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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.

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 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.

Existing studies suggest that negative impacts emanating from corporate fraud revelations may diffuse to other firms through lower trust and lower market participation. Extending this literature stream, the authors examine whether corporate fraud revelations are associated with higher costs of raising capital through initial public offerings (IPOs) for industry peers.

The authors employ several analysis techniques including univariate analysis, multivariate regressions, propensity score matching methodology, and probit estimation. The sample consists of 3,015 US IPO firms for the 1996–2021 period.

By adopting US private securities class action lawsuits as a proxy for the presence of corporate fraud, the authors find that fraud revelations are associated with higher IPO underpricing, higher post-IPO stock return volatility and increased likelihood of withdrawal from the offering for industry peers. The findings are robust to alternative industry definitions and litigation proxies and to the inclusion of a battery of controls, including industry, state and year fixed effects.

This study presents private firms with an additional industry litigation factor to consider when assessing the marginal costs of going public.

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 highlight the risks and threats posed by crowdfunding. It also looks at the new European Union regulation on crowdfunding, which is intended to give participants confidence that there will be specific minimum regulatory standards to protect parties against mis-selling issues affecting some platforms.

This paper is based upon a thorough literature review.

Crowdfunding is an essential alternative for financing commercial and non-commercial projects. Although it is a fast-growing digital financial tool, it can also be considered extremely risky. It can be an ideal platform for money laundering and can facilitate the financing of terrorism and fraud.

Crowdfunding is still in its infancy, so the literature has not yet sufficiently addressed the compliance risks of crowdfunding. As a result, there is a significant research gap. Thus, this study aims to analyse and propose suggestions to mitigate the risks that all crowdfunding stakeholders may face when deciding to participate in a crowdfunding activity or when they want to set one up.

This study aims to investigate Bangladesh’s e-commerce regulations in light of the growing criticism that they are insufficient to curb predicate crimes like fraud and money laundering in the online marketplace.

This study used the exploratory design to examine the latest ministerial directives and laws governing e-commerce in Bangladesh to determine why they cannot prevent fraudulent activities in this promising sector and identify potential solutions.

Bangladesh’s regulatory responses to e-commerce fraud prevention and detection are reactive and inadequate. Regulators are unwilling and unable to enforce available legal provisions for various reasons, including a lack of knowledge and coordination among the agencies.

This paper focuses solely on the legal and regulatory framework in place to combat e-commerce fraud. Other critical issues, such as consumer rights, privacy and data protection in e-commerce, are not addressed.

The findings of this study will assist policymakers in revising current regulatory approaches to e-commerce to protect this sector from criminal abuse.

This study looked into the possibility of using a proactive risk-based approach in the e-commerce sector, similar to what the Bangladesh Financial Intelligence Unit does in the financial sector.

The aim of this study is to approach the way in which corporate governance influences the occurrence of financial fraud, as expressed by the M-Beneish score. In order to get further into the topic, we have first computed a corporate governance score based on the comply-explain statement and then selected a few elements that are part of the corporate governance reporting: equilibrium of board members (EQUIL), independence of board members (INDEP), selection of the board members (NOM), remuneration policy (REM), audit committee (AUDIT) and the proportion of female directors on boards (GenF). They were tested, one by one, using the financial fraud score to see the way in which they interact.

The study is conducted on a sample of 65 companies listed on the Bucharest Stock Exchange (BSE) for the 2016–2022 period. The data were processed using three-stage general least square [general least squares (GLS), with iteration, igls and option] with a common first-order panel-specific autocorrelation correction, so as to explain how a poor adoption of the corporate governance score and its elements has a negative implication for the M-Beneish score, controlling for the auditor opinion, type of auditing company and if the company is privately owned.

The results support most of our research hypothesis, revealing that a poor adoption of the corporate governance score and its components – AUDIT, EQUIL, INDEP and GenF – negatively influences the M-Beneish score, i.e. a low corporate governance score will lead to an increase in financial fraud. This is an encouraging aspect, for an improved adoption of the corporate governance principles reduces the occurrence of financial fraud.

This is a study that concerns the relationship between corporate governance and financial fraud for the case study for Romania.

The study highlights the importance of adopting the corporate governance code applied to the Romanian business environment. By measuring the presence of financial fraud appearance through the M-Beneish score, we have managed to outline the negative relationship between the two components. Thus, it is an important aspect of which companies should take account, so they will have long-term benefits and ensure the continuity of the business.

The policy implications of this project are for policymakers, so that they will understand how a good corporate governance mechanism will enhance high-performing businesses. Different aspects regarding corporate governance were validated and are in the process of being validated. Managers can extract and try to understand and apply the good characteristics of corporate governance for the well-being of their companies. At a broader level, the macroeconomic environment will increase its own well-being while encouraging market players to enhance qualitative corporate governance reporting. There is no doubt that corporate governance has a positive impact on businesses.

The study highlights the importance of adopting the corporate governance code as applied to the Romanian business environment. By measuring the occurrence of financial fraud using the M-Beneish score, we have managed to outline the negative relationship between the two components. Therefore, this is an important aspect that companies should take into account in order to have long-term benefits and ensure the continuity of their business.

A crucial contemporary policy question for financial service organizations of being resilient across the globe calls for rethinking and renovating by adopting and adapting to the technologies of artificial intelligence (AI). The purpose of this study is to propose a policy framework for adoption of AI in the finance sector by exploring the driving factors through systems approach.

Based on literature review and discussions with experts from both industry and academia, nine enablers were shortlisted, which were used in the questionnaire survey to determine ranks of enablers. Further, the study developed the interpretive structural model (ISM) with the help of experts.

The ISM digraph developed with the help of the experts, resulted in the enablers like anticipated profitability, contactless solutions, credit risk management and software vendor support as dependent factors and stood at the top of the ISM. On the other hand, factors like availability of the data, technical infrastructure and funds are the most driving factors, which lie on the bottom of the ISM.

The study provides implications and policy recommendations for the practicing managers and government agencies approaching the digital transformation towards the adoption of AI in the finance ecosystem.

The paper uses the systems approach for the development of the ISM of the enabling factors for the adoption of AI technology. On the basis of the results, the study proposes a policy framework to accelerate the functioning of the finance ecosystem with AI technology.

Course evaluations are formative and are used to evaluate learnings of the students for a course. Anomalies in the evaluation process can lead to a faulty educational outcome. Learning analytics and educational data mining provide a set of techniques that can be conveniently applied to extensive data collected as part of the evaluation process to ensure remedial actions. This study aims to conduct an experimental research to detect anomalies in the evaluation methods.

Experimental research is conducted with scientific approach and design. The researchers categorized anomaly into three categories, namely, an anomaly in criteria assessment, subject anomaly and anomaly in subject marks allocation. The different anomaly detection algorithms are used to educate data through the software R, and the results are summarized in the tables.

The data points occurring in all algorithms are finally detected as an anomaly. The anomaly identifies the data points that deviate from the data set’s normal behavior. The subject which is consistently identified as anomalous by the different techniques is marked as an anomaly in evaluation. After identification, one can drill down to more details into the title of anomalies in the evaluation criteria.

This paper proposes an analytical model for the course evaluation process and demonstrates the use of actionable analytics to detect anomalies in the evaluation process.