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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.

This paper aims to focus on the different types of insider-led cyber frauds that gained mainstream attention in recent large-scale fraud events involving prominent Indian banking institutions. In addition to identifying and classifying cyber fraud, the study maps them on a severity scale for optimal mitigation planning.

The methodology used for identification and classification is an analysis of a detailed literature review, a focus group discussion with risk and vigilance officers and cyber cell experts, as well as secondary data of cyber fraud losses. Through machine learning-based random forest, the authors predicted the future of insider-led cyber frauds in the Indian banking business and prioritized and predicted the same. The projected future reveals the dominance of a few specific cyber frauds, which will make it easier to develop a fraud mitigation model based on a victim-centric approach.

The paper concludes with a conceptual framework that can be used to ensure a sustainable cyber fraud mitigation ecosystem within the scope of the study. By using the findings of this research, policymakers and fraud investigators will be able to create a more robust environment for banks through timely detection of cyber fraud and prevent it appropriately before it happens.

The study focuses on fraud, risk and mitigation from a victim-centric perspective and does not address it from the fraudster’s perspective. Data availability was a challenge. Banks are recommended to compile data that can be used for analysis both by themselves and other policymakers.

The structured, sustainable cyber fraud mitigation suggested in the study will provide an agile, quick, proactive, stakeholder-specific plan that helps to safeguard banks, employees, regulatory authorities, customers and the economy. It saves resources, cost and time for bank authorities and policymakers. The mitigation measures will also help improve the reputational status of the Indian banking business and prolong the banks’ sustenance.

The innovative cyber fraud mitigation approach contributes to the sustainability of a bank’s ecosystem quickly, proactively and effectively.

Aviation has multi-cultural business environment in all aspects as operational and management. Managing aviation requires high awareness on human factor risk which includes organizational behavior-related topics. The greatest risk to an enterprise’s ability to achieve its strategic goals and objectives is the human factor. Both organizational behavior and corporate culture behavior with social psychology are the most vital aspects of management and strategy in terms of human resources. Related risks, including organizational behavior and culture, have the potential to directly impact on both business performance and corporate sustainability. Therefore, in this paper, the most prominent risks were determined in accordance with social psychology, and after identification of human factor-based risks, these have prioritized and prepared risk mapping with fresh approach. For this reason, this study aims to develop risk mapping model for human factors that takes into account interrelations among risk factors three dimensional based new approach. This approach includes both identification of human factor based risks, prioritization them and setting risk mapping according to corporate based qualifications via tailoring risk list. Developed risk map in this paper will help to manage corporate risks to achieve improved performance and sustainability.

This new organizational behavior- and culture-focused risk mapping model developed in this study has the potential to make significant contribution to the management of the human factor for modern management and strategy. In enterprise risk management system, risk mapping is both strong and effective strategic methodology to manage ergonomics issue with strategic approach. Human factor is both determinative and also strategic element to both continuity and performance of business operations with safely and sound. In view of management and strategy, vitally, the human factor determines the outcome in both every business and every decision-making.

It is assumed that, if managers manage human risk you may get advantages to achieving corporate strategies in timely manner. Aviation is sensitive sector for its ingredients: airports, airlines, air traffic management, aircraft maintenance, pilotage and ground handling. Aim of this paper is to present risk management approach to optimize human performance while minimizing both failures and errors by aircraft maintenance technician (AMT). This model may apply all human factors in other departments of aviation such as pilots and traffic controllers. AMT is key component of aircraft maintenance. Thus, errors made by AMTs will cause aircraft accidents or incidents or near miss incidents. In this study, new taxonomy model for human risk factors in aircraft maintenance organizations has been designed, and also new qualitative risk assessment as three dimensions is carried out by considering the factors affecting the AMT’s error obtained from extensive literature review and expert opinions in the field of aviation. Human error risks are first categorized into two main groups and sub three groups and then prioritized using the risk matrix via triple dimension as probability, severity and interrelations ratio between risks.

Risk mapping is established to decide which risk management option they will apply for managers when they will look at this map. Managers may use risk map to both identify their managerial priorities and share sources to managing risks, and make decisions on risk handling options. This new model may be a useful new tool to manage ergonomic human factor-based risks in developing strategy in aviation business management. In addition, this paper will contribute to department of management and strategy and related literature.

This study has originality via new modeling of risk matrix. In this study, dimension of risk analysis has been improved as three dimensions. This study has new approach and new assessment of risk with likelihood (probability), impact (severity) and interrelations ratio. This new model may be a useful new tool to both assess and prioritize mapping of ergonomic-based risks in business management. In addition, this research will contribute to aviation management and strategy literature and also enterprise risk management literature.

The fraud landscape for FinTech industry has increased over the past few years, certainly during the time of COVID-19, FinTech market reported rapid growth in the fraud cases (World Bank, 2020). Taking the consideration, the paper has qualitatively understood the loopholes of the FinTech industry and designed a conceptual model declaring “Identity Theft” as the major and the common fraud type in this industry. The paper is divided in two phases. The first phase discusses about the evolution of FinTech industry, the second phase discusses “Identity Theft” as the common fraud type in FinTech Industry and suggests solutions to prevent “Identity Theft” frauds. This study aims to serve as a guide for subsequent investigations into the FinTech sector and add to the body of knowledge regarding fraud detection and prevention. This study would also help organisations and regulators raise their professional standards in relation to the global fraud scene.

This paper revisits the literature to understand the evolution of FinTech Industry and the types of FinTech solutions. The authors argue that traditional models must be modernised to keep up with the current trends in the rapidly increasing number and severity of fraud incidents and however introduces the conceptual model of the common fraud type in FinTech Industry. The research also develops evidences based on theoretical underpinnings to enhance the comprehension of the key fraud-causing elements.

The authors have identified the most common fraud type in the FinTech Industry which is “Identity Theft” and supports the study with profusion of literature. “Identity theft” and various types of fraud continue to outbreak customers and industries similar in 2021, leaving several to wonder what could be the scenario in 2022 and coming years ahead (IBS Inteligence, 2022). “Identify theft” has been identified as one the common fraud schemes to defraud individuals as per the Association of Certified Fraud Examiners. There is a need for many of the FinTech organisations to create preventive measures to combat such fraud scheme. The authors suggest some preventive techniques to prevent corporate frauds in the FinTech industry.

This study identifies the evolution of FinTech industry, major evidences of Identity Thefts and some preventive suggestions to combat identity theft frauds which requires practical approach in FinTech Industry. Further, this study is based out of qualitative data, the study can be modified with statistical data and can be measured with the quantitative results.

This study would also help organisations and regulators raise their professional standards in relation to the global fraud scene.

This study will serve as a guide for subsequent investigations into the FinTech sector and add to the body of knowledge regarding fraud detection and prevention.

This study presents evidence for the most prevalent fraud scheme in the FinTech sector and proposes that it serve as a theoretical standard for all ensuing comparison.

The purpose of this paper is to undertake an exploratory study on mapping the investment fraud methods and tactics used by scammers against the emerging literature on scam compliance.

Qualitative interviews were conducted with victims of investment fraud supported by the engagement of specialist counsellors and allied health professionals who specialise in scam victim support (including investment fraud).

Investment fraud offending in the cases sampled exhibited a number of dominant offending traits and methodological themes. These included a strong reliance or dependency on legitimate service provisioning on the part of the fraudster and the use of key trust measures to lure the victim. The empirical data revealed the presence of a number of scam compliance influences captured in the literature, including trust, social influence and urgency, as well as others not previously documented that pave the way for further research attention.

The research only examined a sample of investment fraud victim experiences that engaged a national victim support service immediately following detection over a 24 month period.

The research found that offending relied upon the participation of trust-building signals and measures. Legitimate economy participants appear to play a dominant role in enabling investment scam activities, further creating efficiencies for criminals. The offending tended to follow a number of distinct but connected phases. Impacts were influenced by specific offending attributes, such as whether remote access was given to offenders of a victim’s device, as well as the nature of the identity credentials access.

The research has practically applied an emerging view of scam compliance influences and vulnerabilities within an investment fraud context. The study is novel in its thematic analysis of the distinct phases and tactics used by scammers.

This paper aims to explore the potential of computer-assisted qualitative data analysis software (CAQDAS) to be used as a corruption investigation tool to help investigators in carrying out their investigative works.

By reviewing the literature on qualitative research and fraud investigation, this exploratory study identifies similarities between the two types of inquiries and thus proposing the use of CAQDAS as an innovation in the field of corruption investigation. To demonstrate how a QDA application can support corruption investigators, NVivo is used as a case study from which various key analytical tools are discussed to highlight their potential in supporting a corruption investigation.

As a fundamental part of anti-corruption practice in a country, corruption investigation must be planned and executed professionally and adequately. This paper highlights various stages in fraud investigation to identify areas that can be improved with the use of a CAQDAS. Based on the discussion in this paper, the author concludes that the capability of a CAQDAS to assist users in data reduction and data display has the potential to increase the effectiveness and efficiency in various stages of a corruption investigation.

Based on a self-funded study, this paper only uses a simulation case with a fictitious company to illustrate how a CAQDAS application can be used to support a corruption investigation process. Future studies may benefit from using actual corruption cases in illustrating how such an application can support the investigation process.

This paper contributes to the innovation in anti-corruption practice by proposing a new framework and tool to develop corruption investigation capacity.

This paper brings a new perspective into the field of anti-corruption to stimulate innovation in the area of corruption investigation.

Academic corruption and fraudulent practices have become problematic in recent years. Governments around the world have introduced dedicated higher education commissions to regulate higher education providers. The purpose of this paper is to design a system for the detection and prevention framework of fraudulent behaviour in higher education.

This paper performs a survey on academic misconduct practices and expands the survey by analysing the accreditation process. This study further identifies common corrupt practices in the accreditation process with reference to particular accreditation standards or laws. If the accreditation process is as thorough as, this paper is led to believe, a higher institute may stop being compliant immediately after the accreditation process. playing a catch-me-if-you-can at the next accreditation cycle. The survey of the accreditation process and identification of corrupt practices lead to an identification of preventative and detective measures.

The review of accreditation procedures and conditions identifies that fraudulent practices can occur at every part of any policy and procedure. The framework prevents repudiation and allows for spontaneous investigations internally and externally. The blockchain prevented changes to the system and allow for auditing of changes. A system such as this could suppress accreditation fraud and minimise its corrupt impact. Not to mention identify with relative ease the severity and life of corrupt practice.

Contributions are made in the framework for detecting and preventing corrupt practices in Higher Education using blockchain immutable transactions. This enables real-time accreditation compliance checks and monitoring of conditions. External complaints or reviews can be conducted with minimum interactions from higher education providers.

The purpose of this paper is to make readers aware of the extensiveness of healthcare fraud in the USA and how it involves and affects the government, healthcare providers, insurance companies, patients and the public. In addition, recommendations are made that may help control this pervasive type of fraud.

A range of different journal publications, information from government health institutions and law enforcement websites, healthcare fraud cases and healthcare laws are used as a basis to provide information about how fraudsters are committing healthcare fraud and how to prevent this fraud from occurring.

Despite increased funding and prosecution efforts by the government, healthcare fraud continues to be a major threat to the US economy and public. While healthcare fraud will never be eradicated, specific efforts can be deployed to help rein in these complex fraud schemes.

The paper provides a useful resource of information on healthcare fraud for healthcare providers, insurance companies, patients and the public that may help combat healthcare fraud and prevent financial losses.

Every dollar saved from combating fraud could be used to improve access to more or better health services and can, thereby, save lives.

This paper provides recommendations regarding healthcare fraud that could help prevent this large drain on the US economy.

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.

Previous research observed that large internal fraud events in the general financial services industry imply negative spillover effects, whereas internal fraud in investment banks can imply significantly positive effects for other banks. This paper aims to shed further light on this contradictory result.

For this purpose, the authors compare the spillover effects of the three largest cases of rogue trader events in investment banks (Company 1, 1995; Company 2, 2008; Company 3, 2011) on the largest competing non-announcing banks and insurance companies in Europe based on an event study.

The results show that while the respective announcing firm suffered significant market value losses that even led to bankruptcy in case of Company 1, spillover effects on other banks and insurers were twofold. In particular, in case of Company 2 and Company 3, spillover effects on other financial firms were significantly positive depending on the event window, indicating a dominating competitive effect, whereas the Company 1 event with its resulting bankruptcy led to significantly negative spillover effects and thus contagion.

The results offer a first indication that the severity of the event in terms of its consequences for the announcing firm is crucial, as internal fraud events have the potential to significantly worsen the market values of other financial services firms, which is in contrast to the typically observed positive effects.