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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.

The phenomenon of corruption requires extra handling to achieve zero corruption. The purpose of this paper is to examine the integrated governance, risk management and compliance (GRC) implementation, the quality of internal audits and management's commitment to improving the ability to detect corruption and its impact on the company's financial performance.

This paper used primary and secondary data. Financial statement data and survey results from participants in 69 state-owned companies were analyzed using the Partial Least Square method.

There was a positive and significant effect of the integrated GRC implementation, quality of internal audit and management's commitment to increasing the organization's internal capability in detecting corruption. However, the failure to detect corruption mediates the effect of management commitment on financial performance. Besides, the organization's three internal factors could be better because their functions could be more optimal and require further improvement.

State-owned companies are continuing to be restructured, so these results can be helpful for now. However, they must update continuously with developments related to the composition and classification of state-owned companies.

Organizations can improve their ability to detect corruption in the workplace by using an early warning system such as the integrated GRC, internal audit quality and a high commitment from management.

To the author's limited knowledge, empirical research on integrated GRC implementation, internal audit quality and management commitment are still rare if they improve the detection of corruption ability. It uses the factors that cause corruption in the fraud hexagon to analyze the financial performance.

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 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.

This study aims to address the relationship between economic complexities (EC) and the green economy (GE) with fraud in the listed companies on the Tehran stock exchange. The authors study whether EC and GE increase the detection of financial statement fraud.

The authors used a multiple regression model based on the panel data method and fixed effect model to test hypotheses. The sample includes 1,351 companies listed on the Iranian stock exchange from 2014 to 2021.

The results show a negative and significant relationship between EC and GE with financial statement fraud.

Since this research is the first to address the mentioned topic in emerging markets, it provides helpful insights for financial statement users, analysts and legal entities. The study fills the literature gap and promotes knowledge regarding its relevant literature.

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.

This study aims to investigate the perceived willingness to adopt and use Forensic Accounting and Investigation Standards (FAIS) in Forensic Accounting and Investigation (FAI) assignments. The study also analyses the usefulness of FAIS in achieving the principle of natural justice (PNJ) concerning fairness.

The respondents comprised 118 accounting professionals whose online survey responses were analyzed descriptively. This study also uses a 2 × 2 contingency analysis representing two levels of usefulness and fairness.

The results revealed that FAIS 410 received the highest mean rating while FAIS 240 received the lowest mean rating in willingness to adopt and use FAIS, and most of the standards were related to the PNJ concerning fairness. The study shows the accounting professionals’ readiness to adapt and flourish with the help of these Standards in FAI assignments.

The findings of this study will increase practitioners’ awareness of the usefulness and fairness of FAIS, which will enhance their understanding of the significance of implementing these newly developed standards to harmonize the investigative process in forensic audits. Additionally, the findings may encourage regulators, researchers, accounting bodies and their members to adopt and conduct further FAIS studies that can advance financial crime prevention, detection and investigation knowledge.

This paper substantially contributes to the literature as it is the first to examine the usefulness and fairness of “Forensic Accounting and Investigation Standards” in the context of forensic audits and investigations, which has not been previously explored.

This paper aims to investigate the impact of political stability on corruption by drawing upon a sample encompassing both developed and developing European and Asian countries.

The dataset, sourced from the Refinitiv database, spans from July 2014 to May 2022. Panel data techniques, specifically pooled estimation and dynamic panel data [generalized method of moments (GMM)] are employed. The analysis encompasses both fixed and random effects models to capture country-specific cross-sectional effects. To validate our findings, we perform a robustness test by including in the investigation four control variables, namely poverty, type of governance, economic freedom and inflation. To test heterogeneity, the dataset is further divided into two distinct subsamples based on the countries’ locations.

Empirical findings substantiate that political stability (viewed as the risk of government destabilization) has a positive and significant impact on corruption in all analyzed samples of European and Asian countries, though some differences are observed in various subsamples. When we take into account the control variables, these analysis results are robust.

This research provided a panel data analysis with GMM, while other empirical methodologies could also be used, like the difference-in-difference approach. However, our results should be validated by extending the time and the sample to a worldwide sample and using alternative measures of corruption and political stability. Moreover, our focus was on a linear and unidirectional relationship between the considered variables, but it would be interesting to test in our further research a non-linear and bidirectional correlation between them. Furthermore, we have introduced in the robustness test only four economic variables, but to consolidate our findings, we plan to include socioeconomic and demographic variables in future studies.

These outcomes imply that authorities should be aware of the necessity of implementing anti-corruption policies designed to establish effective agencies and enforcement structures for combating systemic corruption, to improve the political environment and the quality of institutions and to apply coherent economic strategies to accelerate economic growth because higher political stability and sustainable development determine a decrease in levels of corruption.

At the microeconomic level, the survival of organizations may be in danger from new types of corruption and money laundering. Therefore, in order to prevent financial harm, the top businesses worldwide should respond to instances of corruption through strengthened supervisory procedures. This calls for the creation of a mechanism inside the code of conduct where correct reporting of suspected situations of corruption would have a prompt procedure to be notified of. To avoid corruption in operational procedures, national plans and policies should be developed by government officials, executives and legislators on a national level, as well as by senior management and the board of directors on an organizational level. This might lower organizations' extra corruption-related expenses, assure economic growth and improve global welfare.

A novel feature of our research resides in its broad examination of a sizable sample of European and Asian countries regarding the nexus between corruption and political stability. The paper also investigates a less explored topic in economic literature, namely the impact of political stability on corruption. Furthermore, the study depicts policy recommendations, outlining effective and reasonable measures aimed at improving the political landscape and combating corruption.

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.

The purpose of this study is to investigate the impact of audit committee characteristics on firm performance. In particular, the authors employ the random-effects variant of the Hunter–Schmidt meta-analyze procedure to analyze the effects of key audit committee attributes, namely audit committee independence, audit committee expertise, audit committee size, audit committee meeting along with big four impact on firm performance. The authors hope to gain a better understanding of the function of audit committees in enhancing firm performance and to uncover potential discrepancies in prior findings due to varying economic levels or performance metrics.

This study uses the Hunter–Schmidt method to conduct a meta-analysis of 39 previous studies published between 2012 and 2022 to investigate the relationship between audit committee characteristics and firm performance.

The results indicate that audit committee independence, expertise, size and affiliation with the big four have a significant and positive effect on firm performance, while audit committee meetings have a non-significant effect. Furthermore, findings suggest that companies should carefully consider the contextual factors that may impact the effectiveness of their corporate governance structures, such as economic level, when designing and implementing governance mechanisms.

This study is significant as it is the first to combine and analyze previous research on this topic and highlights the importance of certain audit committee characteristics in enhancing financial reporting quality and corporate governance.