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1 – 10 of 101
Article
Publication date: 5 March 2024

Sana Ramzan and Mark Lokanan

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Journal of Accounting Literature, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-4607

Keywords

Article
Publication date: 28 February 2023

Magda Siahaan, Harry Suharman, Tettet Fitrijanti and Haryono Umar

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Practical implications

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.

Originality/value

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.

Details

Journal of Financial Crime, vol. 31 no. 2
Type: Research Article
ISSN: 1359-0790

Keywords

Article
Publication date: 17 March 2023

Yulianti Yulianti, Mohammad Wahyudin Zarkasyi, Harry Suharman and Roebiandini Soemantri

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Practical implications

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.

Originality/value

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

Details

Journal of Islamic Accounting and Business Research, vol. 15 no. 3
Type: Research Article
ISSN: 1759-0817

Keywords

Article
Publication date: 20 March 2024

Clinton Free, Stewart Jones and Marie-Soleil Tremblay

The purpose of this paper is to synthesize insights from the emerging work in accounting on greenwashing and sustainability assurance and propose an agenda for future research in…

Abstract

Purpose

The purpose of this paper is to synthesize insights from the emerging work in accounting on greenwashing and sustainability assurance and propose an agenda for future research in this area.

Design/methodology/approach

This article offers an original analysis of papers published on greenwashing and sustainability assurance research in the field of accounting. It adopts a systematic literature review and a narrative approach to analyse the dominant themes and key findings in this new and rapidly evolving field. From this overview, specific avenues for future research are identified.

Findings

In the past few years there has been a substantial spike in concern relating to greenwashing among academics, practitioners, regulators and society. This growing concern has only partly been reflected in the research literature. To date, research has primarily focused on: (1) the characteristics of firms adopting sustainability assurance, (2) the challenges facing sustainability auditors, (3) the development of appropriate assurance standards and regulations, and (4) capital market responses to greenwashing and sustainability auditing/assurance. Three key future research issues with respect to greenwashing are identified: (1) the future of standard-setter attempts to regulate greenwashing, (2) professional jockeying in sustainability reporting assurance, and (3) capital market opportunities and challenges relating to greenwashing and assurance.

Originality/value

Despite the profound economic and reputational impact of greenwashing and the rapid development of sustainability assurance services, research in accounting remains fragmented and emergent. This review identifies avenues offering considerable scope for inter-disciplinarity and bridging the divide between academia and practice.

Details

Journal of Accounting Literature, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-4607

Keywords

Article
Publication date: 5 September 2023

Zainab Ahmadi, Mahdi Salehi and Mahmoud Rahmani

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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

Originality/value

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.

Details

Journal of Financial Crime, vol. 31 no. 2
Type: Research Article
ISSN: 1359-0790

Keywords

Open Access
Article
Publication date: 7 July 2023

Elda du Toit

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…

4661

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Journal of Financial Crime, vol. 31 no. 2
Type: Research Article
ISSN: 1359-0790

Keywords

Article
Publication date: 5 May 2021

Samrat Gupta and Swanand Deodhar

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is…

Abstract

Purpose

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is critical for analyzing complex systems in various areas ranging from collaborative information to political systems. Given the different characteristics of networks and the capability of community detection in handling a plethora of societal problems, community detection methods represent an emerging area of research. Contributing to this field, the authors propose a new community detection algorithm based on the hybridization of node and link granulation.

Design/methodology/approach

The proposed algorithm utilizes a rough set-theoretic concept called closure on networks. Initial sets are constructed by using neighborhood topology around the nodes as well as links and represented as two different categories of granules. Subsequently, the authors iteratively obtain the constrained closure of these sets. The authors use node mutuality and link mutuality as merging criteria for node and link granules, respectively, during the iterations. Finally, the constrained closure subsets of nodes and links are combined and refined using the Jaccard similarity coefficient and a local density function to obtain communities in a binary network.

Findings

Extensive experiments conducted on twelve real-world networks followed by a comparison with state-of-the-art methods demonstrate the viability and effectiveness of the proposed algorithm.

Research limitations/implications

The study also contributes to the ongoing effort related to the application of soft computing techniques to model complex systems. The extant literature has integrated a rough set-theoretic approach with a fuzzy granular model (Kundu and Pal, 2015) and spectral clustering (Huang and Xiao, 2012) for node-centric community detection in complex networks. In contributing to this stream of work, the proposed algorithm leverages the unexplored synergy between rough set theory, node granulation and link granulation in the context of complex networks. Combined with experiments of network datasets from various domains, the results indicate that the proposed algorithm can effectively reveal co-occurring disjoint, overlapping and nested communities without necessarily assigning each node to a community.

Practical implications

This study carries important practical implications for complex adaptive systems in business and management sciences, in which entities are increasingly getting organized into communities (Jacucci et al., 2006). The proposed community detection method can be used for network-based fraud detection by enabling experts to understand the formation and development of fraudulent setups with an active exchange of information and resources between the firms (Van Vlasselaer et al., 2017). Products and services are getting connected and mapped in every walk of life due to the emergence of a variety of interconnected devices, social networks and software applications.

Social implications

The proposed algorithm could be extended for community detection on customer trajectory patterns and design recommendation systems for online products and services (Ghose et al., 2019; Liu and Wang, 2017). In line with prior research, the proposed algorithm can aid companies in investigating the characteristics of implicit communities of bloggers or social media users for their services and products so as to identify peer influencers and conduct targeted marketing (Chau and Xu, 2012; De Matos et al., 2014; Zhang et al., 2016). The proposed algorithm can be used to understand the behavior of each group and the appropriate communication strategy for that group. For instance, a group using a specific language or following a specific account might benefit more from a particular piece of content than another group. The proposed algorithm can thus help in exploring the factors defining communities and confronting many real-life challenges.

Originality/value

This work is based on a theoretical argument that communities in networks are not only based on compatibility among nodes but also on the compatibility among links. Building up on the aforementioned argument, the authors propose a community detection method that considers the relationship among both the entities in a network (nodes and links) as opposed to traditional methods, which are predominantly based on relationships among nodes only.

Details

Information Technology & People, vol. 37 no. 2
Type: Research Article
ISSN: 0959-3845

Keywords

Article
Publication date: 14 April 2023

Md. Zahurul Haq

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Practical implications

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

Originality/value

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.

Details

Journal of Money Laundering Control, vol. 27 no. 3
Type: Research Article
ISSN: 1368-5201

Keywords

Article
Publication date: 13 March 2023

Anagha Vaidya and Sarika Sharma

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Interactive Technology and Smart Education, vol. 21 no. 1
Type: Research Article
ISSN: 1741-5659

Keywords

Article
Publication date: 23 January 2024

Shreya Sangal, Gaurav Duggal and Achint Nigam

The purpose of this research paper is to review and synthesize the role of blockchain technology (BCT) in various types of illegal activities, including but not limited to fraud…

Abstract

Purpose

The purpose of this research paper is to review and synthesize the role of blockchain technology (BCT) in various types of illegal activities, including but not limited to fraud, money laundering, ransomware attacks, firearms, drug tracking, cyberattacks, identity theft and scams.

Design/methodology/approach

The authors conducted a review of studies related to illegal activities using blockchain from 2015 to 2023. Next, a thematic review of the literature was performed to see how these illegal activities were conducted using BCT.

Findings

Through this study, the authors identify the relevant themes that highlight the major illegal activities performed using BCT, its possible steps for prevention and the opportunities for future developments. Finally, the authors provide suggestions for future research using the theory, context and method framework.

Originality/value

No other research has synthesized the illegal activities using BCT through a thematic approach to the best of the authors’ knowledge. Hence, this study will act as a starting point for future research for academic and technical practitioners in this area.

Details

Journal of Information, Communication and Ethics in Society, vol. 22 no. 1
Type: Research Article
ISSN: 1477-996X

Keywords

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