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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 paper aims to reviews the literature on applying visualization techniques to detect credit card fraud (CCF) and suspicious money laundering transactions.

In surveying the literature on visual fraud detection in these two domains, this paper reviews: the current use of visualization techniques, the variations of visual analytics used and the challenges of these techniques.

The findings reveal how visual analytics is used to detect outliers in CCF detection and identify links to criminal networks in money laundering transactions. Graph methodology and unsupervised clustering analyses are the most dominant types of visual analytics used for CCF detection. In contrast, network and graph analytics are heavily used in identifying criminal relationships in money laundering transactions.

Some common challenges in using visualization techniques to identify fraudulent transactions in both domains relate to data complexity and fraudsters’ ability to evade monitoring mechanisms.

This study aims to observe people’s decisions to commit fraud. This study is important in the current time because it provides insights into the development of fraudulent intentions within individuals.

The information used in this study is derived from semi-structured interviews, conducted with 16 high-ranking officials who are employed in Indonesian local government positions.

The study does not have strong evidence to support prior studies assuming that situational factors or social enablers have direct effects on fraud intentions. As suggested, individual factors which are related to moral reasoning (moral judgment and rationalisation) emerge as a consequence of social enablers. The significant role of that moral reasoning is to rationalise any fraud attempt as permissible conduct. As such, when an individual is capable of legitimising his/her fraud attempt into appropriate self-judgement, s/he is more likely to engage in fraudulent behaviours.

This study offers practical prescriptions in guiding the management to develop strategies to curb fraudulent behaviours. The study suggests that moral cognitive reasoning is found to be a parameter of whether fraud is an acceptable option or not. So, an understanding of observers’ moral reasoning is helpful in predicting the likelihood of fraud within an organisation or in detecting it.

This study provides a different perspective on the psychological pathway to fraud. It becomes a complement work for the fraud triangle to explain fraudulent behaviours. Specifically, it provides crucial insights into the underlying motivations that lead individuals to accept invitations to engage in fraudulent activities.

This study aims to explore personal and organizational factors in mitigating fraud intention through machiavellian personality, altruistic personality, religiousity, whistleblowing system, and accounting firm size. Companies will suffer greater losses if they cannot prevent fraudulent practices. The fraud hexagon theory is considered effective in detecting the possibility of fraud and the tendency of fraud motivated by personal and organizational factors. Therefore, the researchers examined several factors, including Machiavellian, altruism, religiosity, whistleblowing system and accounting firm size in mitigating fraud intention.

This study used a self-administered survey of accountants in Indonesia. The accountants were selected as the sample because the accounting profession has considerable potential in committing fraud. To avoid common method bias, the authors performed ex ante and ex post on the questionnaire. This research model was tested using structural equation modeling-partial least square.

The results revealed that personal factors in the form of Machiavellian, altruism and religiosity had a direct impact on decreasing fraud intention. In addition, whistleblowing system and accounting firm size were able to promote the effectiveness of fraud mitigation.

This study uses one profession, namely, accountants, so it requires further research to see the similarity of results in other professions.

The results contribute to managerial decision-making. Companies should include personal tests during employee recruitment because personal factors are the key to determining individual fraud behavior.

Combining personal factors and organizational factors can promote the success of the internal control system, so that individuals are encouraged to do ethical things.

This study combines personal and organizational factors in mitigating fraud, so as to know accurately which factors are most capable of mitigating fraud.

Money laundering weakens the role of the construction industry in stimulating economic growth. The purpose of this paper is to explore the connection between money laundering on the construction sites and undocumented foreign workers, based on a narrative drawn from a qualitative research.

Throughout the study, qualitative methods, i.e. interviews, site visits and document analysis, were used. However, the data for this paper was primarily derived from an interview. Thematic analysis was used to analyse the data.

The findings show that construction personnel who have access to the business’s financial affairs are the most likely to engage in illicit transactions. The size of the project as well as the multiple layers of organisations involved made it easy for launderers to operate. The appealing commission provided incentives to opportunistic personnel. In this regard, the wages for undocumented workers, which were primarily paid in cash, provided a considerable opportunity for the subcontracting organisations to engage in money laundering.

While the single narrative method with an omniscient narrator allows for the conceptualisation of a human experience with money laundering, the depth of information and interpretations is limited. Emerging qualitative research methods may be incorporated in the future to provide a more extensive information due to the fact that money laundering data is complex and sensitive that few people want to discuss.

The multidisciplinary approach of this research provides a pedagogical way that focuses primarily on the disciplines of construction management and business ethics to demonstrate real-world money laundering practice. Understanding such phenomenon on sites opens up key avenues for future research into developing an anti-money laundering regime for the construction industry.

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 case study will help to learn about the importance of pre-sanction precautionary measures before lending to self-help groups (SHGs), to learn about the potential lapses and errors while sanctioning SHG finance and to learn about the importance of bank’s guidelines and compliance before sanctioning loans.

This case study details the tenure of Seema in a rural branch of Safe Bank of India located in Haryana which she joined as a manager in the year 2016. She overachieved the target given by the district collector office, and going by the tide, she kept her reliance on the references provided by non-government organization (NGO) without complying the bank’s instructions. She committed errors while sanctioning the loans, which led towards the upsurge of non-performing assets of the branch. Later on, after investigation it was discovered that she did not follow fundamental bank’s instructions. In wake of those lapses and errors, how she could have avoided those lapses and secure the public money? What were the most important documents while granting agriculture finance and what due diligence she should have taken? How did she treat calls from the government departments? Was she right in trusting the suggestions of the NGO?

This case study caters to students of various streams, namely, management, business administration and law, and can be targeted at both undergraduate and postgraduate students. It could be suitable for several types of courses and students. Furthermore, this case study can also be targeted for various training programmes for bank employees and employees of various lending institutions engaged in agriculture finance and credit linkage programmes.

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CSS 1: Accounting and finance.