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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 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 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.

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.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.

The purpose of this study is to test the determinant of financial report quality and its consequences to the company values.

This research is using a quantitative approach and testing a theory by formulating some hypotheses. The sample of this study is 85 go public companies listed in the Indonesia Stock Exchange, for a 5-year observation period from 2016 to 2020. Hence, it has a total of 425 observations. Data were analyzed using path analysis.

The results found that innate factors from financial reporting quality (FRQ) consists of dynamic factors (operation cycle and sales volatility) as well as static factors (firm’s size, FS). These factors help to achieve FRQ and are able to provide a positive response to the market. On the other hand, static factors (firm’s age, FA) and institution risk factors (leverage) are not able to produce FRQ. Thus, it cannot be considered as an economic decision maker for an investor.

Research implications include theoretical and practical implications. Theoretical implications prove that the valuation of clean surplus theory, which shows the market value of the company, is reflected in the components of the financial statements. This study also uses more than one quality of financial reporting. The practical implication of the research is that the research results are expected to provide information for the company’s management, to fulfill quality financial reporting and so that the market or investors will respond positively to these conditions. In addition, quality financial reporting information provides benefits for investors and capital market analysts (consisting of investors, brokers and market securities analysts) in determining investment decisions. The Financial Services Authority is also able to improve the implementation of corporate governance practices in Indonesia, through reform of the framework supervision of the financial services sector.

This research examines the determinants of FRQ and its consequences on firm’s value (FV). Innate factors proxies from FRQ include dynamic factors (operation cycle and sales volatility), static factors (FS and FA) and institution risk factors (leverage). A follow-up study on the value of the company because it shows the magnitude of the market response (financial statement users) on the quality of financial reporting, which is reflected in FV, the originality of this research is that the object of research is carried out in developing countries, specifically in Indonesia, because most of the previous research was carried out in developed countries.

The purpose of this paper is to examine the interrelationship of marketing, accounting and auditing with corporate social responsibility (CSR) to determine the benefit of CSR marketing, the responsibility of Board of Directors (BODs) with CSR accounting and the duty of external auditors with CSR that has influence on corporate sector.

This paper uses exploratory and qualitative data obtained from multiple research methods, to investigate benefit of CSR marketing, the responsibility of BODs with CSR accounting and the duty of external auditors with CSR and of its practices by companies’ websites, google search, annual reports and CSR reports from all listed companies in the Muscat Securities Market, Oman. The data are used to critically examine and revise a previously published explanatory framework that identifies interrelationship of CSR marketing, accounting with CSR and auditing with CSR.

Results indicate that CSR marketing, CSR accounting and CSR auditing are closely interrelated for accepting and implementing CSR requirements by corporates. This finding suggests that the benefit of CSR marketing, the responsibility of BODs with CSR accounting and the duty of external auditors with CSR has positively influence on corporate sector. The finding helps to build good image by corporates.

Organizations from developing countries such as Oman should be aware of CSR marketing, CSR accounting and CSR auditing that affects decisions with CSR adoption and implementation by organizations that could also lead to competitive advantage when it operates in developed countries. Though, organizations in developed countries are also equip for higher expectations by applying innovative CSR initiatives.

To the best of the author’s knowledge, this is the first academic literature review on interrelationship of marketing, accounting and auditing with CSR based on evidence from an Oman context. The paper contributes by exploring the benefit of CSR marketing, the responsibility of BODs with CSR accounting and the duty of external auditors with CSR which influence on corporate sector.

This study aims to, firstly, develop a red flag checklist for cryptocurrency Ponzi schemes and, secondly, to test this red flag checklist against publicly available marketing material for Mirror Trading International (MTI). The red flag checklist test seeks to establish if MTI’s marketing material posted on YouTube^® (in the form of a live video presentation) exhibits any of the red flags from the checklist.

The study uses a structured literature review and qualitative analysis of red flags for Ponzi and cryptocurrency Ponzi schemes.

A research lacuna was discovered with regard to cryptocurrency Ponzi scheme red flags. By means of a structured literature review, journal papers were identified that listed and discussed Ponzi scheme red flags. The red flags from the identified journal papers were subsequently used in a qualitative analysis. The analyses and syntheses resulted in the development of a red flag checklist for cryptocurrency Ponzi schemes, with five red flag categories, containing 18 associated red flags. The red flag checklist was then tested against MTI’s marketing material (a transcription of a live YouTube presentation). The test resulted in MTI’s marketing material exhibiting 88% of the red flags contained within the checklist.

The inherent limitations in the design of using a structured literature review and the lack of research regarding the cryptocurrency Ponzi scheme red flags.

The study provides a red flag checklist for cryptocurrency Ponzi schemes. The red flag checklist can be applied to a cryptocurrency investment scheme’s marketing material to establish if it exhibits any of these red flags.

The red flag checklist can be applied to a cryptocurrency investment scheme’s marketing material to establish if it exhibits any of these red flags.

The study provides a red flag checklist for cryptocurrency Ponzi schemes.

The review examines the existing literature on blockchain-based small and medium enterprise (SME) finance and highlights its trend, themes, opportunities and challenges. Based on these factors, the authors create a framework for the existing literature on blockchain-based SME financing and lay down future research paths.

The review follows a systematic approach. It includes 53 articles encompassing multiple dimensions of blockchain-based SME finance, including peer-to-peer lending platforms, supply chain finance (SCF), decentralized lending protocols and tokenization of assets. The review critically evaluates these approaches' theoretical underpinnings, empirical evidence and practical implementations.

The review demonstrates that blockchain-based SME finance holds significant promise in addressing the credit gap by leveraging blockchain technology's decentralized and transparent nature. Benefits identified include reduced information asymmetry, improved access to financing, enhanced credit assessment processes and increased financial inclusion. However, the literature acknowledges several challenges and limitations, such as regulatory uncertainties, scalability issues, operational complexities and potential security risks.

The article contributes to the growing knowledge of blockchain-based SME finance by synthesizing and evaluating the existing literature. It also provides a framework for the existing literature in the area and future research paths. The study offers insights for researchers, policymakers and practitioners seeking to understand the potential of blockchain technology in filling the SME credit gap and fostering economic development through improved access to finance for SMEs.

The purpose of this study is to evaluate the current state of forensic accounting education in the Kingdom of Saudi Arabia (KSA), as well as to identify the desired aims and skills required to practice forensic accounting as a profession. It also seeks to understand the education and skills provided by KSA forensic accounting education programs, the job skills required by professional accountants and the skills required by professional accountants' employers.

The study is exploratory in nature. A convenience base sampling approach was used to select the academicians and practitioners working in KSA. Participants were requested to fill out an electronic questionnaire and rank each statement on a 5-point Likert score. The responses were converted and analyzed using the T-test, to evaluate the inter- and intra-group trends in the data.

The study included 58 responses from practitioners and 30 from academicians. Both groups mentioned that the classroom and the Internet were their primary source of forensic accounting information, especially in professional accounting qualifications. According to the participants, most of the institutions in KSA do not offer forensic accounting courses. Nonetheless, forensic accounting is critical for strengthening the credibility of financial reporting in courtrooms. The study finds subtle inter-group differences regarding the development of an ideal curriculum for forensic accounting, which translates to a bigger difference in curriculum development and practice skills. Both groups were optimistic about the future path of forensic accounting in KSA.

The study reports critical differences between the status of forensic accounting education and the skills required to practice forensic accountancy in KSA.