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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 investigate cases of fraudulent financial statements that have occurred in Indonesia and explore the similarities of cases that existed in the period before and after the establishment of the Financial Services Authority.

This paper provides a descriptive examination of financial misstatements issued by different regimes by listed companies of the capital market and financial institution supervisory agency and the introduction of new financial service authority; among 93 listed companies that were subject to an official investigation arising from the publication of financial misstatements, these assessments were facilitated by mean of content analysis of annual reports following the announcement of an investigation.

The findings indicate that each regime has a specific pattern of financial statement fraud. It is found that senior management is responsible for most fraud, and recording a fictitious sale is the most common method of falsifying financial statements. Under the new regime, the publication of cases is limited since the introduction of risk-based supervision. Financial Services Authority is likely to fine and prosecute the director of a company as a perpetrator rather than a corporation as a legal entity.

This study contributes to the literature on the incidence of financial statement fraud in public companies and provides a detailed descriptive comparison of cases scrutinized by securities exchange commission in an emerging country.

This study aims to compare machine learning models, datasets and splitting training-testing using data mining methods to detect financial statement fraud.

This study uses a quantitative approach from secondary data on the financial reports of companies listed on the Indonesia Stock Exchange in the last ten years, from 2010 to 2019. Research variables use financial and non-financial variables. Indicators of financial statement fraud are determined based on notes or sanctions from regulators and financial statement restatements with special supervision.

The findings show that the Extremely Randomized Trees (ERT) model performs better than other machine learning models. The best original-sampling dataset compared to other dataset treatments. Training testing splitting 80:10 is the best compared to other training-testing splitting treatments. So the ERT model with an original-sampling dataset and 80:10 training-testing splitting are the most appropriate for detecting future financial statement fraud.

This study can be used by regulators, investors, stakeholders and financial crime experts to add insight into better methods of detecting financial statement fraud.

This study proposes a machine learning model that has not been discussed in previous studies and performs comparisons to obtain the best financial statement fraud detection results. Practitioners and academics can use findings for further research development.

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.

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.

No country is free from financial crime issues. Therefore, this paper aims to discover how to control financial crime from the perspective of national culture.

This study conducted a bibliometric approach and systematic literature review analysis of 47 publications in the Scopus database.

Bibliometric and content analyses show that national culture is more often associated with tax evasion, money laundering and corruption. The role of national culture is less investigated currently in the schemes of financial statement crime, workplace fraud and cybercrime. Overall, the study concludes financial crime can be prevented by developing a culture that supports anti-fraud measures. These include individualized country profiles, feminism, low power distance, tolerance for uncertainty, short-term orientation and restraint.

This research provides clear knowledge of the role of the six dimensions of national culture in fighting financial crime. Finally, this study is also valuable for decision-making in designing more effective financial crime prevention programs.

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.

This study aims to examine the relationship between selfishness, moral justification and intention to fraud among accounting certified professionals. It focuses on the role of moral justification in explaining the link between selfishness and intention to fraud.

Data were collected with the help of a structured questionnaire. The final sample includes 240 accounting certified professionals. To test the hypothesized model in this study, IBM AMOS ver26 was used to perform the structural equation modeling.

The results of this study show that selfishness has no direct impact on the intention to commit fraud. However, selfishness does have a positive impact on moral justification. Furthermore, the study found that moral justification mediates the relationship between selfishness and fraud intention.

This study provides important implications for accounting firms and other organizations and recommends that they implement the necessary practices to reduce the fraudulent intentions of certified accounting professionals while simultaneously reducing selfishness and moral justification.

This research is among the few studies in the accounting field that address the mediating role of moral justification in the relationship between selfishness and fraud intention among certified accounting professionals.

This study aims to investigate the factors that influence asset misappropriation fraud among police officers in the Internal Security and Public Order (Malay: Keselamatan Dalam Negeri dan Ketenteraman Awam [KDNKA]) Department, Royal Malaysian Police (RMP).

Primary data were collected from a questionnaire-based survey and the data were analysed using descriptive analysis, correlation analysis and multiregression.

The element of pressure was found to have a negative relationship with asset misappropriation fraud. This result shows the uniqueness of the KDNKA Department in the RMP. The other three elements are found to have a significant positive relationship with asset misappropriation fraud.

This study’s findings can aid academicians in gaining a better understanding of the literature surrounding fraud diamond theory and aid the policymakers in recognizing the signs and possibilities of asset misappropriation fraud in public agencies.

To the best of the authors’ knowledge, this is the first study that uses the KDNKA Department which is the second largest department in RMP as a population in fraud study.

The purpose of this study is to examine the impact of anti-money laundering (AML) regulations on accrual earnings management (AEM) and real earnings management (REM) in Iran’s emerging capital market.

The panel data regression is used to testing hypotheses. The sample includes 2,020 data and 202 companies listed on the Tehran Stock Exchange (TSE) over a period of ten years from 2012 to 2021. Also, the companies covered in this study include financial and nonfinancial companies. Furthermore, the data related to the research variables were extracted from the annual financial statements and the TSE database.

The results show that compliance with AML regulations leads to a reduction in AEM and REM. In other words, companies with higher money laundering (ML) tend to manage their earnings, which is in line with agency theory.

This study has implication for policymakers and regulators, auditors and managers. Considering the negative impact of AML regulations on earnings management (EM), Iranian auditing firms need to emphasize on the full implementation of AML regulations in TSE. Also, the results of this research may aid policymakers and regulators to detect financial crimes through accounting signals.

To the best of the authors’ knowledge, this is the first study in an Iran capital market to examine the impact of AML regulations on EM in financial and nonfinancial companies. Previous research has not controlled for the effects of financial companies. Prior studies have not examined the effects of financial companies. In addition, this study differentiates itself from previous studies by introducing a new method for measuring the independent ML variable based on auditor opinions. The obtained data can aid international bodies to better understand compliance with ML regulations in Iran and can reduce their concerns in negotiations.