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This paper aims to investigate the perceptions of financial accountants and both internal and external auditors regarding the impact of corporate governance (CG) and information technology (IT) on the detection and prevention of fraud within organizations.

Primary data were collected from 250 financial accountants, internal auditors and external auditors through questionnaires. The non-probability snowball sampling technique was used for data collection, with the sample t-test, one-way ANOVA and paired sample t-test applied for analysis.

The results indicate that robust CG practices and IT techniques significantly aid in detecting and reducing fraudulent activities by minimizing opportunities, rationalizations, pressures and capabilities of potential employees to commit fraud. Internal controls also play a significant role in reducing instances of fraud. Notably, ethical officers and ethical training were not perceived as significantly effective in preventing and detecting fraud, leading to a perception that fraudulent practices are prevalent and increasing the risk of future fraudulent activities.

This study recommends the adoption of strong CG practices to identify potential fraud within an organization. Moreover, IT techniques should be tailored to specific needs for effective utilization. Furthermore, the government should increase awareness regarding data provision by departments, organizations and other related personnel. Future research could use secondary data from various regions to expand the literature in this field.

This research uniquely combines three significant factors: CG, IT and forensic accounting in fraud detection and prevention. It contributes to the enhancement of literature about fraud and its preventive and detective measures. The results of this study set the seed for future research, government policymaking and enhanced organizational practices.

This study aims to examine how auditors perceive the influence of crucial fraud prevention factors in deterring financial statement fraud within the corporate sector. Additionally, this research explores the mediating effect of fraud awareness in elucidating the impact of ethical leadership and internal control systems on preventing financial statement fraud.

The study used an online survey, targeting a sample of 141 professionally qualified auditors with at least one year of practical experience in the field. The researchers used “Structural Equation Modeling (SEM)” to examine relationships between latent variables using partial least squares structural equation modeling. The study investigated the impact of whistleblowing systems, fraud awareness, ethical leadership, internal control systems and corporate governance on fraud prevention.

This research finding provides evidence to the corporate sector by establishing the significance of fraud awareness as the most influencing factor in preventing financial statement fraud. Furthermore, the combined explanatory variables account for 77.4% of the overall variance in financial statement fraud prevention. The study reveals a partial mediation effect of fraud awareness on the relationship between the internal control system and financial statement fraud prevention.

This research finding may assist in developing an effective fraud prevention programme to mitigate fraud instances and improve financial reporting quality. In the corporate sector, each organisation should clearly specify the policies on whistleblowing systems, fraud awareness training, internal control systems and corporate governance. To foster a comprehensive fraud prevention programme, the leaders should enforce these policies with employee support.

This research integrated crucial elements to develop a new theoretical framework for investigating financial statement fraud prevention within the corporate context. Accordingly, this research framework provides a more in-depth explanation of preventing financial statement fraud from an auditor’s perspective. Additionally, this research is the first to explore the mediating role of fraud awareness in influencing the effectiveness of the internal control system in preventing financial statement fraud.

This study aims to examine the degree of consciousness of forensic accounting (FA) in Jordan. This study surveys practitioners and academicians about their views and thoughts toward the expected role of using FA techniques to detecting and preventing fraud practices and shedding more light on advantages and obstacles of using the FA techniques.

To collect the data, a questionnaire was constructed and distributed to the study population which consists of accounting academics, students and accounting practitioners.

The results of this study show evidence that both students and professionals have a lower level of awareness on the FA concept and its importance. The results also confirm there is a significant correlation between, fraud prevention and detection, advantages of the application of FA, the training courses toward the application of FA and the application of FA in the context of Jordan. It has also been confirmed that there is a number of significant factors hinders this implementation in Jordan.

The findings of this study offer many policy implications for regulators and policymakers on the needed relevant information to address and implement FA in education and practice, thereby activating the FA concept in Jordan.

The primary motivation of this study is driven by the limited and inconclusive research on the FA as a monitoring tool, notably there is a high possibility of fraud and misstatement practices due to the agency conflict. This study is the first of its kind to discuss this topic in the context of Jordan. The need to integrating the accounting education within accounting profession regarding FA becomes an urgent need to develop the awareness level of practitioners when it comes to practice of FA.

This paper aims to investigate the role of forensic accounting skills in enhancing auditor’s self-efficacy towards fraud detection in Egypt. Additionally, it explores the moderating effect of computer-assisted audit techniques and tools (CAATTs) application on the relationship between accounting and auditing skills and auditor’s self-efficacy, as well as its role in enhancing fraud detection.

A cross-sectional survey was developed and distributed to 117 external auditors working in Egypt. Partial least square structural equation modelling is used to examine the study hypotheses.

The results show a significant direct relationship between effective communication skills, psycho-social skills, accounting and auditing skills and an auditor’s self-efficacy. Additionally, the results show a significant direct relationship between auditor’s self-efficacy and fraud detection. It is revealed that CAATTs application moderate the relationship between auditor’s self-efficacy and fraud detection. In contrast, the results do not show a significant relationship between technical and analytical skills and auditor’s self-efficacy.

The originality of this research paper lies in its exploration of the role of forensic accounting skills in enhancing auditor’s self-efficacy towards fraud detection in Egypt. It sheds light on the role of improved auditor’s self-efficacy in detecting fraud. Additionally, this study further enhances the understanding of the potential benefits of using technological advancements in the audit process. It provides insights for accounting professionals and regulatory bodies in Egypt, highlighting the importance of leveraging forensic accounting skills and using CAATTs to enhance fraud detection efforts.

The emergence of machine learning has opened a new way for researchers. It allows them to supplement the traditional manual methods for conducting a literature review and turning it into smart literature. This study aims to present a framework for incorporating machine learning into financial statement fraud (FSF) literature analysis. This framework facilitates the analysis of a large amount of literature to show the trend of the field and identify the most productive authors, journals and potential areas for future research.

In this study, a framework was introduced that merges bibliometric analysis techniques such as word frequency, co-word analysis and coauthorship analysis with the Latent Dirichlet Allocation topic modeling approach. This framework was used to uncover subtopics from 20 years of financial fraud research articles. Furthermore, the hierarchical clustering method was used on selected subtopics to demonstrate the primary contexts in the literature on FSF.

This study has contributed to the literature in two ways. First, this study has determined the top journals, articles, countries and keywords based on various bibliometric metrics. Second, using topic modeling and then hierarchy clustering, this study demonstrates the four primary contexts in FSF detection.

In this study, the authors tried to comprehensively view the studies related to financial fraud conducted over two decades. However, this research has limitations that can be an opportunity for future researchers. The first limitation is due to language bias. This study has focused on English language articles, so it is suggested that other researchers consider other languages as well. The second limitation is caused by citation bias. In this study, the authors tried to show the top articles based on the citation criteria. However, judging based on citation alone can be misleading. Therefore, this study suggests that the researchers consider other measures to check the citation quality and assess the studies’ precision by applying meta-analysis.

Despite the popularity of bibliometric analysis and topic modeling, there have been limited efforts to use machine learning for literature review. This novel approach of using hierarchical clustering on topic modeling results enable us to uncover four primary contexts. Furthermore, this method allowed us to show the keywords of each context and highlight significant articles within each context.

Although the academic literature provides extensive insight into the motivations for the unethical use of information technology in online classes, little is known about how perceived justice, the opportunity to cheat and spiritual legitimacy mitigate unethical behavior among young academics. The purposes of this study are two folds: first, to determine how perceived lecturers’ justice and opportunity to cheat may mitigate academic misconduct in online classes, and second, to evaluate the moderating effect of spiritual power on the relationship between perceived lecturers’ justice and opportunity to cheat and academic misconduct.

This research was conducted at universities in three Southeast Asia countries, including Indonesia, Malaysia and Thailand, with a total of 339 respondents. The research questionnaire was distributed using Google Forms. The analytical method used to test the research hypothesis is moderated regression analysis (MRA).

The findings of this study reveal that spirituality moderates the relationship between lecturer justice and the opportunity to cheat online. Even though the justice level of the lecturer is low, individuals with relatively high spirituality will show much less cheating behavior than when there is a low level of lecturer justice and a low level of student spirituality, and vice versa.

Cheating occurs when students develop an intention to cheat, which leads to actual involvement in cheating, meaning that theoretically, the findings extend the fraud triangle theory. In addition, the practical implications of this research are that lecturers need to conduct fair teaching, such as transparency of exam conditions, assessment, the right to an opinion and supervision during exams, consequently, the students cannot cheat. Spirituality is also an essential factor that can reduce online cheating, so instilling spirituality in specific courses is a fruitful solution.

The contributions of this study are twofold. First, this study gives testable theories on how spiritual help works. Second, this study offers tailored and more humanistic assistance, such as a mechanism that adjusts to the academic world’s usage of more positive technologies. This study contributes to the literature on online cheating in higher education across three Southeast Asian nations (Indonesia, Malaysia and Thailand).

This study aims to objectively synthesize the volume of accounting literature on financial statement fraud (FSF) using a systematic literature review research method (SLRRM). This paper analyzes the vast FSF literature based on inclusion and exclusion criteria. These criteria filter articles that are present in the accounting fraud domain and are published in peer-reviewed quality journals based on Australian Business Deans Council (ABDC) journal ranking. Lastly, a reverse search, analyzing the articles' abstracts, further narrows the search to 88 peer-reviewed articles. After examining these 88 articles, the results imply that the current literature is shifting from traditional statistical approaches towards computational methods, specifically machine learning (ML), for predicting and detecting FSF. This evolution of the literature is influenced by the impact of micro and macro variables on FSF and the inadequacy of audit procedures to detect red flags of fraud. The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper chronicles the cluster of narratives surrounding the inadequacy of current accounting and auditing practices in preventing and detecting Financial Statement Fraud. The primary objective of this study is to objectively synthesize the volume of accounting literature on financial statement fraud. More specifically, this study will conduct a systematic literature review (SLR) to examine the evolution of financial statement fraud research and the emergence of new computational techniques to detect fraud in the accounting and finance literature.

The storyline of this study illustrates how the literature has evolved from conventional fraud detection mechanisms to computational techniques such as artificial intelligence (AI) and machine learning (ML). The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper contributes to the literature by providing insights to researchers about why the evolution of accounting fraud literature from traditional statistical methods to machine learning algorithms in fraud detection and prediction.

The purpose of this paper is to understand if forensic accounting techniques and tools could contribute to the deterrence of fraud in financial statements, considering the expertise of forensic accountant on ex post activities and that the traditional mechanisms to prevent this type of fraud have not been sufficient to stop the impact on companies, investors, auditors, employees and on society in general.

This research was carried out using a qualitative exploratory study with a phenomenological approach conducted through in-depth interviews with professional experts in the forensic field.

The findings confirm that the use of forensic accounting techniques and tools could contribute to the prevention of fraud in financial reporting not only when the risk of fraud has been materialized. Similar studies, about fraud prevention addressing the situation under a qualitative approach from the perspectives of its protagonists, have not been observed in the bibliographical review, so this research contributes to expanding the scientific research, the study and practice of forensic accounting.

From a business management perspective, this study contributes a paradigm shift from the traditional ex post forensic auditing activity toward an ex ante activity to improve management control systems within organizations anywhere in the world. Because this study is guided to prevent fraudulent financial statements, other fraud categories such as misappropriation or corruption could be addressed in other studies and various countries.

Increased fraudulent practices have heightened the need for innovation in anti-fraud programs, necessitating the development of analytics techniques for detecting and preventing fraud. The subject of fraud analytics will continue to expand in the future for public-sector organizations; therefore, this research examined the progress of fraud analytics in public-sector transactions and offers suggestions for its future development.

This study systematically reviewed research on fraud analytics development in public-sector transactions. The review was conducted from June 2021 to June 2023 by identifying research objectives and questions, performing literature quality assessment and extraction, data synthesis and research reporting. The research mainly identified 43 relevant articles that were used as references.

This research examined fraud analytics development related to public-sector financial transactions. The results revealed that fraud analytics expansion has not spread equally, as most programs have been implemented by governments and healthcare organizations in developed countries. This research also exposed that the analytics optimization in fraud prevention is higher than for fraud detection. Such analytics help organizations detect fraud, improve business effectiveness and efficiency, and refine administrative systems and work standards.

This research offers comprehensive insights for researchers and public-sector professionals regarding current fraud analytics development in public-sector financial transactions and future trends.

This study presents the first systematic literature review to investigate the development of fraud analytics in public-sector transactions. The findings can aid scholars' and practitioners' future fraud analytics development.

This paper aims to systematically review over two decades of academic articles on romance fraud to provide a holistic insight into this crime and identify literature gaps.

More than two decades of peer-reviewed academic journal articles from 2000 to 2023 were systematically reviewed using multiple search engines and databases for relevant papers, identified through searches of paper titles, keywords, abstracts and primary texts.

The findings reveal 10 themes: i) the definitions and terminology of romance fraud; ii) romance fraud’s impact on victims; iii) the profile of romance fraud criminals and victims; iv) romance fraud methods and techniques; v) why victims become susceptible to romance fraud; vi) the psychology of romance fraud criminals; vii) the links between romance fraud and other crimes; viii) the challenges of investigating romance fraud; ix) preventing romance fraud and protecting victims; and x) how romance fraud victims can be supported.

The paper reveals implications regarding the future direction of policy and strategy to address the pervasive low reporting rates and narratives of shame bound with victims of this crime.

Romance fraud is a serious crime against individuals with impacts beyond financial losses. Still, this fraud type is under-researched, and the literature lacks a holistic view of this crime. To the best of the authors’ knowledge, this is the first systematic literature review providing a holistic view of romance fraud. It combines evidence across the academic landscape to reveal the breadth and depth of the current work concerning romance fraud and identify gaps in the understanding of this fraud crime.