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The purpose of this study is to explore how the risk of management motives for fraud can be assessed in external audits.

Semi-structured interviews were conducted with 26 experienced external auditors to explore their perspectives on the methods they employ to assess the risk of management motives for fraud.

The study identifies six methods external auditors can use to assess management motives for fraud. It emphasises that assessing management motives requires auditors to go beyond understanding these motives and necessitates a sceptical and analytical mindset. Auditors need to identify the accounts most vulnerable to management manipulations, observe management attitudes and assess the credibility of management assertions. The auditors in this study highlight specific accounts frequently manipulated by management. Still, manual year-end journal entries are the most vulnerable to management manipulations as they are subject to fewer controls. They recommend increasing the sample size to 100% and assigning more experienced staff, particularly, those with qualifications in fraud examination or anti-fraud training, to audit these vulnerable accounts thoroughly. They also provided examples of how auditors can identify management motives for fraud, observe management attitudes and assess the credibility of management assertions.

Audit standards (e.g. ISA 240, SAS99) lack explicit guidance on assessing management motives for fraud, but auditors are required to consider it in fraud risk assessment. This study proposes guidance recommendations to improve auditors' ability to assess this risk, which could be integrated into professional audit standards and training materials to improve auditors' professional scepticism, ability to challenge management and skills in fraud risk assessment.

Assessing the risk of management motives for fraud in external audits has received limited attention in the literature. To the best of the authors’ knowledge, this study is the first to address this knowledge gap.

Financial statement fraud has become a global concern, and auditors are increasingly focused on identifying and investigating it. Auditors may play a crucial role in investigating and reducing financial statement fraud, and this is particularly important in developing countries where fraudulent practices are more prevalent due to the lack of strict regulations and oversight. This study investigates whether enhanced audit quality has an impact on reducing financial statement fraud. The primary aim is to recognize whether a higher level of audit quality relates with a decrease in fraudulent activities in Indonesia, which is one such country that has not yet adopted IFRS.

This study investigates the effect of audit quality, as measured by audit tenure, audit fee, and audit size, on the dependent variable of financial statement fraud, as indicated by Dechow F-value. The sample for this study comprises 951 observations from 2015 to 2020, and the research design utilizes a panel data approach. To test the main hypothesis, OLS, and GMM estimation techniques are employed.

The analyses reveal a negative relationship between audit tenure and financial statement fraud. This suggests that shorter audit tenure may be associated with an increased risk of financial statement fraud. This heightened risk could stem from auditors having limited time to thoroughly understand the company's operations and internal controls, potentially making it more challenging to detect and prevent fraudulent activities perpetrated by the client. Conversely, a positive relationship is identified between audit fees and financial statement fraud, suggesting that companies paying higher fees may be engaging auditors less adept at detecting fraudulent activities. Furthermore, a negative relationship is observed between Big-5 and financial statement fraud, which may be due to the greater resources, expertise, quality control, scrutiny, reputation, and ethical conduct of Big-5 audit companies.

This study only focused on listed companies in Indonesia, therefore, caution should be exercised when generalizing the findings to other developing and Muslim countries such as Malaysia. The findings may differ due to the adoption of IFRS in Malaysia. As such, it is important for future studies to include Malaysia as a sample and compare the results with those of Indonesia. This comparison would demonstrate the impact of IFRS adoption on the relationship between audit quality and financial statement fraud and provide insights for policy makers in Indonesia.

The findings of this study have important implications for developing countries that have been shown to be more susceptible to fraud than developed countries. This study contributes to the existing research on the role of audit quality in reducing financial statement fraud and emphasizes the need for auditors and accountants to take a proactive approach in detecting and investigating financial fraud.

This study is a new study because it investigates the relationship between audit quality and financial statement fraud in Indonesia, a developing Muslim country that has not yet adopted International Financial Reporting Standards (IFRS). The study provides valuable evidence on the unique factors that influence fraud in Indonesia and fills a gap in the literature as previous studies on this topic have largely focused on developed countries. Additionally, the study recommends that policymakers in Indonesia consider implementing IFRS to improve the reliability of financial reporting and strengthen the effectiveness of the auditing process, thus reducing the incidence of fraud.

This study aims to examine the ability of big data analytics (BDA) to investigate financial reporting quality (FRQ), identify the knowledge base and conceptual structure of this research field and explore BDA techniques used over time.

This study uses a comprehensive bibliometric analysis approach (performance analysis and science mapping) using software packages, including Biblioshiny and VOSviewer. Multiple analyses are conducted, including authors, sources, keywords, co-citations, thematic evolution and trend topic analysis.

This study reveals that the intellectual structure of using BDA in investigating FRQ encompasses three clusters. These clusters include applying data mining to detect financial reporting fraud (FRF), using machine learning (ML) to examine FRQ and detecting earnings management as a measure of FRQ. Additionally, the results demonstrate that ML and DM algorithms are the most effective techniques for investigating FRQ by providing various prediction and detection models of FRF and EM. Moreover, BDA offers text mining techniques to detect managerial fraud in narrative reports. The findings indicate that artificial intelligence, deep learning and ML are currently trending methods and are expected to continue in the coming years.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive analysis of the current state of the use of BDA in investigating FRQ.

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 investigate the moderating role of natural language processing natural language processing (NLP) on the relationship between AI-empowered AIS (data gathering, data analysis, risk assessment, detection, prevention and Investigation) and auditing and fraud detection.

Quantitative methodology was adapted through a questionnaire. In total, 221 individuals represented the population of the study, and SPSS was used to screen primary data. The study indicated the acceptance of the hypothesis that “Artificial Intelligence in AIS has a statistically significant influence on auditing and fraud detection,” showing a strong correlation between auditing and fraud detection. The study concluded that NLP moderates the relationship between AI in AIS and auditing and fraud detection.

The study’s implications lie in its contribution to the development of theoretical models that explore the complementary attributes of AI and NLP in detecting financial fraud.

A cross-sectional design is a limitation.

NLP is a useful tool for developing more efficient methods for detecting fraudulent activities and audit risks.

The study’s originality stems from its focus on the use of AI-empowered AIS, a relatively new technology that has the potential to significantly impact auditing and fraud detection processes within the accounting field.

This case study is based on fraudulent press releases by Turbo Global Partners, Inc., an Over the Counter (OTC) traded public company in the United States. After the fraudulent press releases, the Securities and Exchange Commission (SEC) suspended the trading of securities of Turbo Global Partners, Inc. and filed a complaint against the company in the US District Court in the Middle District of Florida. This case study presents accounting students (Intermediate II and auditing students) with various concepts related to fraud, ethics, and financial reporting. Specifically, this case study presents the concepts related to (1) fraud triangle; (2) the impact of fraud to various stakeholders; (3) debt extinguishment; (4) analysis of financial statements; (5) accounting for intangible assets; (6) analytical procedures; and (7) SEC investigation and actions. This case provides students with an opportunity of active learning as they analyze a real-world case of fraud and access professional literature such as Accounting Standards Codification (ASC) and SEC documents.

This paper investigates the relationship between risk management practices and potential fraudulent financial reporting in Malaysia by considering recent regulatory reforms of the Malaysian government on risk management practices.

The sample of this study was based on 257 firm-year observations during the 2012–2017 period. This study employed panel-least square regressions with period fixed effects.

This study found a significant association between risk management activities in the disclosure and potential fraudulent financial reporting. Nevertheless, this study found there is insignificant effect of the risk-management committee in reducing potential of fraudulent financial reporting.

This study is a pioneer research that relates firms’ risk management practices with potential fraudulent financial reporting measured by F-score. Thus, this study provides an insight to regulators on the extent of risk-management practices in deterring potential fraudulent financial reporting which can be used as an input for greater enforcement of risk-management regulations.

The purpose of this paper is to investigate and analyze the adoption of digital technologies in the banking industry and its impact on the rise of digital fraudulent activities, specifically focusing on online banking frauds. This paper aims to provide insights into the current technologies implemented by banks to secure their online banking systems and explores the methods used by cybercriminals to exploit security vulnerabilities in these systems.

In order to understand how digital technologies in banking can be secured against online fraud, this research conducted a systematic literature review (SLR) on digital banking, online banking fraud, and security measurements. The review encompasses a variety of sources from online databases such as Emerald Insight, Google Scholar, IEEE, JSTOR, Springer and Science Direct.

The key finding of the paper is that the adoption of digital technologies in the banking industry has led to a significant increase in digital fraudulent activities, particularly in the form of online banking frauds. This paper emphasizes that these frauds have become a global concern and have evolved into an industry where cybercriminals use sophisticated tools such as phishing attacks, denial-of-service attacks, Trojan horses, malware infections, identity theft and computer viruses.

This study relies solely on a literature review without incorporating primary data or case studies; therefore, it might miss out on the firsthand experiences and perspectives of banks and cybersecurity professionals.

This study emphasizes the need for banks to adopt advanced security measures to safeguard their online banking systems.

This study underscores the importance of ongoing training and awareness programs for both bank employees and customers.

This study specifically addresses the adoption of digital technologies in the banking industry and its correlation with the increase in digital fraudulent activities. This focus on the intersection of technology and fraud in the banking sector is a distinctive aspect. This study conducts a SLR to examine the current technologies implemented by banks to safeguard their online banking systems. This comprehensive approach provides insights into the diverse security measures used by banks to protect against various types of cyber threats.

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 assess the effectiveness of forensic accounting techniques to prevent and detect fraudulent activities in firms in Pakistan.

A descriptive research approach has been adopted in this study. Primary data has been collected through structured questionnaires distributed to professionals from investigating firms, professional bodies and field researchers. The independent variables that were analyzed included fraud investigation, litigation support and dispute resolution, whereas the dependent variables were fraud detection and prevention. The Statistical Package for Social Sciences has been used for data analysis to derive objective results.

This research reveals that forensic accounting techniques such as fraud investigation, litigation support and dispute resolution have a positive impact on fraud detection and prevention in Pakistani firms.

Firms should train staff on forensic accounting techniques, implement fraud risk management and anti-corruption policies, conduct regular financial statement audits and develop a whistleblower protection program to encourage employees to report fraudulent activities. The government should develop regulations and guidelines to promote the use of forensic accounting in firms.

This study is covering the gap in literature on financial fraud and forensic accounting practices concerning emerging economies such as Pakistan. This study can serve as a valuable resource for firms and policymakers to strengthen their fraud prevention efforts and build a more robust culture of financial integrity.