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According to the Association of Certified Fraud Examiners, financial statement fraud represents the smallest amount of fraud cases but results in the greatest monetary loss. The researcher previously investigated the characteristics of financial statement fraud and determined the presence of 16 fraud indicators. The purpose of this study is to establish whether investors and other stakeholders can detect and identify financial statement fraud using these characteristics in an analysis of a company’s annual report.

This study analyses a financial statement fraud case, using the same techniques that were previously applied, including horizontal, vertical and ratio analysis. These are preferred because stakeholders have relatively easy access to them.

The findings show several fraud characteristics, with a few additional ones not previously found prevalent. Financial statement fraud thus tends to differ between cases. It is also easier to detect and identify fraud indicators ex post facto.

This study is a practical case showing that financial statement fraud can be detected and identified in the financial statements of companies that commit fraud.

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 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.

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.

The purpose of this study is to investigate whether the likelihood that a firm will face financial statement fraud litigation is affected by the disclosure of internal control material weaknesses (MW) and the “busyness” of a firm’s board of directors.

The results are derived from logistic regression models and data are collected from the Audit Analytics database augmented by data from CompuStat, the Stanford Law School website and the SEC Accounting and Auditing Enforcement Releases. The authors also test for endogeneity with a propensity score matching procedure.

The authors find that an MW report is strongly associated with the likelihood of subsequent financial statement fraud litigation, and that the influence of entity-level MW on litigation likelihood is stronger than that of account-level MW. Moreover, the number of outside board directorships significantly increases the influence of entity-level MW on the likelihood of litigation, indicating that board of directors’ busyness significantly increases the risk of litigation.

Previous research notes that board members holding multiple directorships cannot effectively oversee the financial reporting process and, thus, are associated with poorer governance. The authors extend this implication of board busyness to the association between disclosure of MW type and the filing of subsequent litigation alleging financial statement fraud. To the best of the authors’ knowledge, no other research has done so.

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.

This study aims to explore the relationship between fraud triangle theory (FTT) and the accounting fraud phenomenon in all listed companies in China.

The CSMAR database is used as the sample, including 16,063 data of all listed companies in Shanghai and Shenzhen markets for the 2010–2020 period. The authors also use quantitative methods, such as regression analysis, to investigate the relationship between five variables (cover three elements of FTT) and fraud occurrence.

Results show that leverage and liquidity ratios positively affect fraud detection, whereas return on net equity, audit size and independent director percentage negatively affect fraud detection.

This study enriches theoretical research on the causes of accounting fraud in China and is of great significance to the sound development of China’s capital market.

This study aims to examine the roles of organisational control, structure, culture and technology in preventing occupational fraud. This study is essential in the current time. It brings a significant impact on both theory and practice. In the existing studies, there is a lack of clarity on a specific mechanism to prevent organisational fraud. The problem is that they tend to generalise the types of organisational fraud. Conceptually, organisational fraud may include corruption, double funding, asset misappropriation, bribery or falsification of documents. However, many scholars tend to neglect such diversities. Consequently, many occupational fraud cases become unstoppable, particularly corruption. To deal with this topical issue, the current study applies the term “occupational fraud” cited by the Association of Certified Fraud Examiners, consisting of corruption, asset misappropriation and fraudulent financial statement.

This study surveyed three Indonesian Local Governments. This study focussed on management levels that have strong power for coordinating governmental activities. The author chose these local governments because their local leaders (the regents) were jailed due to corruption scandals. As expected, this study gives us different perceptions of how fraud mitigation should be designed in the organisation.

The results suggest that corruption is a little bit complex than other types of occupational fraud. It is improbable to be prevented through technological and administrative approaches. As such, organisations need to think of extra efforts that could perfectly tailor the organisational control and organisational culture, organisational structure and technological advancement. The benefit of this effort is related to diagnosing the fit or misfit of organisation designs in addressing the dynamic dimensions of corporate governance. Then, it can also strengthen the efficacy of preventive measures to deal with occupational fraud.

This study provides a provocative discussion regarding the public perception of occupational fraud, consisting of corruption, asset misappropriation and financial statement fraud. And this study also offers a new refined conceptual analysis of how to deal with such types of occupational fraud by incorporating contingency theory and the Committee of Sponsoring Organizations of the Treadway Commission (COSO’s) internal control components.

Recent studies have concluded that auditors underreport existing internal control over financial reporting (ICFR) weaknesses. This study aims to assess how effective external auditors are, as independent third parties, at disclosing reliable opinions to the public on the ICFR.

Using a logistic regression, the authors analyzed a sample of 106 US companies classified as large accelerated filers or accelerated filers consisting in 53 companies which restated their financial statements and a control group of 53 companies having “clean financial statements” at any given moment during the research period, between 2005 and 2018.

The results indicate that only 34% of companies with financial statements deemed unreliable have received an adverse ICFR opinion issued by the external auditor during the misrepresentation period or its prior year. The authors also notice that external auditors are somewhat effective in identifying and disclosing red flags to the public that certain companies have internal control (IC) material weaknesses. The results also indicate that the average presence of an adverse IC opinion issued by the external auditor during the misrepresentation period or its prior year for companies with unreliable financial statements is higher than for companies with financial statements deemed reliable.

This study tests if an increase in efforts and disbursements with audit fees are justifiable by external auditors’ issuing effective, reliable opinions and reinforcing a more transparent and ethical capital markets environment, that is, an environment where accurate information is available for stakeholders. If external auditors are negligent in providing a qualitative and independent opinion to stakeholders, the increase of disbursements made with audit fees is less justifiable. Thus, the research has practical implication for auditors as well as standard setters.

This study extends the literature on ICFR by empirically testing whether the public can rely on external auditors’ opinions expressed on Sarbanes–Oxley Section 404 reports.