Procurement fraud poses significant financial and reputational risks to organizations, yet existing efforts to address it are fragmented between academia and industry. While academic research has proposed sophisticated fraud detection models using machine learning and data analytics, these solutions often lack practical applicability due to limited guidance for practitioners. In this study, we address this gap by proposing a decision framework for procurement fraud detection, synthesizing insights from existing literature and a real-world data analytics project with a global brewing company. We identify three critical decision problems in developing fraud detection models: (1) constructing fraud indicators, (2) determining the aggregation level, and (3) selecting the model validation method. By evaluating alternatives for each decision, we offer practical solutions that organizations can tailor to their unique procurement processes and risk profiles. The proposed framework combines the knowledge from literature and practical insights, offering actionable guidance for practitioners while bridging gaps between academic research and industry practice. This study contributes to the field by formalizing decision-making challenges in procurement fraud detection and fostering collaboration between academia and industry.
This study examines how artificial intelligence (AI) compares with traditional econometric models in predicting audit risk across two institutional contexts: the United Arab Emirates (UAE) and the United Kingdom (UK). Using firm-level data from 2017–2024, audit risk is modelled using financial, governance, audit, and market factors. Logistic and probit regressions serve as econometric benchmarks, while Random Forest, XGBoost, and deep neural networks represent AI methods. Explainable AI (XAI) tools—such as SHAP and LIME—enhance interpretability and regulatory transparency. Findings show that AI models consistently outperform econometric ones in accuracy, recall, and AUC across both countries. Yet, key audit risk drivers vary: governance factors like board independence and ownership concentration dominate in the UAE, while financial indicators and Big 4 affiliation are more influential in the UK. Explainability tools clarify predictions, boosting trust and regulatory alignment. Cross-country transferability tests reveal lower accuracy outside the original setting, emphasizing institutional specificity. Overall, the study demonstrates that effective audit risk prediction requires locally adapted, transparent AI models that combine predictive strength with interpretability to enhance auditor and regulator confidence.
We employed a systematic literature review (SLR) to map the intellectual landscape of stablecoin research, categorising it into five critical areas: stability and volatility; use as a safe haven, hedge, or diversifier; the effects of stablecoin events on other cryptocurrencies; financial collapses of stablecoins; regulatory challenges. By investigating price stability mechanisms and factors leading to volatility, our study highlights how stablecoins interact with the broader financial market. We also explored their role in investment portfolios, the repercussions of their transaction activities on the crypto ecosystem, and the systemic risks leading to their collapse. Furthermore, we delved into the regulatory frameworks governing stablecoins, emphasising the evolving challenges and opportunities for regulatory integration. We identified significant research gaps, such as inconsistencies in stablecoin pricing data and undefined events affecting volatility changes. The SLR’s limitations include potential bias from the selected literature, suggesting future expansions to include more databases for a broader, more inclusive review. We concluded by proposing future research directions, focusing on stablecoins in business applications and the tax implications of their use, which are crucial for understanding their potential impact on global financial practices. Our investigation underscores the need for comprehensive studies on stablecoins, especially concerning their operational integration and tax-related policies in digital transactions.
In recent years, the use of blockchain technologies has increased. The aim of this paper is to analyse the current state of its use in major Western European companies as reported in their corporate reports. Using automatic extraction techniques, the relevant information is collected and classified according to different disclosure categories. The sample consists of 1,409 annual/sustainability reports, published in 2018, 2019, and 2020, by 337 companies listed on 13 Western European countries’ stock markets. Our findings show that, according to corporate reports, the use of blockchain is still at an early stage and the first adopters are large companies in the financial and technology sectors located in countries with a well-defined national blockchain strategy. An overview of this new phenomenon in European, as well as the way that large companies engage with this innovative technology, whether they report on it in their corporative report, the content type of such disclosure, and the factors associated with it.
This study explores the factors influencing the successful implementation of the Continuous Auditing (CA) system at PT PLN (Persero), an energy and electricity company in Indonesia, using the DeLone and McLean Information Systems Success Model. The research aims to understand the impact of System Quality, Information Quality, and Service Quality on System Use, User Satisfaction, and Net Benefits, addressing a gap in understanding CA in large organizations. Data were collected through structured surveys of PT PLN auditors and supplemented by insights from the development team. The findings indicate that Information Quality significantly enhances System Use and User Satisfaction. Accurate, relevant, complete, and current information supports decision-making and builds trust in the system. Service Quality, including training and responsive support, improves User Satisfaction but impacts System Use less. Conversely, System Quality, despite good reliability and usability, does not significantly influence User Satisfaction or System Use, suggesting that technical aspects alone do not drive adoption without meeting user needs. The study concludes that Information Quality and Service Quality are more critical for successful CA implementation. Recommendations include improving data accuracy, training, documentation, and response times. Future research should explore factors such as user perception and traditional audit preferences, to guide CA system development.
Energy transition and companies’ commitment to sustainability can be supported by integrating innovative technologies into the renewable energy (RE) sector. Blockchain technology (BT) represents one such technology. This paper explores how BT can support RE consumption as an answer to energy sector companies’ technological, transparency and traceability needs. We conducted a literature review on blockchain’s ability to adapt to the energy sector, focusing on RE applications. In addition, we qualitatively analysed two projects pursued by energy sector companies in Europe. Although there is an abundance of research on the application of BT in the energy sector, there are only a few operational studies on this theme. Therefore, we combined the theoretical analysis with an exploration of the practical application of BT in two actual developments that highlight its positive implications for the transition to RE. BT applications for RE are at an early stage and require time for development. The analysis invites interactions among academics, energy sector operators and legislators. The findings contribute to facilitate the RE adoption and greenhouse gas emissions reduction in compliance with 2030 and 2050 goals.
Most anomaly detection models are developed by using expert system methods that mimic human experts. The process to capture the expertise honed by fraud examiners is complicated and practically challenging, often resulting in suboptimal models. This study proposes a clustering-based model that captures hidden characteristics of potentially fraudulent wire transfers with less human intervention and expertise. Clustering methods classify and group observations with similar characteristics, excluding anomalies from major clusters. The choice of a clustering method and its parameters is often subjective and significantly affects a set of resulting clusters. In order to reduce the subjectivity of a clustering method while retaining its strength, this study proposes a clustering model with Density Based Spatial Clustering of Applications with Noise (DBSCAN) to detect potentially fraudulent wire transfers of an insurance company. The results show that the DBSCAN models identifies hidden relationships between the variables not only included but also excluded for the modeling with noise wire transfers while less human intervention is needed for clustering parameter selections.
This article examines the authorship origins of accounting information systems (AIS) and emerging technologies (ET) research from 2004 to 2021 in six journals: Journal of Emerging Technologies in Accounting (JETA), Journal of Information Systems (JIS), International Journal of Accounting Information Systems (IJAIS), International Journal of Digital Accounting Research (IJDAR), Accounting Information Systems Educator Journal (AISEJ), and Intelligent Systems in Accounting, Finance, and Management (ISAFM). This study contributes to the understanding of AIS and ET research by conducting a comprehensive analysis of 1,101 research articles published in these AIS journals by authors’ employer and doctoral country, employer institutions, doctoral institutions, doctoral disciplines, author type, and by AIS and ET classifications. The aim of this study is to identify the historically most productive and influential countries and institutions in the AIS and ET domain and to discover the educational and professional background of AIS and ET researchers, respectively. The findings of this study provide helpful information for job seekers, prospective Ph.D. students, researchers seeking co-authorship, and those interested in this literature and serve as a valuable supplement to the existing bibliometric analysis of AIS literature.
Aiming to assess the reliability of governmental accounting under an armchair-audit approach, we develop a framework to compare the financial reports submitted by municipalities to two different agencies: the Ministry of Finance and the respective Court of Accounts. We developed a framework using concepts of RPA in conjunction with OCR to download, extract, organize, and finally compare the reliability of the financial reports submitted by the municipalities. The results indicate that a framework of RPA is helpful to automate many tasks necessary to armchair-audit municipalities' financial reports. The results also indicate that many Brazilian municipalities submit inconsistent data to the monitoring agencies, i.e., the Ministry of Finance and respective Court of Accounts. Additionally, our findings suggest that more computerized entities are less prone to present inconsistencies in their accounting data.
The research investigated auditor’s Professional Skepticism (PS) mindset while auditing the “integrated financial statement” of green reputation clients in a technology enabled audit environment. The study tries to understand the difference in thought and action of auditors based on perception of their client as sustainability responsible or not. Subsequently, the study offers meaningful insights about the nuances that upholds this distinction. This research comprises two studies using the mixed method procedure as per Creswell and Clark (2017). The first study is a 2 x 2 between subject experiment. The second study uses the Theories in Use (TiU) methodology by analyzing qualitative interviews of practicing auditors in an emerging market setting. The findings of study 1 (comprising the experiment) highlight that auditors are more professionally skeptical while auditing clients with a green reputation. Study 2 (utilizing qualitative interviews) points out that technology assists the PS mindset by enhancing the audit effectiveness and audit efficiency of green client’s audit. The study offers an in-depth understanding of the level of auditor’s PS mindset toward clients with a green reputation, and therefore demystifies the inherent forces at play during such a phenomenon. Although the setting of the study is an emerging market, the study offers transferable findings to improve the overall understanding of auditor’s mindset. The study has implications for multiple actors engaged in the audit process, viz., auditors, audit firms, regulator of the audit profession, audit committees, academia, and policy makers.
Over the last decade, we have witnessed how new technologies, such as AI in the form of automation or machine learning, have proliferated in business processes. Although digitalisation has led to a significant increase in efficiency, it raises certain concerns related to privacy, data protection and other human rights, which might be at stake when huge amounts of data are being collected and processed or when AI is used for decision making. Digitalisation, apart from increasing efficiency, has a strong potential to contribute to sustainable development if responsibility and trust are guaranteed. Therefore, companies should critically reflect upon different ethical criteria to avoid compromising democratic rights and values when engaging in digitalisation. In our study, we wanted to draw attention to and increase awareness of an evolving area of corporate digital responsibility. In addition to the bibliometric analysis of the CDR literature, a summary of the definitions is provided.
The inevitable disruptions in the Fourth Industrial Revolution necessitates that companies provide investors with digitalization disclosure in integrated reports. This paper investigated whether digitalization disclosure in integrated reports affects the share prices of South African listed companies. The relationship between digitalization disclosure and share prices is examined using the Ohlson (1995) Model through the application of panel data. A new proxy for the “other information” variable in the Ohlson (1995) Model was created for digitalization disclosure by developing a disclosure index to measure the scope of digitalization disclosure in integrated reports. The disclosure index was incorporated into a new text analysis software named the Fourth Industrial Revolution Disclosure Analysis Tool (4IRDAT), which uses algorithms based on natural language processing techniques to facilitate the content analysis of digitalization disclosure in integrated reports. Two scenarios were evaluated: including loss-making companies and excluding loss-making companies. The sample size, including loss-making companies and excluding loss-making companies, was 90 (270 observations) and 72 (216 observations), respectively, for three years from 2018 to 2020. It was established that there was an increase in digitalization disclosure over three years. The results indicated that digitalization disclosure had yet to be incorporated in the share price of South African listed companies for both scenarios. This study is indispensable to regulators, practitioners, standard setters, and academics because it provides empirical evidence on the value relevance of digitalization disclosure in integrated reports. This area has not been interrogated in a South African context.
Blockchain is a decentralized information technology (IT) architecture that has garnered significant attention across various sectors of the global economy. In the banking sector, blockchain was initially used for cryptocurrency trading and later expanded to encompass smart contracts, peer-to-peer transactions, and other banking services. In recent years, blockchain technology (BT) has been applied to streamline less standardized credit processes and to successfully support mortgage credit through decentralized recording on ledgers. Employing a qualitative research approach, this paper proposes a novel business model for small banks that utilizes new-generation information technologies to enhance loan profitability. While previous research has linked BT to lending processes, this study is the first to propose a BT application for reshaping traditional banking practices, especially for commercial banks. The research findings demonstrate that blockchain implementation offers advantages in containing information asymmetries, managing credit rationing, and driving business innovation.
Blockchain, or distributed ledger technology, is acknowledged as the most significant and disruptive innovation in accounting since the double-entry system. All the ‘Big Four’ accounting firms and several major S&P500 companies have invested considerable resources in developing blockchain technologies. Some maximalists of this technology have even hinted that it will fundamentally change accounting and auditing if all transactions can be captured in an immutable blockchain. It is a daunting task for accounting academics to determine how to infuse blockchain in accounting curricula since the body of knowledge in this area spans several disciplines, such as, accounting, economics, finance, computer science, and engineering. It is also difficult for accounting practitioners to know what aspects of this technology are relevant to accountants for the same reason. In this paper, using the diffusion of innovation theory, I help explain why we need to incorporate the accounting-relevant aspects of blockchain in accounting curricula and practice and how we can accomplish that goal without introducing unnecessary technological complexity and jargon. I also provide eight case studies, which were successfully trialled by me at CPA organization/association conferences, that can be used to communicate the accounting relevant aspects of blockchain in the domains of accounting, tax, and audit services.
Gartner’s hype cycle of technology famously progresses from the “peak of inflated expectations” to the “plateau of productivity” via the “trough of disillusionment”. Accounting researchers and practitioners—like researchers and practitioners in many other fields—have jumped onto the blockchain bandwagon for fear of missing out on what has been hailed as a world changing technology. Unfortunately, there is a pervasive lack of understanding of what blockchain is, and misconceptions about what it can do. A fundamental problem is that blockchain was derived from bitcoin and there is a great deal of difficulty in defining what blockchain is, and how suitable the methodology for a trustless, public cybercurrency application is to a public blockchain between trusted partners. It is time, we believe, to look at blockchain in accounting with more objectivity. We undertake a detailed exploration of blockchain and identify several key factors that will defines the uses of this technology, namely, the distinction between public and private blockchains and the importance of processing costs as a validating mechanism.
This study aims to examine the impact of gender diversity on the digital reporting practices of non-financial U.S. firms listed on the S&P 500 index. Our results confirm the proposed hypothesis, indicating that the presence of female board members improves the levels of digital reporting. This could relate to the thought that gender diversity may correspond to more extensive discussions within the boardroom, which leads to better-informed decisions based on greater levels of information exchange both between the board and other stakeholders and amongst board members themselves. Our findings provide evidence for policy makers that gender diversity enhances online disclosure and thus, the transparency of the firm. The findings can be used, also, by corporate governance institutions to raise awareness of the advantages of having female members on the board. Our study contributes to the body of literature on both gender diversity and corporate online disclosure by providing new evidence that gender diversity on the board can improve digital reporting.
The Information Technology (IT) revolution that led to the development of cloud computing services and systems has brought numerous benefits to end users handling business through the Internet, particularly in the field of accounting information systems (AIS). Cloud-based accounting information systems (CB-AIS) enable firms to substantially reduce their investment in IT and have flexible access to an enormous group of current and scalable resources. CB-AIS enables small- and medium-sized enterprises (SMEs) to undertake basic bookkeeping responsibilities themselves instead of paying external auditors for the same services. In Jordan, however, current businesses are still in the infancy stage when it comes to CB-AIS adoption. Therefore, this study applied the Technology, Organization, and Environment model to examine CB-AIS adoption among SMEs in Jordan. Data collection was achieved using a structured survey questionnaire collected from 156 owners/managers of SMEs in Jordan through online means. The proposed research framework comprises six factors that influence intention to adopt CB-AIS (IACB-AIS). Based on the findings, the proposed hypotheses were supported in that the factors positively and significantly affect the IACB-AIS of SMEs in Jordan. Through examining an actual IACB-AIS case and highlighting the importance of its application, the study and its findings are expected to contribute to decision-makers and practitioners in the IT field.
To assess the financial statements of companies that invest in stablecoin, a digital representation of a fiat currency managed and backed by a blockchain, the auditor must collect evidence of transactions from the blockchain (on-chain) or from an off-chain ledger managed by an intermediary. This study aims to expand the understanding of such transactions, outline possible configurations for the recognition of stablecoin balances and transactions in financial statements, and audit procedures for collecting evidence of these transactions. Based on actual transactions of stablecoin registered on the Ethereum blockchain, we present a hypothetical case of the accounting history of an audited company to demonstrate the challenges in establishing accounting and audit procedures for these novel transactions. We observe an abundance, diversity, and unprecedentedness in the stablecoin transactions studied. We further identify the need to adapt current audit procedures and create new ones, and rethink the very process of doing so. The findings could help auditors obtain more significant knowledge of the information required to assess a company’s financial statements when such statements include stablecoin transactions. In addition, the study addresses the evolving relationship between auditing, accounting, and information technology, and the problems in integrating accounting and information technology.
Blockchain technology, smart contracts, and asset tokenization have relevant implications for the auditing environment. This paper evaluates the current stage of blockchain application in auditing, analyzing scientific publications and identifying the impact of what is already a reality and the potential effects of its improvements in audit professionals’ activities performance. The article considers the proposals and suggestions on the leading research indexed by the Scopus and Web of Science databases. We analyzed 374 papers on the topic of blockchain and provide a summary and analysis of the current state of auditing research. The bibliometric analysis was performed using the Bibliometrix R Package and the VOSviewer software. After a systematic study of abstracts and a general review of the papers to only include those directly related to our work’s objectives, we found 78 papers. The work results in a framework of potential and effective implications of blockchain technology for auditing, pointing out several new challenges in terms of skills and knowledge needed in this new reality of audit professionals.
The COVID-19 pandemic increased uncertainty about the financial future of many organizations, and regulators alerted auditors to be increasingly skeptical in assessing an entity’s ability to continue as a going concern. An auditor’s assessment of an entity’s ability to continue as a going concern is a matter of significant judgment. This paper proposes to use machine learning to construct a Decision Tree Automated Tool, based on both quantitative financial indicators (e.g., Z-scores) and qualitative factors (e.g., partners’ judgment and assessment of industry risk given the pandemic). Considering both quantitative and qualitative factors results in a model that provides additional audit evidence for auditors in their going-concern assessment. An auditing firm in Spain used the model as a supplemental guide, and the model’s suggested results were compared to auditors’ reports to evaluate its effectiveness and accuracy. The model’s predictions were significantly similar to the auditors’ assessments, indicating a high level of accuracy, and differences between the model’s proposed outcomes and auditors’ final conclusions were investigated. This paper also provides insights for regulators on both the use of machine-learning predictive models and additional factors to be considered in future going-concern assessment research.
