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This study aims to investigate the factors that influence asset misappropriation fraud among police officers in the Internal Security and Public Order (Malay: Keselamatan Dalam Negeri dan Ketenteraman Awam [KDNKA]) Department, Royal Malaysian Police (RMP).

Primary data were collected from a questionnaire-based survey and the data were analysed using descriptive analysis, correlation analysis and multiregression.

The element of pressure was found to have a negative relationship with asset misappropriation fraud. This result shows the uniqueness of the KDNKA Department in the RMP. The other three elements are found to have a significant positive relationship with asset misappropriation fraud.

This study’s findings can aid academicians in gaining a better understanding of the literature surrounding fraud diamond theory and aid the policymakers in recognizing the signs and possibilities of asset misappropriation fraud in public agencies.

To the best of the authors’ knowledge, this is the first study that uses the KDNKA Department which is the second largest department in RMP as a population in fraud study.

This study aims to empirically examine the influence of Islamic corporate social responsibility (ICSR) on social welfare moderated by financial fraud.

The method used was the mix method. The number of respondents was 410. They combined the moderate regression analysis with PROCESS Andrew F Hayes to test the research hypothesis. After conducting the survey, it was continued by conducting interviews with the village community and the head of the village.

The first finding of this study is that ICSR has a significant positive effect on social welfare. The second finding is that financial fraud weakens the influence of ICSR on social welfare. The results of the interviews also confirmed the two findings of this study.

The high level of bias in answering the questions is due to the low public knowledge of ICSR. In addition, the interviews still needed to involve the oil and gas companies and government.

The main implication is improving social welfare, especially for those affected by offshore oil drilling. Furthermore, stakeholders are more sensitive to the adverse effects of financial fraud. Finally, to make drilling companies more transparent and on target in implementing ICSR.

The main novelty in this research is using of the mixed method. In addition, applying financial fraud as a moderating variable is rarely studied empirically.

This study aims to investigate the influence of information and communication technology (ICT) capabilities on supply chain fraud and sustainability within the context of Ghana’s small and medium-sized enterprises (SMEs). Additionally, the research explores the mediating role of supply chain fraud in the relationship between ICT capabilities and supply chain sustainability.

Data were collected from 102 respondents within Ghana’s SME sector, and the research employed the dynamic capability theory as the conceptual framework. The study utilized partial least squares-structural equation modeling (PLS-SEM) to develop and analyze the proposed model.

The results of the study reveal a significant reduction in supply chain fraud attributable to enhanced ICT capabilities within Ghanaian SMEs. Moreover, ICT capabilities exert a significant positive influence on supply chain sustainability. Importantly, supply chain fraud emerges as a mediator, elucidating its role at the nexus of supply chain sustainability and ICT capabilities.

This research contributes to the limited body of evidence on the interconnectedness of ICT capabilities, supply chain fraud and supply chain sustainability, particularly within the context of Ghanaian SMEs. Notably, this study pioneers an examination of the mediating impact of supply chain fraud on the relationship between ICT capabilities and supply chain sustainability.

The rapid growth of the mobile money industry has been matched by a rise in mobile money fraud. The technology required to apprehend perpetrators of such fraud is nonexistent in most developing countries. Hence, the need for individuals to be willing to pay for insurance against such frauds is crucial. This paper aims to examine individuals’ willingness to pay for insurance against mobile money fraud in Ghana.

The paper uses nationally representative data collected from 4,266 adults (persons 18 years and above) in Ghana. Individuals’ willingness to pay premiums for protection against mobile money fraud was elicited by a single-bound dichotomous choice and open-ended contingent valuation designs.

On average, 24.34% of Ghanaians are willing to pay premiums for insurance against mobile money frauds, with more men (26.37%) being willing than women (22.56%). Similarly, the average monthly premium that men are willing to pay for protection against mobile money fraud is GH¢32.16 (US$8.16), while that of women is GH¢22.5 (US$5.62). Furthermore, the results show that years of schooling, income, previous fraud experience, and using the accounts for saving are all positively associated with willingness to pay. However, using other networks apart from MTN has a negative association with willingness to pay.

To the best of our knowledge, this is the first study that examines willingness to pay for insurance against mobile money fraud. Thus, this is the first that estimate quantitatively how much mobile account holders will pay as premiums for insurance against mobile money fraud.

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 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 chapter focuses on a case study of Kareem Exchange Company and its use of big data analysis to detect and prevent fraud and suspicious financial transactions. The chapter describes the various phases of the big data analysis cycle, including discovery, data preparation, model planning, model building, operationalization, and communicating results, and how the Kareem Exchange Company team implemented each phase. This chapter emphasizes the importance of identifying the business problem, understanding the resources and stakeholders involved, and developing an initial hypothesis to guide the analysis. The case study results demonstrate the potential of big data analysis to improve fraud detection capabilities in financial institutions, leading to informed decision making and action.

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 the effect of professional commitment, commitment to ethics, internal locus of control and emotional intelligence on the ability to detect fraud through reduced audit quality behaviors.

The analysis unit is the internal auditor in internal control unit at state Islamic religious higher education in Indonesia. Data processing used covariance-based structural equation modeling using Lisrel Software and the Sobel test to verify the direct and indirect effects.

This study found empirical evidence that professional commitment and emotional intelligence positively impact the ability to detect fraud. Commitment to ethics and emotional intelligence has a negative effect on reduced audit quality behaviors. Furthermore, this study also provides that commitment to ethics and emotional intelligence indirectly impacts on the ability to detect fraud through reduced audit quality behaviors.

The organization periodically monitors auditors’ behaviors, especially reduced audit quality behaviors, during the audit process and encourages regulators to formulate policies related to increasing the ability to detect fraud.

This study provides knowledge regarding the driving force of internal auditors to mitigate reduced audit quality behaviors and increase the ability to detect fraud.

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.