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This study aims to examine how auditors perceive the influence of crucial fraud prevention factors in deterring financial statement fraud within the corporate sector. Additionally, this research explores the mediating effect of fraud awareness in elucidating the impact of ethical leadership and internal control systems on preventing financial statement fraud.

The study used an online survey, targeting a sample of 141 professionally qualified auditors with at least one year of practical experience in the field. The researchers used “Structural Equation Modeling (SEM)” to examine relationships between latent variables using partial least squares structural equation modeling. The study investigated the impact of whistleblowing systems, fraud awareness, ethical leadership, internal control systems and corporate governance on fraud prevention.

This research finding provides evidence to the corporate sector by establishing the significance of fraud awareness as the most influencing factor in preventing financial statement fraud. Furthermore, the combined explanatory variables account for 77.4% of the overall variance in financial statement fraud prevention. The study reveals a partial mediation effect of fraud awareness on the relationship between the internal control system and financial statement fraud prevention.

This research finding may assist in developing an effective fraud prevention programme to mitigate fraud instances and improve financial reporting quality. In the corporate sector, each organisation should clearly specify the policies on whistleblowing systems, fraud awareness training, internal control systems and corporate governance. To foster a comprehensive fraud prevention programme, the leaders should enforce these policies with employee support.

This research integrated crucial elements to develop a new theoretical framework for investigating financial statement fraud prevention within the corporate context. Accordingly, this research framework provides a more in-depth explanation of preventing financial statement fraud from an auditor’s perspective. Additionally, this research is the first to explore the mediating role of fraud awareness in influencing the effectiveness of the internal control system in preventing financial statement fraud.

The purpose of this paper, which is based on author's PhD study, is to analyze the trends in credit card fraud prevention in the USA, the UK, Australia and Indonesia, particularly over the period 2003‐2007, with special focus on the fraud prevention practices in the payments systems.

This study uses primary and secondary data particularly from the payments systems of the USA, the UK, Australia and Indonesia to conduct historical and benchmarking analyses to highlight the trends in credit card fraud prevention in the four countries.

The study establishes that a common approach in preventing credit card fraud is reducing offenders' opportunities to commit their offences, which often require significant amount of resources and thus sound strategy needs to be properly formulated and executed. Referring primarily to the practices in the USA, the UK, Australia and Indonesia, resources are mainly allocated to six key areas of fraud prevention: understanding of the real problems, fraud prevention policy, fraud awareness, technology‐based protection, identity management and legal deterrence. These are supported in principle by four main groups in a payments system: user, institution, network and government and industry.

The paper provides insights into the nature of credit card fraud, as well as a framework for designing a sound credit card fraud prevention strategy in a country's payments system.

Food fraud as intentional deception for economic gain relies on a low-tech food value chain, that applies a ‘paper-and-pencil approach’, unable to provide reliable and trusted data about food products, accompanied processes/activities and actors involved. Such approach has created the information asymmetry that leads to erosion of stakeholders and consumers trust, which in turn discourages cooperation within the food chain by damaging its ability to decrease uncertainty and capability to provide authentic, nutritional, accessible and affordable food for all. Lack of holistic approach, focus on stand-alone measures, lack of proactive measures and undermined role of customers have been major factors behind weaknesses of current anti-fraud measures system. Thus, the process of strong and fast digitalisation enabled by the new emerging technology called Industry 4.0 is a way to provide a shift from food fraud detection to efficient prevention. Therefore, the objective of this chapter is to shed light on current challenges and opportunities associated with Industry 4.0 technology enablers' guardian role in food fraud prevention with the hope to inform future researchers, experts and decision-makers about opportunities opened up by transforming to new cyber-physical-social ecosystem, or better to say ‘self-thinking’ food value chain whose foundations are already under development. The systematic literature network analysis is applied to fulfil the stated objective. Digitalisation and Industry 4.0 can be used to develop a system that is cost effective and ensures data integrity and prevents tampering and single point failure through offering fault tolerance, immutability, trust, transparency and full traceability of the stored transaction records to all agri-food value chain partners. In addition, such approach lays a foundation for adopting new business models, strengthening food chain resilience, sustainability and innovation capacity.

The study aims to overview the different types of internal-led cyber fraud that have gained mainstream attention in recent major-value fraud events involving prominent Indian banks. The authors attempted to identify and classify cyber frauds and its drivers and correlate them for optimal mitigation planning.

The methodology opted for the identification and classification is through a detailed literature review and focus group discussion with risk and vigilance officers and cyber cell experts. The authors assessed the future of cyber fraud in the Indian banking business through the machine learning–based k-nearest neighbor (K-NN) approach and prioritized and predicted the future of cyber fraud. The predicted future revealing dominance of a few specific cyber frauds will help to get an appropriate fraud prevention model, using an associated parties centric (victim and offender) root-cause approach. The study uses correlation analysis and maps frauds with their respective drivers to determine the resource specific effective mitigation plan.

Finally, the paper concludes with a conceptual framework for preventing internal-led cyber fraud within the scope of the study. A cyber fraud mitigation ecosystem will be helpful for policymakers and fraud investigation officers to create a more robust environment for banks through timely and quick detection of cyber frauds and prevention of them.

Additionally, the study supports the Reserve Bank of India and the Government of India's launched cyber security initiates and schemes which ensure protection for the banking ecosystem i.e. RBI direct scheme, integrated ombudsman scheme, cyber swachhta kendra (botnet cleaning and malware analysis centre), National Cyber Coordination Centre (NCCC) and Security Monitoring Centre (SMC).

Structured and effective internal-led plans for cyber fraud mitigation proposed in this study will conserve banks, employees, regulatory authorities, customers and economic resources, save bank authorities’ and policymakers’ time and money, and conserve resources. Additionally, this will enhance the reputation of the Indian banking industry and extend its lifespan.

The innovative insider-led cyber fraud mitigation approach quickly identifies cyber fraud, prioritizes it, identifies its prominent root causes, map frauds with respective root causes and then suggests strategies to ensure a cost-effective and time-saving bank ecosystem.

The purpose of this paper is to report on a search of criminology and related databases to identify fraud prevention intervention projects that showed promising achievements in reducing offences.

A keyword search of Criminal Justice Abstracts was supplemented by searches of related databases and case study repositories – conducted up to 31 May 2019. The paper includes some attention to indicators of “what doesn’t work” as well as “what might work” or “what should work”. Selection criteria were open about evidence, rather than exclusively applying strict scientific standards.

Overall, the literature is marked by inferences regarding what should work, based on diagnostics about opportunity factors in fraud and victim characteristics. In terms of evaluated intervention projects, only two were identified that met best practice scientific standards. However, a further 17 projects were included where there was some evidence of a likely benefit.

Available evaluations of intervention projects are predominantly within-in group studies. Pre- and post-intervention time frames are often short, limited to one year or less; with only one follow-up study.

The findings demonstrate the need for applied experiments to build knowledge about effective fraud reduction strategies. The main lesson from the content of the 19 projects concerns the value of a situational crime prevention framework for designing and testing interventions, especially through enhancing rule setting, reducing anonymity, extending guardianship and formal surveillance, and facilitating compliance.

This appears to be the first systematic literature review of applied counter-fraud intervention projects.

This paper aims to determine how forensic accounting contributes to fraud detection and prevention and answer the following research questions: What are the standard techniques for fraud detection and prevention; and What are the significant challenges that hinder the application of forensic accounting in fraud prevention and detection?

The authors use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to carry out a systematic literature review (SLR) to identify and assess the existing literature on forensic accounting.

There exists a positive correlation between forensic accounting and fraud detection and prevention. Moreover, in both the empirical and non-empirical findings, the authors note that fraud is complex, and in carrying out fraud investigations, one must be aware of its complexity.

Although drug counterfeiting is a sector where forensic accountants have paid less attention, it is a rapidly expanding fraud area. This paper finds that to detect fraud at an early stage, one must increase consumer understanding of basic forensic accounting techniques by implementing accurate supply chain monitoring systems and inventory management controls and conducting adequate and effective regulatory, honest and legitimate customs inspections.

The major factors that restrict forensic accounting are a lack of awareness and education. Hence, it is essential to incorporate forensic accounting in undergraduate and post-graduate courses.

From the existing literature, it has been observed that very few studies have been conducted in this field using the PRISMA and SLR techniques. Also, the authors carried out a holistic study that focuses on three different areas – fraud detection, fraud prevention and the challenges in forensic accounting.

Purpose: The study aims to explore the wider acceptance of blockchain technology and growing faith in this technology among all business domains to mitigate the chances of fraud in various sectors.

Design/Methodology/Approach: The authors focus on studies conducted during 2015–2022 using keywords such as blockchain, fraud detection and financial domain for Systematic Literature Review (SLR). The SLR approach entails two databases, namely, Scopus and IEEE Xplore, to seek relevant articles covering the effectiveness of blockchain technology in controlling financial fraud.

Findings: The findings of the research explored different types of business domains using blockchains in detecting fraud. They examined their effectiveness in other sectors such as insurance, banks, online transactions, real estate, credit card usage, etc.

Practical Implications: The results of this research highlight (1) the real-life applications of blockchain technology to secure the gateway for online transactions; (2) people from diverse backgrounds with different business objectives can strongly rely on blockchains to prevent fraud.

Originality/Value: The SLR conducted in this study assists in the identification of future avenues with practical implications, making researchers aware of the work so far carried out for checking the effectiveness of blockchain; however, it does not ignore the possibility of zero to less effectiveness in some businesses which is yet to be explored.

Identity fraud is a growing issue for online retail organisations. The literature on this issue is scattered, and none of the studies presents a holistic view of identity fraud management practices in the online retail context. Therefore, the purpose of this paper is to investigate the identity fraud management practices and present a comprehensive set of practices for e-tail sector.

A systematic literature review approach was adopted, and the articles were selected through pre-set inclusion criteria. The authors synthesised existing literature to investigate identity fraud management in e-tail sector.

The research finds that literature on practices for identity fraud management is scattered. The findings also reveal that firms assume identity fraud issues as a technological challenge, which is one of the major reasons for a gap in effective management of identity frauds. This research suggests e-tailers to deal this issue as a management challenge and counter strategies should be developed in technological, human and organisational aspects.

This study is limited to the published sources of data. Studies, based on empirical data, will be helpful to support the argument of this study; additionally, future studies are recommended to include a wide number of databases.

This research will help e-tail organisations to understand the whole of identity fraud management and help them develop and implement a comprehensive set of practices at each stage, for effective management identity frauds.

This research makes unique contributions by synthesising existing literature at each stage of fraud management and encompasses social, organisational and technological aspects. It will also help academicians understanding a holistic view of available research and opens new lines for future research.

Despite the increasing awareness of fraud in organisations and the potential benefits of strong fraud management through deterrence and prevention in the UK, there remains limited research on fraud in small charities. This paper aims to examine astonishing cases of fraud in small charities whilst raising awareness of the impact of fraud and its wider implication in the charity sector.

This research used a qualitative approach amongst randomly selected 24 charity trustees with income of £0-250,000 and over £250,000. Recent statistics from fraud survey published in Annual Fraud Indicator by the National Fraud Authority and the United Kingdom Fraud Costs Measurement Committee were presented and the theory of why people commit fraud is described.

This paper summarises evidence that shows the frequency and severity of fraud in charities, which remains increasingly high. Furthermore, smaller charities are not immune from fraud and suffer losses due to lack of segregation of duties and weak control systems when compared to larger charities with stronger control systems and better governance structure. This paper addresses a very important topic in the charity sector. Whilst fraud and fund misappropriation receive significant media coverage in large charities, smaller charities also suffer losses occasioned by fraud even in large proportion albeit with less reporting in the media.

Charity managers and trustees will benefit from having sufficient knowledge in deterrence and prevention of charity fraud.

This is a novel research as it looks into the nature of fraud in small charities of which there is limited research both in the voluntary and fraud literature.

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.