Search Results (68)

According to the literature, the advancement of information and communication technology (ICT) has increased individual exposure to scams, turning fraud victimization into a significant concern. While prior research has primarily focused on socio-demographic predictors of fraud victimization, this study adopts a behavioral perspective that is grounded in the Signal Detection Theory (SDT) to investigate the likelihood determinants of individuals becoming fraud victims. Using survey data of 671 Indonesian respondents analyzed with the Partial Least Squares Structural Equation Modeling (PLS-SEM), we explored the roles of vigilance and financial literacy in moderating the relationship between fraud exposure and victimization. Our findings substantiate the notion that higher exposure to fraudulent activity significantly increases the likelihood of victimization. The results also show that vigilance negatively moderates the relationship between fraud exposure and fraud victimization, suggesting that individuals with higher vigilance are better at identifying scams, thereby decreasing their likelihood of becoming fraud victims. Furthermore, financial literacy is positively related to vigilance, indicating that financially literate individuals are more aware of potential scams. However, the predictive power of financial literacy on vigilance is relatively low. Hence, while literacy helps a person sharpen their indicators for detecting fraud, psychological, behavioral, and contextual factors may also affect their vigilance and decision-making. Full article

This study aimed to examine the influence of red flag awareness and self-efficacy on the ability to detect fraud through professional skepticism. This study was conducted on commercial banks in Indonesia, due to the high level of fraud that occurs in the banking sector. This study used a quantitative method, and data were obtained from the results of a survey that distributed questionnaires to all internal auditors of commercial banks in Indonesia. The analysis tool used in this study was Smart PLS. The results show that red flag awareness and self-efficacy has an influence on the ability to detect fraud directly or through professional skepticism. This research contributes to bank managers and regulators improvement of the quality of internal auditor training, as well as strengthening the fraud detection system through the development of professional skepticism. Full article

The adoption of electronic payments has increased globally, driving economic growth by enabling smoother transactions. Digital payments enhance speed, security, trust, and efficiency, prompting governments to implement policies that promote financial inclusion through new payment technologies. However, trust in the financial system is crucial for adoption, given concerns about security, fraud, and data breaches. In Latin America and the Caribbean, where economies are vulnerable to external financial shocks, and trust in financial institutions is low, digital payment adoption presents both financial and social challenges. This study analyzes the impact of financial trust on the likelihood of using digital payments in 17 countries, based on the 2023 Latinobarómetro survey (19,205 individuals). Using logit models, it examines financial trust’s influence across income levels. Results show that trust in financial institutions increases the likelihood of digital payment adoption by 62%, with a stronger effect among high-income individuals. Younger age, higher education, and mobile phone ownership also correlate positively with adoption. This study highlights the need to foster financial trust to boost digital payments, enhance financial inclusion, and reduce cash usage—key for tackling inequality and informality. A major limitation is the lack of longitudinal data for further analysis. Full article

Despite the recognized importance of ethical idealism in enhancing fraud detection in the audit context, there remains limited understanding of the mediating role of conscientiousness in the relationship between auditors’ ethical idealism and fraud detection. The purpose of this paper is to analyze the influence of auditors’ ethical idealism on fraud detection via using the conscientiousness of auditors as a mediator. This study employs a cross-sectional approach, and quantifiable data were gathered via structured surveys from 401 external auditors employed in offices licensed to practice the accounting and auditing profession in Saudi Arabia. Accidental sampling was used to ensure a representative sample of auditors in Saudi audit firms. This study utilized the Structural Equation Modeling (SEM) technique to examine the relationships between ethical idealism (as independent variable), conscientiousness (as mediating variable), and fraud detection (as dependent variable). The result showed that ethical idealism has a positive effect on auditors’ detection of fraud. However, the proposed mediation effect of conscientiousness between ethical Idealism and fraud detection was not statistically significant. The research underscores that the ethical idealism of auditors can enhance fraud detection, especially when accounting firms give priority to ethical training programs, ensuring that they are guided by strong ethical idealism rather than personal conscientiousness. Full article

This paper examines the uptake of AI-driven fraud detection systems among financial institutions in the UAE and Qatar, with a special focus on trust, transparency, and perceptions of fairness. Despite the promise of AI operations in identifying financial anomalies, unclear decision-making processes and algorithmic bias constrain its extensive acceptance, especially in regulation-driven banking sectors. This study uses a quantitative strategy based on Partial Least Squares Structural Equation Modeling (PLS-SEM) and Multi-Group Analysis (MGA) of survey responses from 409 bank professionals, such as auditors and compliance officers. This study shows that transparency greatly enhances trust, which is the leading predictor of AI uptake. Fairness perception mediates the negative impacts of algorithmic bias, emphasizing its important role in establishing system credibility. The analysis of subgroups shows differential regional and professional variations in trust and fairness sensitivity, where internal auditors and highly AI-exposed subjects are found to exhibit higher adoption preparedness. Compliance with regulations also emerges as a positive enabler of adoption. This paper concludes with suggestions for practical implementation by banks, developers, and regulators to align AI deployment with ethical and regulatory aspirations. It recommends transparent, explainable, and fairness-sensitive AI tools as essential for promoting adoption in regulation-driven sectors. The findings provide a guide for promoting responsible, trust-driven AI implementation in fraud detection. Full article

Spot Bitcoin Exchange Traded Products (ETPs) are financial instruments enabling Bitcoin to be traded on traditional brokerage platforms, reducing the risks associated with direct Bitcoin exposure while addressing fraud and market manipulation concerns. This study examines the adoption of Spot Bitcoin ETPs, emphasizing the roles of financial and digital literacy, market dynamics, and regulatory frameworks in influencing individual investor behavior. Based on a survey of 428 U.S. respondents, financial literacy and early adopter traits were found to significantly enhance adoption likelihood (β = 0.458, p < 0.001). Government factors, such as compliance guidelines and tax policies, improved investor confidence and adoption rates (β = 0.409, p < 0.001). Market factors, including volatility and sentiment, played a notable yet secondary role (β = 0.34, p < 0.001). Institutional investment mediated the effects of regulatory and market dynamics on individual adoption, legitimizing Spot Bitcoin ETPs and fostering trust (β = 0.298, p < 0.001). The findings emphasize the need for clear regulations, robust disclosure requirements, and investor education to enhance adoption. Policymakers should focus on regulatory transparency to build investor confidence, while financial institutions can advance adoption by promoting financial and digital literacy. This study contributes to understanding how individual, market, and regulatory factors collectively drive the integration of regulated cryptocurrency products into mainstream finance. Full article

Blockchain is a secure, digital ledger that enables faster transactions, reduces fraud, lowers costs, and enhances transparency. The blockchain is capable of changing the face of digital payments by providing greater opportunities for transformation. Consumer acceptance in emerging markets such as Bhutan depends on a number of key factors. This paper explores the impact of performance expectancy, effort expectancy, social influence, and facilitating conditions on consumer acceptance of blockchain-based digital payment systems in Bhutan. Sustained by the Unified Theory of Acceptance and Use of Technology (UTAUT), the study uses PLS-SEM to analyze survey data from 302 respondents. The results show that performance expectancy, the expectation of blockchain’s usefulness, is the most influential factor determining customer acceptance. Effort expectancy and facilitating conditions are equally important. Social influences, although rather marginal, play an important role in Bhutan’s collectivist culture. The paper sheds light on factors for consumer acceptance of blockchain adoption. The findings add to the literature on blockchain adoption in burgeoning economies and provide the foundation for further research on blockchain adoption in multi-cultural contexts. Full article

This study examines the key drivers behind the adoption of artificial intelligence (AI) in the accounting profession, emphasizing the influence of AI-related knowledge, personality traits, and professional roles. By applying Decision Tree Regression analysis to survey data from accounting professionals, our research identifies AI knowledge as the strongest determinant of AI adoption, underscoring the importance of expertise in technology acceptance. While personality traits play a secondary role, extraversion and openness emerge as significant factors influencing adoption intentions. The study further explores AI applications in financial auditing, tax compliance, and fraud detection, clarifying the specific accounting domains impacted by AI integration. These findings offer valuable guidance for policymakers, educators, and business leaders aiming to equip the accounting workforce with the necessary skills and mindset to navigate the AI-driven transformation of the profession. Full article

The present study investigates consumers’ perceptions and knowledge of food sustainability, food authenticity and food fraud/risk in Italy and whether their perception and knowledge differ according to demographic factors, consumption choices and preferences. To address these issues, a network analysis technique was applied to analyse the theoretical framework. Subsequently, the primary online survey data of 328 respondents in Italy were explored using principal component analysis, canonical correlation analysis and hierarchical cluster analysis. The results indicate that socio-economic determinants—above all, marital status, the presence of children, and annual net income—not only influence the propensity to seek information on the certification, sustainability labels and quality of products but also impact consumer perceptions of food fraud/risk. The findings provide a useful, informative tool for the protection of consumer health, which can be negatively impacted by the purchase of fraudulent food products. Despite the abundant literature on consumer perspectives and perceptions of food authenticity and the integrity of the food supply, to the best of this author’s knowledge, this study represents one of the first attempts to analyse consumer perceptions of certified food products and knowledge of food fraud/risk. Full article

Decentralized Finance (DeFi) is a recent advancement of the cryptocurrency ecosystem, giving plenty of opportunities for financial inclusion, innovation, and growth domains by providing services such as lending, borrowing, and trading without traditional intermediaries. However, inadequate regulatory oversight and technological vulnerabilities raise pressing concerns around market manipulation, fraud, and regulatory compliance, exposing a clear research gap in effective DeFi risk management. This paper addresses this gap by proposing a utility-based framework to evaluate six leading DeFi tracking platforms—Chainalysis, Elliptic, Nansen, Dune Analytics, DeBank, and Etherscan—focusing on two critical metrics: transaction accuracy and real-time responsiveness. Applying a mixed methods approach that combines a quantitative survey (n = 138) with qualitative interviews (n = 12), we identified critical platform features and found significant differences across these platforms with respect to compliance features, advanced analytics, and user experience. We used a utility-based model that links accuracy and responsiveness metrics, allowing us to adjust differing priorities and risk management needs for users. The results show the need for balanced, user-centric solutions that accommodate regulatory, technological efficiency and affordability requirements. Our study contributes to the growing knowledge base by providing a structured evaluation model and empirical insights, offering clear directions for practitioners, platform developers, and policymakers aiming to strengthen the DeFi ecosystem. Full article

In the domain of animal management, the technology for individual livestock identification is in a state of continuous evolution, encompassing objectives such as precise tracking of animal activities, optimization of vaccination procedures, effective disease control, accurate recording of individual growth, and prevention of theft and fraud. These advancements are pivotal to the efficient and sustainable development of the livestock industry. Recently, visual livestock biometrics have emerged as a highly promising research focus due to their non-invasive nature. This paper aims to comprehensively survey the techniques for individual livestock identification based on computer vision methods. It begins by elucidating the uniqueness of the primary biometric features of livestock, such as facial features, and their critical role in the recognition process. This review systematically overviews the data collection environments and devices used in related research, providing an analysis of the impact of different scenarios on recognition accuracy. Then, the review delves into the analysis and explication of livestock identification methods, based on extant research outcomes, with a focus on the application and trends of advanced technologies such as deep learning. We also highlight the challenges faced in this field, such as data quality and algorithmic efficiency, and introduce the baseline models and innovative solutions developed to address these issues. Finally, potential future research directions are explored, including the investigation of multimodal data fusion techniques, the construction and evaluation of large-scale benchmark datasets, and the application of multi-target tracking and identification technologies in livestock scenarios. Full article

Purpose—This paper investigates the role of forensic accounting skills in enhancing auditor self-efficacy towards fraud detection in Indonesia. It also examines the moderating effect of the implementation of Generalized Audit Software (GAS) and the whistleblowing system on the relationship between accounting and auditing skills and auditor self-efficacy, as well as their combined role in enhancing fraud detection. Methodology—A cross-sectional survey was conducted with 537 external auditors in Indonesia. Data were analyzed using multiple linear regression with moderation models, employing WarpPLS 8.0 software. Findings—The results indicate that practical communication skills, psychosocial skills, and accounting and auditing skills significantly enhance auditor self-efficacy. However, technical and analytical skills do not show a significant effect on auditor self-efficacy. Furthermore, auditor self-efficacy is found to have a direct and significant impact on fraud detection. This study also reveals that implementing GAS moderates the relationship between auditor self-efficacy and fraud detection, whereas the whistleblowing system does not demonstrate a significant moderating effect. Novelty—This study contributes to the literature by highlighting the role of forensic accounting skills and the implementation of GAS in enhancing auditor self-efficacy and fraud detection in the Indonesian auditing context. Full article

Using the internet to recruit participants into research trials is effective but can attract high numbers of fraudulent attempts, particularly via social media. We drew upon the previous literature to rigorously identify and remove fraudulent attempts when recruiting rural residents into a community-based health improvement intervention trial. Our objectives herein were to describe our dynamic process for identifying fraudulent attempts, quantify the fraudulent attempts identified by each action, and make recommendations for minimizing fraudulent responses. The analysis was descriptive. Validation methods occurred in four phases: (1) recruitment and screening for eligibility and validation; (2) investigative periods requiring greater scrutiny; (3) baseline data cleaning; and (4) validation during the first annual follow-up survey. A total of 19,665 attempts to enroll were recorded, 74.4% of which were considered fraudulent. Automated checks for IP addresses outside study areas (22.1%) and reCAPTCHA screening (10.1%) efficiently identified many fraudulent attempts. Active investigative procedures identified the most fraudulent cases (33.7%) but required time-consuming interaction between researchers and individuals attempting to enroll. Some automated validation was overly zealous: 32.1% of all consented individuals who provided an invalid birthdate at follow-up were actively contacted by researchers and could verify or correct their birthdate. We anticipate fraudulent responses will grow increasingly nuanced and adaptive given recent advances in generative artificial intelligence. Researchers will need to balance automated and active validation techniques adapted to the topic of interest, population being recruited, and acceptable participant burden. Full article

Rates of victimization from identity theft continue to rise exponentially. Personally identifiable information (PII) has become vitally valuable data bad actors use to commit fraud against individuals. Focusing primarily on the United States and Canada, the objective of this paper is to raise awareness for those involved in criminal justice (CJ) to more fully understand potential life-changing consequences for those whose PII is used fraudulently. We examine the impact of crimes involving PII and the urgent need to increase investigations and legal proceedings for identity theft-related crimes. Referring to a National Crime Victimization Survey, we analyze why many victims of identity theft crimes resist notifying appropriate authorities. We also address why those within the CJ system are often reluctant to initiate actions against occurrences of identity theft. We provide insight into consequences experienced by identity theft victims, particularly if their PII is posted on the Dark Web, a threat that can exist into perpetuity. If rates of victimization from identity theft-based crimes are to decline, reporting of victimization must increase, and current legislation related to investigating and processing identity theft crimes must progress. Full article

Food fraud presents a growing threat globally, impacting consumer health; food safety; and brand credibility. The key motivation for food fraud is usually an economic or financial advantage. Economically motivated food fraud (EMA) is the illegal deception, deliberate and intentional substitution or addition of a substance in a food product, which may pose a possible health risk to unsuspecting consumers. This study aims to assess the awareness and attitudes of Nigerian consumers towards food authenticity and the regulatory measures in place to combat food adulteration. The study comprised 2160 respondents who were asked about their knowledge of high-profile food fraud incidents, frequently adulterated products, and their opinions of the effects of food fraud and preventative measures. The findings of this study revealed that more than a third of respondents were unfamiliar with the term “food fraud”. However, they were aware of local high-profile cases, such as “plastic rice” and counterfeit dairy products. Most participants relied on point-of-sale information for assessing food authenticity, with street vendors being viewed as potential sources of food adulteration. The study also found that more than half of the respondents were concerned about food fraud regardless of whether it involved local or imported products. A wide variety of food items were identified as prone to adulteration or fraudulent activity. These included alcoholic drinks, dairy products, honey, rice, and tomato paste, amongst others. These findings highlight the need for improved consumer awareness, regulatory effectiveness, and remediation efforts to combat food fraud in Nigeria. Full article