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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.

Using a qualitative grounded theory approach, this study explores the methods experienced external auditors use to detect fraudulent financial reporting (FFR) during standard audits.

Semi-structured interviews were conducted with 24 experienced external auditors to explore the methods they used to detect FFR successfully during standard external audits.

The authors find 58 methods used for FFR detection, out of which the following methods are frequently used and help in detecting more than one type of FFR: (1) specific analytical procedures, (2) positive confirmation, (3) understanding of the client's business and industry, (4) the inspection of specific documents, (5) a detailed analysis of the audit client's anti-fraud controls and (6) investigating tip-offs from suppliers, employees and customers.

Based on the grounded theory approach, the authors theorise that auditors must return to the basics and focus on specific audit procedures highlighted in this study for effective fraud detection.

The study provides practical guidance, including 58 methods used in audit practice to detect FFR. This knowledge can improve auditors' skills in detecting material misstatements due to fraud. Besides, analytical procedures and positive confirmation helped external auditors in this study detect all forms of FFR, yet they are overlooked in the external audit practice. Therefore, audit firms should emphasise the significance of these audit procedures in their professional audit training programmes. Audit regulators should advise auditors to consider positive confirmation instead of negative confirmation in financial audits to increase the likelihood of FFR detection. Moreover, audit standards (ISA 240 and SAS 99) should explicitly require auditors to conduct a detailed analysis of the client's anti-fraud controls.

This is the first study to identify actual, effective methods used by external auditors in detecting FFR during the ordinary course of an audit.

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 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 reviews and discusses the accounting literature that analyzes the role of auditors and enforcers in the context of fraud.

This literature review includes both qualitative and quantitative studies, based on the idea that the findings from different research paradigms can shed light on the complex interactions between different financial reporting controls. The authors use a mixed-methods research synthesis and select 64 accounting journal articles to analyze the main proxies for fraud, the stages of the fraud process under investigation and the roles played by auditors and enforcers.

The study highlights heterogeneity with respect to the terms and concepts used to capture the fraud phenomenon, a fragmentation in terms of the measures used in quantitative studies and a low level of detail in the fraud analysis. The review also shows a limited number of case studies and a lack of focus on the interaction and interplay between enforcers and auditors.

This study outlines directions for future accounting research on fraud.

The analysis underscores the need for the academic community, policymakers and practitioners to work together to prevent the destructive economic and social consequences of fraud in an increasingly complex and interconnected environment.

This study differs from previous literature reviews that focus on a single monitoring mechanism or deal with fraud in a broadly manner by discussing how the accounting literature addresses the roles and the complex interplay between enforcers and auditors in the context of accounting fraud.

Stockbrokers’ frauds in India frequently occur, causing investors significant financial loss. This study aims to unfold the various dubious practices adopted by stock brokers in the recent past to defraud investors and the necessary corrective regulations passed by the market regulator to prevent and detect fraud.

The authors conduct exploratory research using a collective model of literature review, case studies and regulatory changes.

The authors find tightening the system’s loopholes and strengthening the regulatory system using technology helps in the early detection and prevention of fraud. Media activism and investors’ awareness play a role in reducing incidences of fraud.

This study unfolds the practices followed by stock brokers to defraud investors, indicative of regulatory gaps and enforcement lapses. Regulators are evolving a robust system to curb these practices and make them on par with international standards. But, it has a long way to go.

Robust fraud detection and prevention mechanism is desirable to restore investors’ confidence in the stock market. Regulators should focus on investors’ protection and education and whistleblowers’ protection. Compared to the market regulators worldwide, the Securities and Exchange Board of India has less power to identify, detect and punish fraudulent brokers and needs to be empowered.

Besides the regulatory changes, strict enforcement and investor campaigns are required to increase public awareness and restore trust in the stock market to combat the recurrence of fraud.

This paper can be helpful to regulators, investors and financial intermediaries like stock brokers and aid in strengthening the reliability of capital markets and restoring investors’ confidence.

This paper aims to review the relevant forensic accounting research (FAR) around the world and suggests avenues for future research in forensic accounting.

The study used the thematic and systematic literature review methodology to analyse the existing literature in FAR.

The major thematic areas in the literature are fraud motivation, fraud consequences, fraud detection using forensic accounting techniques, forensic accounting theory, forensic accounting skills, forensic accounting education and forensic accounting jobs. The quantity of FAR is relatively small compared to the quantity of research in other accounting specializations. FAR is well developed in the USA and Canada and is less developed in Europe, Oceania and Asia. There is high interest in FAR in African countries. There is a relatively low global interest in internet information about “forensic accounting research” compared to global interest in other forensic accounting topics. Areas for future research include the role of the environment, digitalization, religiosity and sustainable development in forensic accounting.

FAR around the world is lopsided, as some regions have more advanced FAR compared to other regions. There is a need for even development of FAR across all regions and a need to publicize the outputs of FAR to a larger audience to increase people’s interest in forensic accounting.

The study extends the literature by presenting a rigorous thematic and systematic review of the existing literature. It highlights the depth of FAR, the major thematic areas, the benefits of FAR to society and the geographical reach of existing FAR.

Although corporations exert considerable efforts to uphold ethical standards in their business operations, fraud instances persist as an enduring and formidable challenge within organisations, defying their utmost efforts. The presence of fraud poses a substantial and recurring threat to corporations, leading to significant financial losses on an annual basis. This emphasises the crucial need for a comprehensive understanding of the factors contributing to fraudulent activities and the intricate nature of fraud risk factors inherent in business operations. Therefore, this paper aims to enhance the efficacy of fraud detection and prevention measures through critical analysis and refinement of established fraud theories, drawing upon the existing literature on this subject matter.

This paper offers a comprehensive qualitative analysis of the existing literature, thoroughly reviewing prominent models that aim to elucidate the underlying motivations behind fraudulent behaviour. Moreover, drawing upon the existing theoretical foundation, this study conceptualises a model that enhances the understanding of the crucial factors contributing to fraudulent behaviour.

The study presents new theoretical insights concerning the role of personal integrity in fraudulent decision-making, presenting refined interventions that enhance comprehension of the underlying drivers of fraud occurrences and strategies for prevention. Furthermore, the study reveals a comprehensive three-part approach to improving organisational health through strengthening compliance mechanisms and cultivating an ethical-values-based culture.

The study introduces a novel conceptual framework, the personal ethic-based fraud motivation model, which offers a deeper understanding of the factors and conditions influencing individuals’ propensity to engage in fraudulent activities. Furthermore, this study presents a three Cs strategy that effectively delineates the influential forces that drive individuals to surmount fraud risks.

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 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.