Search results

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 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 provide a systematic literature review (SLR) on contemporary cardinal money mule issues.

This paper reviews the most common money mule themes in perpetrating financial crime activities, especially its roles, recruitment and awareness. A systematic review protocol called preferred reporting items for systematic review and meta-analysis protocols is adopted for this study.

Money mules are used by organized criminal groups (OCG) or fraudster to launder illicit funds from outrageous criminal activities. They allow their accounts to be used for money laundering by OCG. The attacker, OCG or fraudsters would layer the stolen funds using money mule accounts. These money mules are recruited using various approaches, oftentimes deceived by opulent lifestyles to captivate the interest of potential money mules.

This paper presents money mule awareness needed by accountant, bank employees and the society. It is an unprecedented SLR on money mule. This paper will be beneficial for future money mule researchers, enforcement agencies and practitioners in banking industry.

This paper aims to examine the options available to arbitrators when they suspect money laundering during arbitration proceedings, considering their compatibility with fundamental principles and concepts of arbitration.

Using a doctrinal analysis approach, the paper draws on legal principles, antimoney laundering regulations and relevant literature to explore the topic. It considers relevant international treaties, standards set by the financial action task force on money laundering, cases and arguments from legal analysts and experts.

The paper identifies three options for arbitrators: disregarding suspicions, initiating an investigation or terminating the proceedings. Disregarding suspicions is deemed inappropriate, as it may facilitate the concealment of financial crimes. Initiating an investigation is seen as a preferable option, aligning with the arbitrator’s role and the public interest in nullifying contracts linked to criminal conduct. Terminating the proceedings is not recommended, as it contradicts the principle of natural justice. The paper emphasizes the importance of reasonable grounds for suspicions, notifying the parties, and allowing them to address the concerns.

This paper contributes to the existing literature by comprehensively analyzing the compatibility of these options with arbitration principles and concepts. It underscores the need for clear laws and directives to guide arbitrators in addressing financial crimes within the arbitration process, maintaining a balance between party autonomy and preventing the misuse of arbitration for illicit activities.

In past decades, artificial neural network (ANN) models have revolutionised various stock market operations due to their superior ability to deal with nonlinear data and garnered considerable attention from researchers worldwide. The present study aims to synthesize the research field concerning ANN applications in the stock market to a) systematically map the research trends, key contributors, scientific collaborations, and knowledge structure, and b) uncover the challenges and future research areas in the field.

To provide a comprehensive appraisal of the extant literature, the study adopted the mixed approach of quantitative (bibliometric analysis) and qualitative (intensive review of influential articles) assessment to analyse 1,483 articles published in the Scopus and Web of Science indexed journals during 1992–2022. The bibliographic data was processed and analysed using VOSviewer and R software.

The results revealed the proliferation of articles since 2018, with China as the dominant country, Wang J as the most prolific author, “Expert Systems with Applications” as the leading journal, “computer science” as the dominant subject area, and “stock price forecasting” as the predominantly explored research theme in the field. Furthermore, “portfolio optimization”, “sentiment analysis”, “algorithmic trading”, and “crisis prediction” are found as recently emerged research areas.

To the best of the authors’ knowledge, the current study is a novel attempt that holistically assesses the existing literature on ANN applications throughout the entire domain of stock market. The main contribution of the current study lies in discussing the challenges along with the viable methodological solutions and providing application area-wise knowledge gaps for future studies.

This study aims to determine the impact of forensic accounting, probability of detections, tax penalties, government spending, tax justice and tax ethics on value-added tax (VAT) evasion.

The study uses partial least squares-structural equation modeling to examine the connection between tax sanction, probability of detection, tax ethics, tax justice, forensic accounting and government spending on VAT evasion based on 248 responses collected from the retail industry in Jordan.

The findings also demonstrate that there is a negative correlation between tax sanctions, probability of detection, tax ethics, tax justice, forensic accounting, government spending and VAT evasion efficiency.

The results, considering forensic accounting and government expenditure considerations, may emphasize the importance of the tax sanction, probability of detection, tax ethics, adoption of tax justice in the public sector and tax authority. Additionally, the findings are important for regulators and decision-makers in announcing new laws and strategies for VAT evasion.

It turns out that the tax authority and public sector can definitely improve their capacity to protect public funds and limit VAT evasion practices within SMEs by adopting increased tax sanctions, probability of detection, tax ethics, tax justice, forensic accounting and government spending.

Numerous studies have been conducted at the individual level in the context of income tax on the link between tax punishment, probability of detection, tax ethics, tax justice, forensic accounting and tax evasion. This study expands on the scant evidence of this connection to the retail business in the context of VAT avoidance. Additionally, it advances prior studies by integrating fresh elements, such as forensic accounting and government expenditure, that have never been considered in connection to VAT evasion in the retail sector.

The construction industry sector is developing rapidly, especially with the increasing pace of the Fourth Industrial Revolution in this sector. Construction projects can benefit from greater integration and collaboration between their technologies and processes to reap the advantages and keep pace with the recent significant technological and managerial techniques developments. Therefore, this study aims to delve into and investigate building information modeling (BIM) and Lean Construction (L.C.) with a concentration on the potential BIM–lean interactions synergy and integration in the Jordanian construction industry.

This study takes exploratory nature, followed by the deductive research approach, and is designed to be a mono-quantitative research methodology. Moreover, the sampling technique is non-probability convenience sampling, and the research strategy is implemented through a questionnaire used and analyzed by using Statistical Package for Social Science to conduct descriptive and inferential statistical analysis and verify the reliability and validity through proper tests.

The BIM–lean interactions synergy and integration findings revealed that eliminating waste (time, cost, resources), promoting continuous improvement (Kaizen) and standardizing as lean construction principles are the most significant and agreeable toward achieving BIM–lean interactions synergy. On the other hand, “High 3D Visualization Modelling” was the most significant BIM function, followed by “Rapid and Auto-Generation of Documents and Multiple Design Alternatives” and “Maintenance of Information and Design Model Integrity.” Moreover, based on the relative importance index (RII) values, “Lack of Technical Expertise in BIM-LEAN” is the most significant challenge with a 0.89 value of RII, followed by “Lack of Government Direction and Standard Guidelines” with a 0.88 value of RII and “Financial considerations” with a 0.83 value of RII.

This study will help provide a new detailed overview that investigates the effects and expected benefits of integrating BIM processes and technological functionalities with lean construction principles within a synergetic environment. Moreover, the study will increase the awareness of using new technologies and management approaches in the architectural, engineering and construction industry, seeking to achieve integration between these technologies to reach ideal results in terms of the outputs of construction operations.

The purpose of this study is to define and investigate the governance requirements of supply chain finance (SCF).

A qualitative analysis of 849 news articles published in UK newspapers (2000–2022) using the Gioia method.

SCF governance relies on developing capacities for reflexive scrutiny at two stages: (1) prior to entering into an SCF relationship and (2) during its operation. Based on the notion of SCF as a complex adaptive system, we theorise SCF governance requirements as a dual-layered semipermeable boundary. The semipermeability of the two layers allows for a dynamic exchange between the SCF system and its environment. The first layer is the capacity to selectively enable or control the entry and access of certain actors and practices into the SCF system. The second layer is a capacity for ongoing scrutiny of the SCF operation and its development. Further, we identify five aspects of governance to be enabled, i.e. enhancing adaptability, building confidence, improving efficiency, advancing technology and promoting transparency; and four aspects to be controlled, i.e. preventing abuse of power, curbing fraud risk, constraining operational risk and restricting risky extensions to SCF practices.

Our dynamic framework can guide supply chain (SC) members in making decisions about whether to participate, or continue to operate, in an SCF relationship. Moreover, the findings have implications for policymakers and authorities who oversee entry/access and the involvement of SCF providers, particularly, fintech firms.

The study contributes to both the SC and governance literature by providing a systematic analysis of what SCF governance has to accomplish. Our novel contribution lies in its analysis of SCF governance based on a complex adaptive system approach, which expands the existing literature where SCF is described in rather static terms. More specifically, it suggests a need for a dynamic duality of SCF governance through the semipermeable boundary that selectively enables and controls certain SCF actors and practices.

This study aims to investigate the moderating effect of the COVID-19 epidemic on the relationship between key audit matter (KAM) and auditing quality.

The authors use the ordinary least squares regression on data from 942 firm-year observations of Jordanian non-financial institutions across the period (2017–2022) to test the hypotheses. The authors use content analysis method to measure levels of KAM disclosure.

The investigation’s findings highlight the importance of KAM disclosure in achieving audit quality in line with international standard on auditing no. 701 (ISA-701) requirements. COVID-19 is also found to have a positive relationship with audit quality, further confirming the crisis’s devastating impact on audit complexity and risks and providing evidence for the need for supplementary, high-quality audit services. Due to the correlation between KAM disclosure and increased auditor workload and responsibility, the analysis reveals that the COVID-19 factor strengthens the link between KAM disclosure and audit quality.

This study has the potential to be used as a basis for the creation of a new regulation or standard regarding the reporting of unfavourable events in financial filings. This study’s findings provide standard-setters, regulators and policymakers with current empirical data on the effects of implementing ISA-701’s mandate for external auditors to provide more information on KAM. The COVID-19 crisis offers a suitable setting in which to examine the value of precautionary disclosures in times of economic uncertainty, as well as the significance of confidence interval disclosures and the role of external auditing in calming investor fears. This analysis is helpful for stakeholders, regulatory agencies, standard-setters and readers of audit reports who are curious about the current state of KAM disclosures and the implementation of ISA-701. The results may have ramifications for academia in the form of a call for more evidence expanding this data to other burgeoning fields to have a clear explanation of the real impact of reporting KAM on audit practices.

To the authors’ awareness, this research is one of the few empirical studies on the effect of the COVID-19 crisis on auditing procedures, and more specifically, the effect of disclosures on KAM by external auditors on audit quality. This study’s findings represent preliminary scientific evidence linking the pandemic to business performance. Minimal research has been done on how auditors in developing nations react to pandemic investor protection and how auditors’ enlarged reporting responsibilities affect them. The vast majority of auditing studies have been conducted in a highly regulated system, so this research contributes by examining audit behaviour in a weak legal context.

The main purpose of the study was to synthesise the role of COVID-19 social media messages and indigenous religious beliefs on public health promotion initiatives among rural consumers in Zimbabwe.

A qualitative approach was adopted. Population consisting of 15 interviews and six focus groups was purposively sampled from Manicaland, Mashonaland Central and Masvingo provinces in Zimbabwe. A thematic approach was used to present and analyse the data.

Rural consumers believed WhatsApp messages posted by people whom they know or influential personnel like health workers. Credibility of WhatsApp messages was enhanced through its ability to send videos and audios. Teachings and indoctrination by indigenous churches and misinformation were found to be an impediment in believing COVID-19 WhatsApp messages and vaccination by rural consumers. Faith healers in indigenous churches used various practices and artefacts like holy water, stone pebbles, clay pots, flags and wooden rods to pray and treat patients suffering from COVID-19 and other ailments.

Social media messages, religious teachings and indoctrination may be a hindrance to rural consumers in adopting government public health promotion initiatives; hence, public health professionals need prior emic understanding and co-option of local leadership in vaccination campaigns.

This study outstretches the theoretical landscape in consumer behaviour and also practical contribution to health practitioners and marketers on breaking indigenous religious barriers and social media misconceptions on vaccination uptake through promotional strategies earmarked for rural consumers.