Audit Data Analytics Research Articles

Enhancing quality in same-day emergency care: a service improvement perspective

Background: Same-day emergency care (SDEC) units were introduced in the UK in response to growing numbers of emergency department visits. Key quality indicators for their performance include timely assessment, diagnosis and treatment to reduce delays and optimise care delivery. Aims: This article presents the findings from a multi-cycle service improvement project undertaken at a regional SDEC unit from the perspective of the advanced clinical practitioner (ACP). Methods: The SI project adopted an array of SI methodologies, including the Plan, Do, Study, Act model, process mapping and audit data analytics to identify and reduce variance in patient care. Results: The project identified the importance of adopting a whole-system approach to clinical leadership to improve the care experience of patients and staff. Success is highly dependent on the availability of a confident and skilled workforce to provide high-quality patient care. Conclusions: As demands on emergency health services continue to grow, the ACP is in an ideal position to adapt to change and generate innovative solutions to address capacity issues.

Effort Audit Analytics System Using Power BI & DAX

Abstract— My project involved building a learning module system using Power Bi and DAX. Our team was responsible for developing the Effort Audit Data Analytics, which manages and makes it possible, at your fingertips, to gain the competitive advantage of being on track for the field staffs of Pharma, Animal Health and Baby Care .Effort Audit data allows you to gain a deep understanding of how users in your organization are using Power BI. In turn, your ability to educate and support users can improve dramatically The Effort Audit Analytics data can help organization measure whether their implementation is aligned with their goals or becoming a more data-driven organization.

Do Audit Data Analytics Influence Juror Perceptions of Audit Quality and Auditor Negligence?

SUMMARY We summarize a recent study that examines whether and how the signals provided by the internal control over financial reporting (ICFR) opinion and auditor use of advanced data analytic tools (ADAs) influence juror negligence perceptions. When auditors issue an unqualified ICFR opinion and rely on traditional statistical sampling, jurors assess the auditors as more negligent than when the auditors use ADAs. Conversely, when auditors issue an adverse ICFR opinion, jurors ascribe less blame to auditors and more to investor plaintiffs, regardless of whether the auditors use ADAs. Further, jurors perceive auditors as less negligent when they use ADAs for full population testing because they perceive ADAs to be an indicator of higher audit quality. Interestingly, jurors perceive no difference in the level of assurance provided by the audit opinion alone when auditors use ADAs relative to traditional sampling testing methods.

Integrating data analytics into the auditing curriculum: Insights and perceptions from early-career auditors

This study aims to help audit educators determine how, where, and to what extent audit data analytics (ADA) should be integrated into existing auditing curriculum to better prepare students for the auditing profession. We interview early-career auditors to understand their experience with ADA and add their perspective to the literature on audit curriculum changes. This group performs many of the tasks where ADA techniques would be applied and can provide valuable insight to audit educators based on their work experience and recent completion of auditing and/or data analytics courses. Responses indicate that early-career auditors rely more routinely on traditional ADA tools (e.g., Excel) and that the use of advanced ADA tools (e.g., Power BI and Alteryx) is relatively limited. Furthermore, firm-provided training on advanced ADA tools focuses on navigating tools rather than interpretation of ADA output. We also find that, regardless of the ADA tool used, the skillset used most frequently is interpretation of ADA output to identify anomalies and determine the impact on audit testing, which could be emphasized in existing audit courses. Most participants expressed that rather than removing content from the audit course to make room for data analytics, faculty should integrate ADA within existing content, encouraging audit educators to change how they teach, rather than what they teach. Specifically, faculty can provide hands-on examples of ADA to supplement lectures on existing topics or assign case studies that use ADA tools. These findings have implications for immediate changes to integrate ADA into auditing courses that are more manageable than a complete overhaul of the audit curriculum.

Empirical research frameworks in a changing world: The case of audit data analytics

Advances in data analytics is fundamentally changing the field of auditing. The primary objective of this paper is to develop a holistic, multidimensional framework to better understand the dynamics of the diffusion of audit data analytics (ADA). The framework we developed covers categories related to the diffusion of ADA (the technology, the actors using it, and the external rules that regulate it) and the actors reproducing the rules and technologies (focusing on the audit and cognitive processes). We analyze the key findings from 40 empirical studies within and across the interrelated categories of the framework. The findings emphasize that a better understanding of auditors’ judgment and decision making (cognitive processes) is fundamental for a study of the diffusion of ADA. Primary drivers of fundamental changes include audit quality, audit efficiency, and the expectation gap. Our results suggest that ADA competencies should be a professional priority. In addition, conceptual issues (the audit risk model, audit evidence, and audit assertions) and materiality considerations need to be resolved. A solution for these problems is a prerequisite for in-depth changes to audit standards, which in turn will also open the door to the diffusion of ADA.

The impact of audit data analytics on audit quality and audit review continuity in Thailand

PurposeThe main objective of this study is to examine the impact of audit data analytics (ADA) on audit quality (AQ) and audit review continuity (ARC).Design/methodology/approachUsing 452 CPAs in Thailand as samples, mail questionnaires were used and sent to collect the data. Descriptive analysis, correlation matrix and path analysis were used to analyze the data.FindingsThe results of this study indicated that audit data analytics had a positive impact on AQ and ARC. Cybersecurity, used as a moderator in this study, was found to be the interaction between ADA, AQ and review continuity.Practical implicationsAuditors and audit firms can consider using big data in their data analytics to improve AQ and ARC.Originality/valueResource advantage theory has been used in this study to explain the impact of ADA on AQ and ARC in Thailand.

Less Is More: An Outsider Perspective on Audit Data Analytics

Less Is More: An Outsider Perspective on Audit Data Analytics

Internal Auditor Competency Gap: Perception Of Students, Academics And Practitioners

The purpose of this study is to investigate internal auditor competency gap by comparing the perceptions between students, academics, and practitioner. Questionnaires were sent to 1009 respondents who meet the criteria using google form. The questionnaire was divided into two parts. The first part, we ask respondents’ perception related with hard skill needed by internal auditor, the second part discussed soft skill required to prepare agile and adaptive internal auditor. This study found two main gaps between three groups of respondents. First, there are competency gap related to technology and emerging risk. Internal auditor must update with agile audit methodologies and data analytics. The universities must enrich the internal audit course with current audit method and data analytic skills. Second, all respondents put emphasis on soft skill more than hard skill, therefore important soft skill for auditor should embedded in curricula. Academics and practitioners agree that hard skill competencies specially related with performance standards as mentioned on international standards is important knowledge that should possessed by internal auditor to performed internal audit role comprehensively.

THE INFLUENCE OF INTERNAL AUDIT, RISK MANAGEMENT, WHISTLEBLOWING SYSTEM AND BIG DATA ANALYTICS ON THE FINANCIAL CRIME BEHAVIOR PREVENTION

This study provides a critical review of the literature that examines and analyses how Fraud Prevention mediates the Effect of Internal Audit, Risk Management, Whistle Blowing System and Big Data Analytics on the Prevention of Financial Crime Behaviour. The problem discussed in this study is the limited strategic formulation in risk management, internal audit, whistleblowing system and big data analytics for early detection for fraud prevention and prevention of financial crime behavior in Indonesia, especially the problem of fraud that occurs in the Sumatra Regional Government, namely in Aceh, North Sumatra, Riau, Kepulauan Riau, South Sumatra, Bangka Belitung, Jambi, West Sumatra, Bengkulu and Lampung. Various kinds of scientific studies that have been carried out provide clues that the skills mismatch on the impact of fraud and financial crime behavior is still a fundamental polemic that will continue to hamper the productivity and competitiveness of various economic and industrial sectors in Regional Governments in Indonesia. To prepare for the emerging discourse, this research refers to 90 articles published in leading academic journals, discussing related topics from the early 1990s to 2021. Therefore, the formulation of the problem in this study: (1) How does Internal Audit influence prevention fraud, (2) How does Risk Management influence fraud prevention, (3) How does Whistleblowing system influence fraud prevention, (4) How big data analytics influence fraud prevention, (5) How fraud prevention mediates the influence of Internal Audit, Risk Management, whistleblowing system and big data analytics to prevent financial crime behavior.

Text Visual Analysis in Auditing: Data Analytics for Journal Entries Testing

Business transaction data includes numeric values of the transactions and the date/time when the transactions are recorded, and textual data such as descriptions. Understanding the textual information of business transactions is also important since this information captures the nature of transactions in a qualitative manner. This study proposes a text visual analysis approach for auditing. We argue that combining text analysis and data visualization can improve the efficiency of audit data analytics for textual data in the organization's accounting information system. We provide a demonstration of the proposed method using a year-around general ledger data set. We use data visualization software Orange and Tableau for the demonstration. The proposed method can be used to understand a client's business and identify abnormal or unusual transactions from not only quantitative information but also qualitative information.

Audit data analytics, machine learning, and full population testing

Emerging technologies like data analytics and machine learning are impacting the accounting profession. In particular, significant changes are anticipated in audit and assurance procedures because of those impacts. One such potential change is audit sampling. As audit sampling only provides a small snapshot of the entire population, it starts to lose some of its meaning in this big data era. One feasible solution is the usage of audit data analytics and machine learning to enable an analysis of the entire population rather than a sample of the transactions. This paper presents an approach for applying audit data analytics and machine learning to full population testing and discusses related challenges.

The emergence of audit data analytics in existing audit spaces: findings from three technologically advanced audit and assurance service markets

PurposeThe purpose of this exploratory study is to better understand the interactions between external auditors, their audit clients and audit regulators when considering the supply of and demand for high-level audit technology. The authors examine the developed markets of Australia, New Zealand and the UK to better understand: how high-level audit technology has started to become embedded into existing audit spaces and any emerging issues this technology has created for the audit profession.Design/methodology/approachThrough the theoretical lens of the socio-technical (ST) systems of innovation theory, the present study involved semi-structured interviews with 25 stakeholders in Australia and New Zealand from 2019 to 2020 and 21 stakeholders in the UK from 2016 to 2018.FindingsAdvancements are revitalizing the technologies of not only the external auditors and their firms but also of their audit clients. Although the audit model is changing, external auditors are reported to be reluctant to fully engage with new audit technologies. In this setting, the authors find audit rules are yet to become embedded in the objects or practices of ST systems and that keeping up with the pace of change for regulators and standard setters is a major challenge.Practical implicationsThe findings of this study raise call for regulators to be more up to speed with these new technological changes, as audit standards need to be amended accordingly. Although the International Auditing and Assurance Standards Board deliberates, both clients and auditors need to lobby for specific audit data analytics regulations.Originality/valueThe present study provides perspectives about new audit practices that emerge due to high-level technological advancements and then embed themselves into existing audit spaces. The authors draw on several different stakeholder groups, not just the Big Four firms. The ST systems theoretical lens we adopt better helps us understand how audit firms at the organisational level are adapting to these new technological changes in existing audit spaces.

Behavioral challenges to professional skepticism in auditors’ data analytics journey

The aims of this paper are to inform audit practice and academia about the potential behavioral challenges to the application of auditors’ professional skepticism when using audit data analytics (ADA) and to discuss future research opportunities. This is accomplished by reviewing relevant audit research and discussing the potential challenges from five perspectives, including auditors’ attitudes toward ADA, data characteristics, anomalies identified by ADA, auditors’ mindsets, and social contexts and interactions involved in ADA practice. Although applying ADA brings many benefits to audit practice, they simultaneously raise many challenges to the application of appropriate levels of auditor professional skepticism. Being aware of and prepared for those potential behavioral challenges is critical to maximize the benefits of ADA to professional skepticism and ultimately audit quality.

Audit Data Analytics, Machine Learning, and Full Population Testing

Audit Data Analytics, Machine Learning, and Full Population Testing

Adoption of Audit Data Analytics - The Moderation Effect of Audit, Firm Size, and Voluntariness to Use

The study is one of the first empirical studies that focuses on the evolution of BDAs in the auditing field. This study aims to examine the moderation effect of audit firm characteristics such as audit firm size and voluntariness to use have on the relationships between the factors affecting auditors’ ATT towards using ADAs. The study is supported by the TAM model and the UTAUT model. A survey is the main research instrument used in the current study; the survey is administrated on Google forms and in direct collect form as well. The data examined for both Big4 and Non-Big4 auditors and the results shows mixed significance level for the different variables.

The Effects of the Internal Control Opinion and Use of Audit Data Analytics on Perceptions of Audit Quality, Assurance, and Auditor Negligence

SUMMARYAudit data analytics (ADAs) allow auditors to analyze the entire population of transactions that has measurable benefits for audit quality. However, auditors caution that the level of assurance on the financial statements is not incrementally increased. We examine whether the testing methodology and the type of ICFR opinion issued affect jurors' perceptions of auditor negligence. We predict and find that when auditors issue an unqualified ICFR opinion, jurors make higher negligence assessments when auditors employ statistical sampling than when they employ ADAs. Further, when auditors issue an adverse ICFR opinion, jurors attribute less blame to auditors and more blame to the investor for an audit failure. Additionally, jurors perceive the use of ADAs as an indicator of higher audit quality and are less likely to find auditors negligent. However, jurors do not perceive a difference in the level of assurance provided when auditors use ADAs versus sampling testing methods.

Readiness Analysis of Data Analytics Audit Implementation in Inspectorate General of the Ministry of Finance: An Indonesian Case

Organizations including public sector organizations are required to utilize data optimally. Unfortunately, only 9% of organizations in the world use data analytics properly ( Meulen and McCall, 2018) . The Ministry of Finance has a lot of potential data and is the only internal control organization in Indonesia that has initiated the audit data analytics scheme on the roadmap in 2019. This study aims to measure the readiness of audit data analytics implementation reviewed from general to specific. To achieve this objective, this study conducted using qualitative method where the informants were selected based on purposive sampling involving 20 speakers consisted of auditor, supporting unit, auditee, and expert. This study use main model from Gürdür et al. (2019) based on the synthesis of the research study of Schuh et al. (2017) about Industry 4.0 Maturity Index. Then, this model has been elaborated to generate 4 categories, 8 aspects, and 15 criteria. These categories consist of resources readiness, information system readiness, culture readiness, and organizational readiness. The results show that [1] Generally, Ministry of Finance Inspectorate General has resources readiness at high level and other categories at medium level. [2] Specifically, based on two biggest process in Inspectorate General, namely tax audit and financial statement review, show that tax audit have a high level of resource readiness, and the others at a medium level, meanwhile the financial statement review has a high level of resources readiness and information system readiness, and the others at a medium level. [3] Gaps are caused by challenges both from internal and external organization.

A Picture is Worth a Thousand Words: Using Interactive Data Visualization to Assess Fraud Risk

ABSTRACT Accounting firms are making significant investments in audit data analytics technologies to modernize their audit services and the audit profession is believed to be on the verge of a transformation (BDO 2016; Deloitte 2016; EY 2015; Forbes Insights 2015; PwC 2015). In particular, the firms are emphasizing newer technologies such as interactive data visualization (BDO 2016; Deloitte 2016; PwC 2016) and they are increasingly expecting students to have data analytics skills (Forbes Insights 2015; PwC 2015). In this case you take on the role of Bryan, an audit senior assigned to Acme Company, who has been tasked with using interactive data visualization to gain an understanding of Acme's sales and perform an initial evaluation of two fraud risks identified during a fraud brainstorming session. Bryan has been given a data file with over 250,000 financial transactions and five master tables that he needs to analyze using interactive data visualization.

How well do audit textbooks currently integrate data analytics

The auditing profession is undergoing a transformation, becoming heavily reliant on computerized systems to produce data analytic reports. As a result, the demand for accounting graduates with knowledge in data analytics (DA) has increased. Because textbooks remain the primary educational resource in a college classroom, we sought to determine the extent to which textbooks include DA content and provide a summary of our findings to assist auditing educators in locating this content. Our primary analysis includes the examination of the six most commonly used audit textbooks and one book on DA for accountants. For each text, we evaluated (1) the degree to which textbooks have integrated current and emerging technologies into the written chapter content; (2) the degree to which auditing textbooks have students perform specific DA activities, using DA software; and (3) the degree to which these problems follow the AICPA’s five-step process for planning and performing audit DA. We also provide a Detailed Analysis section for each text in which we summarize both in-chapter and end-of-chapter DA exercises. Recognizing the large amount of DA resources available online such as case studies and datasets, we also provide a review and summary of this content, thereby providing auditing educators a wide variety of options for including DA in their classroom. Finally, based on our review of these resources, we provide recommendations for educators, textbook authors, and publishers to consider when developing DA educational materials. Our purpose is to contribute to the discussion on auditing curriculum and whether trends in practice are reflected in the course resources.

Incorporating an analytics mindset into the audit curriculum

Drawing on insights from recent academic and practitioner papers on audit data analytics (ADA), this paper explores the opportunities and resources available to auditing educators who are interested in integrating an analytics mindset into their curriculum. The aim is to improve auditing education by facilitating the incorporation of an analytics mindset into the auditing curriculum. This study highlights the impact of ADA on the audit profession and the challenges of applying ADA to the full range of auditing tasks. It also provides a comprehensive summary of readily available educational resources that audit educators can use to update their curriculum and enhance students' analytics competency.