solutions that can support MCS and its integration with digitalization, which should be strengthened to improve decision-making processes.

In this big data age, it is imperative to replace the traditional data analysis techniques with big data analytics that can deal with both structured and unstructured datasets from various sources. This study's goal is to provide a method for analyzing unstructured data such as online customer reviews of mobile bank app to better understand customer perceptions. For analyzing customer online reviews, this study makes use of a text mining technique. Pre-processing of the extracted review data, analysis of the sentiment of each review, and an understanding of customer perception and evaluation are all part of the research process. This has come up with some important findings—when looking at it from the perspective of the customer, it was possible to determine which aspects of the app-based banking service are most important to them. As a result, service interruptions can be detected and avoided earlier, resulting in higher customer satisfaction levels. IBBL's bank management should focus more on expanding mobile banking's network reach from a practical standpoint. In order to prevent service failures, they can set up a systematic complaint management system that will allow them to identify and address customer complaints early. In this paper, we use sentiment analysis, one of the text mining applications, to measure service quality using customer reviews of a mobile bank.

This paper provides a guidance note to accounting educators seeking to incorporate applications of blockchain technology (BT) into accounting curricula. This paper is based on review of recent blockchain related publications in the accounting domain. It explains the areas of blockchain relevant to the accounting profession and provides a list of potential topics for inclusion in the accounting curriculum. Potential academic and industry resources that can be used to develop BT materials for integration into the accounting curriculum are also outlined. Being motivated by the need for the accounting profession to update their blockchain-related awareness and skills to meet the expectations of the accounting industry, this paper will help accounting educators as a guidance note in curriculum design and developing their course materials. This paper represents a reference for accounting educators tasked with incorporating emerging technologies into the accounting curricula to prepare work-ready graduates for the rapidly changing accounting profession.

The idea of technologically enhanced pedagogy, such as digitized simulation and gamified authentic assessments, in higher education is relatively new but offers the potential to revolutionize classroom delivery. This paper is designed to provide insights into curriculum designs and student responses to the use of innovative assessment in accounting education. This research examines how digitized simulation and serious games can enhance student engagement and help to address cognitive load challenges experienced by students. This paper also provides a case of detailed, practical insights for academics interested in digitizing and gamifying pedagogy for learning, while citing the benefits of serious game use in verifying assessment authenticity.

This chapter explores how to integrate the in-demand soft skills with the hard skills of financial analytics in an experiential roleplay. Specifically, it examines the impact of the experiential roleplay on MBA students’ self-perceived interpersonal skills. Designed using the experiential learning principles for students to practice and reflect, the roleplay is found to improve students’ self-perceived interpersonal skills in all 28 survey items except intercultural sensitivity. OLS regressions using the pre-roleplay data show students with longer work experience rated themselves higher for interpersonal skills. However, after the roleplay, difference-in-difference analysis indicates the outcome of the interpersonal skills is not affected by the length of work experience. It implies that students with less work experience did not have a lower level of self-perceived interpersonal skills than peers due to the intervention. This chapter contributes to the literature on self-efficacy theory by providing empirical evidence that roleplays can supplement real-world experience in interpersonal skills development. It offers important insight for educators that work-integrated authentic learning can improve students’ self-efficacy and job readiness.

The accountancy profession is now challenged by the pace of technological advancement and the ubiquitous digitalization leading to data explosion and advanced analytics. Digital technology is also replacing mundane tasks and manual work which accountants undertook in the past. Besides data analytics skills, accountants now need to possess critical thinking skills, knowledge of data science tools and communication skills. Consequently, equipping accounting professionals with data analytics skills is critical. Professional accounting bodies address this need by emphasizing continuing professional education and developing guidelines for data analytics. At the same time, higher education institutions are taking the initiative to integrate data analytics into their accounting curricula. However, given the numerous professional accreditation requirements that higher education institutions must fulfill, a big challenge remains for any institution to insert rigorous data analytics training into their existing curriculum. This chapter describes the development of a data analytics roadmap for undergraduate accountancy education—from reviewing our academic and industry data analytics curricula and evaluating existing modules that could be integrated with relevant data analytics topics, to seeking feedback from industry partners regarding the curriculum model we had developed. In delivering our curricula across the levels of study, a spaced retrieval teaching technique was opted to ensure that students could progressively develop data analytics competencies.

Learning Analytics was recognized to be “the third wave of large-scale developments in instructional technology”. Learning Management Systems (LMSs) have been widely adopted as the learning analytics tools because the captured data represents how the learners’ interact with the system during formal learning. However, most LMSs’ analytics models do not capture learning activities outside the systems. We built an integrated Telegram mobile application and a web-based portal discussion forum, to enable informal, participatory and collaborative learning beyond the classroom. We analyzed student-initiated question-and-answer discussion posts where our machine learning algorithm will predict the quality of the posts, and the system will prompt the students to improve their posts. With six in-built engagement features, our system generated higher number of high-quality posts, resulting in better learning outcomes among the students. Based on three implementation runs in an undergraduate course, our results show that there were positive correlations between post quality and student assessment outcomes. Students who used the system could achieve higher knowledge gain, and in-class intervention by the course instructor to review the weekly discussion posts will further improve knowledge gain. Mandatory participation benefitted the academically stronger students, while academically weaker students will need positive intervention actions when mandatory use of the system is enforced. We envisage that our system can be a successful alternative for workplace learning and ultimately contribute to organization knowledge creation. Using the system, working professionals can post questions and answers shared among peers within their own organizations and learn through such informal discussions, which can be blended seamlessly in their day-to-day workflow. While our system has not been implemented in workplace learning, we attempt to draw inference from our implementation results, to understand the parallels in the business organization context.

The phenomenon of digitalization has spread in the field of education and research, as demonstrated by the digitalization of teaching and training methods, the use of digital technologies for conducting research and the spread of the concept of the ‘digital university’. One of the main expectations is that digitalization can improve the performance of universities, supporting the delivery of more efficient and effective services. Nevertheless, the relationship between digitalization and performance measurement and management has so far been under-investigated. This chapter studies how this relationship has been addressed in the academic debate by conducting a review of the literature on the topic. The analysis of the literature allows the identification of key themes, both previously studied and future research areas. The findings show that, in most cases, attention has been paid to the effect of the use of digital tools on (student) performance by investigating the adoption of digital teaching/learning tools and resources. Next, attention has been directed to the use of digital tools to measure the performance of universities. However, digitalization does not concern only tools, but it implies changes in the language used in universities, calling for further research on the costs and benefits of digitalization, going beyond the technicalities of digital tools to investigate performance and changes in academia as a result of the digitalization of the language.

Managing household waste has become a real problem in Australia. One solution is to deal with this dilemma with a circular economy model of waste management; encompassing the repair, reuse and recycling of materials to get as much use out of waste material as possible, identified as a priority for the Victorian State Government. Households play a critical role in all stages of waste management, including reducing, reusing and recycling their waste materials. Research shows undertaking such measures has a dramatic and material impact on the generation of such household waste. This chapter describes a project aimed at evaluating an online interactive training-tool designed to increase awareness of effective household waste management (HWM) strategies. The waste management training-tool will be free and made available to Australian households in Victoria through their mobile phones. The Rasch psychometric model will be used to assess the impact of this waste management training-tool, to provide expected percentages of behavioral improvement.

Taxation undergraduate students in Wales, Singapore and China experienced virtual reality (VR) in their learning of taxation, where a real-world capital allowances scenario supported student learning of the topic. Experiential learning can help students improve their understanding of the subject and gain valuable skills for employment or further studies e.g. professional qualifications. Virtual reality is an immersive learning experience that can help students improve their understanding. As a visual learning approach, students are more likely to be able to recall their visual experiences. VR has the benefit of participators experiencing “presence” in their learning, putting themselves in the virtual world making it a memorable and often an enjoyable experience. This study compares student perceptions from students at each of the three universities using a voluntary questionnaire, accessed via a QR reader, before the VR session to capture their knowledge and use of technology plus their thoughts on using VR for learning. A further questionnaire after the VR session captured student’s thoughts on their VR learning experience, did they enjoy the experience, did it help their understanding, and would they like to use it more in their studies? A summary of the results demonstrates the majority of students indicated: they were positive about using VR for learning; VR enhanced their learning experience; VR improved tax understanding; They enjoyed using VR; and they would like to see more VR in their studies.

Blockchain technology (BT) has been receiving increasing attention from the academics and practitioners, in terms of its emergence, evolution, transformation, potential disruptions, technical aspects, and implications on accounting, auditing and finance practices. Through a review of the 51 papers published from 2015 to 2021 in Scopus indexed academic journals in accounting and auditing. Based on the analysis of the selected papers, this chapter charts the current knowledge on BT, examines key themes identified from the literature, and recommends opportunities for future research. The chapter finds that the innovation and ensuing disruption of BT is still in an emerging phase, particularly the scope and influence in the accounting, auditing, and finance practice and research. The findings of this chapter can be used by the key stakeholders involved in professional practice in the accounting and auditing domain. The chapter offers avenues for future research seeking to develop theory and align theory-practice.