Fraudulent Behavior Research Articles

Assessing the Impact of Effective Internal Controls in Fraud Prevention in Zambian Beverage Companies, a Case of Falls Beverages Zambia Limited

Internal controls encompass policies, procedures, and organizational structures designed to provide reasonable assurance that a company achieves its business objectives and prevents or detects undesired risk events, whether initiated by management concerns or compliance requirements. The study aimed to evaluate how effective internal controls impact fraud prevention, using a survey to collect data from 109 employees, including an internal auditor. Findings revealed that existing internal controls significantly aided in preventing major fraudulent activities and ensuring measures were in place to detect and deter fraud. Over 50% of respondents confirmed effective monitoring and implementation of internal controls capable of uncovering fraudulent behaviors within the company. The study emphasized that fraudulent activities adversely affected company operations and recommended measures such as fostering better management-staff relations, strengthening the audit department, offering incentives for fraud reporting, and implementing stringent controls. In conclusion, improving internal controls was identified as crucial for preventing fraud and safeguarding Falls Beverages from financial losses and resource mismanagement. Keywords: Internal Controls, Fraud Prevention

Fraud Management Model and Forensic Accounting – A Systematic Literature Review

This study interprets the importance of critical thinking and concern for the triggers of fraudulent behavior and financial fraud. The purpose of the study is expanded by explaining the application of fraud management as corporate governance to prevent fraud, and the involvement of forensic accounting practices is necessary. This study, a systematic literature review (SLR) by adopting part of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) method, to identify, and construct a fraud management and forensic accounting model. The findings, fraudulent behavior occurs because there is a triggering factor, and someone has difficulty ignoring it. Psychologically it has taken root and rationalized the truth of fraud on the basis of pressure, opportunity supported by capability, such as triggers for fraudulent behavior in the fraud triangle model and the diamond fraud model. Synthesis of findings, it is important for internal control in fraud management to be applied for early detection and investigation and it is necessary to involve forensic accounting practices to detect, investigate accounting and litigation to resolve financial fraud in the financial data-based justice system. The novelty of this research offers a fraud management and forensic accounting model to prevent fraud and the financial condition of the company.

Peranan Audit Forensik Dalam Mencegah Kejahatan Keuangan Perbankan Dengan Menggunakan Teknologi Informatika

Financial crime is any activity that involves fraudulent or criminal behavior to gain personal financial gain. This is a criminal activity carried out by individuals or groups involved in financial crime activities, such as: money laundering, terrorism financing, fraud, tax evasion and identity theft. Financial crime has become a big problem and is detrimental to many parties, using increasingly sophisticated techniques, which requires a solution. In this research the author will focus on discussing banking financial crimes using information technology, because they seriously damage the reputation of financial institutions, destroy public trust, and cause significant financial losses. Banking must have a strategy to protect various technologies, information and data simultaneously, which requires coordination with all stakeholders in Indonesia. The aim of writing this journal is to determine trends, patterns, factors that influence, anticipate and punish banking financial crimes using information technology. The research uses qualitative methods with data collection methods using literature studies. The object of this research is secondary data in the form of banking financial crimes using information technology committed by perpetrators of banking financial crimes. The role of forensic audit is the best way to prevent and detect banking financial crimes using information technology in Indonesia. Forensic audit has the ability to provide statements based on its expertise.

Melawan Academic Fraud: Menguak Peran IPK dan Kejujuran Mahasiswa Akuntansi dalam Fraud Pentagon dengan Dark Triad sebagai Moderasi

Fraud is a problem that often occurs and is a worrying issue among society, including in the world of education. The GPA is considered very valuable so that most students indicate fraud in the process of achieving a perfect score. This study investigates the influence of fraud pentagon variables on academic dishonesty behavior among undergraduate accounting students at faculty Economics and Businnes, Tanjungpura University, with dark triad factors as a moderating, while also exploring student prespecyives on GPA and the causes of academic dishonesty. This research focuses on understanding the influence of pressure, opportunity, rationalization, competence, and arrogance, which are combined in the fraud pentagon, contributing to academic fraud behavior with the dark triad: Machiavellianism, narcissism, and psychopathy used as moderation. This research uses quantitative methods with data collected throught survey with the help of Google forms. The data population from the research is undergraduate students in Accounting. Faculty of Economics and Business, Tanjungpura University. This research involved 100 students as respondents and data was processed using SPSS version 26 software. The research result showed that rationalization, competence, and arrogance had a positive effect in influencing academic fraud behaviour, while pressure and opportunity as moderation had a negative effect. The dark triad as moderation is unable to strengthen the variables of opportunity, competence, rationalization and arrogance towards academic fraud behavior.

Using Machine Learning Models to Detect the Increasing Threats of Financial Fraud in the Cyberspace

In the dynamic landscape of the financial sector, the escalating menace of financial fraud presents pervasive implications for businesses and consumers alike. Particularly, detecting credit card fraud in real- time transactions has become a pivotal concern within the financial industry. This abstract delves into the critical role of data mining in addressing the complexities of credit card fraud detection, shedding light on the multifaceted challenges that confront this domain. The realm of financial business is increasingly besieged by the spectre of financial fraud, necessitating robust measures to combat its detrimental effects. As the sophistication and prevalence of fraudulent activities continue to evolve, the imperative of deploying effective strategies for fraud detection becomes more pronounced. Applying data mining techniques in this context is paramount in identifying and mitigating credit card fraud. Leveraging advanced data mining methodologies is essential for scrutinising live transactions and discerning anomalous patterns indicative of fraudulent behaviour. Credit card fraud detection poses formidable challenges, primarily attributable to two compelling factors. Firstly, the inherent dynamism of normal and fraudulent behavioural profiles engenders a perpetual need for adaptive and responsive detection mechanisms. Secondly, the highly imbalanced nature of credit card fraud data sets further complicates accurately identifying fraudulent activities, necessitating nuanced approaches to discern anomalies amidst voluminous transactional data effectively. In light of the foregoing, this abstract underscore the criticality of data mining in addressing the intricate landscape of credit card fraud detection, emphasising the need for agile and sophisticated methodologies to navigate the evolving nature of fraudulent behaviours and the skewed distribution of fraud-related data sets. By comprehensively elucidating these challenges, this abstract provides a foundational understanding of the nuanced complexities inherent in combatting financial fraud through the lens of data mining.

Integrating machine learning and blockchain: Conceptual frameworks for real-time fraud detection and prevention

Integrating machine learning (ML) and blockchain technologies presents a groundbreaking approach to real-time fraud detection and prevention, addressing the growing complexity and sophistication of financial fraud schemes. This integration leverages the strengths of both technologies: the predictive power of ML algorithms and the transparency, security, and immutability of blockchain. Machine learning algorithms are proficient at analyzing large datasets, detecting patterns, and identifying anomalies that signify potential fraud. By employing supervised learning models such as logistic regression, decision trees, and neural networks, financial institutions can classify transactions and predict fraudulent activities with high accuracy. Unsupervised learning techniques, such as clustering and anomaly detection, are instrumental in discovering new fraud patterns without the need for labeled data, thus enhancing the detection of novel fraudulent behaviors. Blockchain technology, on the other hand, provides a decentralized and tamper-proof ledger that ensures data integrity and traceability. Transactions recorded on a blockchain are immutable and transparent, allowing for real-time monitoring and auditing. Smart contracts, self-executing contracts with the terms directly written into code, can be programmed to trigger alerts or actions when suspicious transactions are detected, further automating the fraud prevention process. The conceptual framework for integrating ML and blockchain involves several key components. First, data from financial transactions are continuously collected and stored on a blockchain, ensuring transparency and security. ML algorithms analyze this data in real time, identifying suspicious patterns and flagging potential fraud. When a potential fraud is detected, a smart contract is executed, which can instantly block the transaction, alert the relevant authorities, or initiate further verification processes. This integrated approach addresses several challenges in traditional fraud detection systems. The decentralized nature of blockchain eliminates single points of failure and reduces the risk of data tampering. The transparency of blockchain enhances the trustworthiness of the detection process, while the predictive capabilities of ML provide high accuracy and adaptability to new fraud tactics. Additionally, the real-time processing capabilities of both technologies ensure prompt detection and prevention of fraudulent activities. In conclusion, the integration of machine learning and blockchain offers a robust framework for real-time fraud detection and prevention. This synergy not only enhances the security and reliability of financial transactions but also paves the way for more advanced and automated compliance systems, ultimately strengthening the financial ecosystem against fraudulent threats.

An Intelligent Financial Fraud Detection Model Using Knowledge Graph-Integrated Deep Neural Network

Financial fraud detection has been an urgent technical demand in cyberspace. It highly relies on clear extraction and deep representation toward complex relationships inside financial social networks. As consequence, this study combines both knowledge graph and deep learning to deal with such issue. Thus, an intelligent financial fraud detection model based on knowledge graph guidance and deep neural network is proposed in this paper. First, a new knowledge graph based on financially related systems is constructed, which includes multiple entities and relationships. Then, an adversarial learning-based neural network structure is formulated to extract financial attributes. Finally, the detection results can be output according to the extracted factors. Empirically, the proposal is implemented on a real-world dataset for performance evaluation. The experimental results show that it has higher accuracy and effectiveness compared to traditional fraud detection methods. The proposed detection model can not only identify known fraudulent behaviors, but also predict potential fraud patterns based on consumer habits, thereby improving the security and reliability of financial transactions. It can also update the knowledge graph in real-time, enabling it to cope with emerging fraud methods and variants.

SIKAP BELA NEGARA SEBAGAI KONTROL DIRI DALAM MEMINIMALISIR PERILAKU KECURANGAN DIPANDANG DARI PERSPEKTIF FRAUD DIAMOND

This research aim to test and empirically demonstrate how pressure, opportunity, rationalization, and capacity can influence academic fraud behaviour and how national defense attitudes play a role in moderating such influence. This research is a quantitative study using up to 94 students from S1 Accounting student UPN “Veteran” East Java as samples. The research used SEM PLS with WarpPLS 7.0 software for data analysis. The finding of this research may be used as a resource for universities related to fraud in the university environment, specially in S1 Accounting students and can provide an overview of fraud related to occurring, so that the universities can take determined further action to deal with such matters. Research findings demonstrate that pressure and rationalization have a significant influence on fraud behavior and national defense attitudes can moderate the influence of opportunity against fraud behavior. Opportunity and capability have no significant influence on fraud behavior and national defense attitudes do not moderate the influence of pressure, racinoalization, and capability against fraud behavior.

The Dilemma of Achieving "Same Case, Same Sentence" in Cases of "Knowing and Buying Counterfeits" in the Field of Food and Drugs and Its Legal Progress

The frequent disparity in judicial rulings for identical cases of "Knowingly Purchasing Counterfeit Goods" within the food and drug sector has significantly undermined the authority of the law and compromised judicial fairness. An empirical study of 100 randomly selected judicial decisions from Shandong Province reveals that the current level of uniformity in judgments for equivalent cases is less than ideal. To delve deeper into the factors influencing these inconsistencies, this paper conducts an analysis of the suspicion of counterfeit awareness, the burden of proof, and the nature of the appellate case, utilizing the chi-square test for independence. Challenges such as establishing consumer identity, defining fraudulent behavior, and evaluating the standards of food safety are pivotal issues that impede the equitable treatment of knowingly purchasing counterfeit goods within the food and drug sector. In this distinct domain, the act of knowingly purchasing counterfeit goods, despite potential associations with professional racketeering, often yields a more constructive outcome. If it is determined that the parties involved are not engaged in commercial operations, their status as consumers should be acknowledged. When assessing food safety standards, emphasis should be placed on substantive criteria rather than mere formalities. Moreover, the presence of substantial harm should not be a mandatory threshold for the application of punitive damages. Additionally, if an operator fails to fulfill their evidentiary responsibilities or demonstrates "knowledge" of the counterfeit goods, the consumer's claim for compensation should be upheld.

“It Is No Big Deal!”: Fraud Diamond Theory as an Explanatory Model for Understanding Students’ Academic Fraudulent Behavior

The Fraud Diamond theory (rationalization, opportunity, motivation and perceived capability) has been widely used as a framework to explain criminal behavior. However, little is known about its application in an academic context. Research on the relationship between the prevalence of academic fraud (e.g., cheating on exams, plagiarizing essays) and students’ perceptions of the severity of such behaviors is also lacking. We surveyed 1,032 university students and asked them whether they engaged in fraudulent behaviors and how severe they thought these behaviors were. The results showed that motivation, rationalization, and perceived capability dimensions of the Fraud Diamond theory are important factors in predicting the prevalence of students’ academic fraudulent behavior, but not opportunity. We also found that the more students reported that they engaged in fraudulent academic behaviors, the less severe they perceived those behaviors to be. However, only rationalization emerged as a predictor of perceived severity. The results suggest that the more students are able to find justifications for their fraudulent behavior, the less severe they perceive those behaviors to be. Rationalization seems to explain, therefore, the tendency to disassociate moral values from dishonest behavior. Taken together, the study shows a vicious cycle between engaging in fraudulent academic behavior and the ability to justify these acts. Implications for Higher Education Institutions (HEIs) are discussed.

Academic Fraud Behavior From The Diamond Fraud Perspective

This research aims to determine the influence of pressure, opportunity, rationalization, capability on academic fraud. Academic fraud that occurs in the university environment includes cheating, copying from the internet, taking exams together and even using assistant for final assignments and theses. This research is quantitative research using primary data that researchers obtained from distributing questionnaires. The samples taken were obtained randomly from each batch of private university accounting students in Palembang City. The researcher processed the questionnaire using SPSS software. The research results stated that all the variables used had a simultaneous effect. The variables pressure, opportunity, capability partially have a significant effect on fraudulent behavior. In the rationalization variable, it can be seen that the significance of the results is greater than the predetermined significance, so that the rationalization variable has no effect on fraudulent behavior at private universities in Palembang City.

Eksplorasi Fraud Intention pada Karyawan Ditinjau dari Status Hubungan Kerja

Fraud is an action carried out by individuals to seek personal gain at the expense of others. These events lead to large financial losses for the company. This study aims to explore fraud intention among 116 employees based on their employment status. The research employs a quantitative method with a sample of 116 employees positioned as crew store. The participants in this study consist of both contract and permanent employees. The data analysis technique used in this study is descriptive statistical analysis. Fraudulent behavior is difficult to measure; therefore, the instrument in this study uses a development from the theory of planned behavior to measure individual intentions. The results of the study indicate a difference in fraud intention between contract and permanent employees. Overall, the findings show that permanent employees have the highest average scores. Because the measurement of fraud intention in permanent employees is higher than contract employees, therefore, permanent employees have more fraud intention towards the agency than contract employeesKata kunci: fraud, intention to commit fraud, employment status

Perilaku Fraud dalam Kerangka Fraud Triangle : Survey Pada Aparatur Pemerintah Desa

This study aims to analyze the influence of fraud triangle on fraud behavior in village governments. The survey was conducted. The population of this study is the total number of Village Officials in Central Adonara District, East Flores Regency, a total of 65 Village Officials, while the sample taken is 65 respondents using the saturated sample technique. The data collection technique uses questionnaire techniques and data analysis techniques use multiple linear regression. The results of the study show that pressure, opportunity and rationalization have a positive and significant effect on fraud behavior.

The role of obedience pressure and self-monitoring in public procurement fraud: An experimental analysis

Fraud in public procurement is a critical issue; it erodes public trust and disrupts service delivery. Understanding the factors behind procurement fraud is vital for creating effective prevention strategies. While previous studies have linked obedience pressure to unethical behavior, they have not fully examined the role of self-monitoring. This study addresses this gap by investigating the impact of obedience pressure on fraudulent procurement behaviors, with self-monitoring as a moderating factor. Using an experimental method and a 2x2 factorial design, the study involved accounting students from the University of Muhammadiyah Jakarta. Findings indicate that self-monitoring significantly influences the relationship between obedience pressure and fraud: high self-monitoring individuals do not reduce fraudulent behavior under obedience pressure, unlike their low self-monitoring counterparts. Conversely, highly self-monitoring individuals exhibit less fraud when not under obedience pressure compared to those who experience such pressure. The study concludes that regardless of self-monitoring levels, subordinates tend to follow superior orders, underscoring the need for strict supervision to curb unethical practices. This research enhances attribution theory by highlighting that obedience pressure from superiors is a key factor driving fraud in the procurement process.

Considerations of Religion and Situational Factors, Internal Control on the Occurrency of Fraud Trends: An Experimental Study of the Financial Services Sector in Indonesia

Financial statement fraud does not only occur in the private sector but can also occur in the government sector in the form of material misrepresentation of financial statements to cover up the actual financial condition by carrying out financial engineering. This study aims to examine religious considerations and situational factors, namely pressure or directives from superiors and internal controls against committing fraud tendencies. Literature reveals that religion plays a dominant role in shaping employees' values in their work. This study used an experimental method on 33 financial institution employees divided into two sessions to see the impact of scenarios. The analysis technique using Analysis of Variances (ANOVA) is used to perform multivariable comparative analysis. The results of empirical testing show that internal control factors have a negative influence on fraudulent behavior, and pressure factors or superior directions have a positive effect on the tendency to commit fraud. Meanwhile, religious considerations have less influence on fraud tendencies.

Fraud Detection of the Electricity Consumption by combining Deep Learning and Statistical Methods

An important issue for the electricity distribution companies is the non-technical loss (NTL), also known as electricity fraud. This issue has a significant impact on the economies of all countries in the world. In this context, we studied the problem of the imbalance between the electrical energy invoiced and the electrical energy supplied within the Algerian economic sector. This article presents an approach to detecting electrical fraud using a combination of Long Short-Term Memory (LSTM) and robust Exponential and Holt-Winters Smoothing (EHWS) methods in order to enhance the accuracy and efficacy of fraud detection mechanisms. The proposed approach investigates the fraudulent behaviour of electricity consumers and unfolds in several key phases. In the first step, monthly consumption forecasts are made and the model with the most accurate results is selected. Then, the phase of detection of anomalies in economic meters and detection of cases of fraud by economic customers begins. This phase relies on the robust exponential and Holt-Winters Smoothing methods for uncovering irregular patterns indicative of potential fraud instances. The proposed model was trained and evaluated, and several experiments were carried out using a large dataset of real users from the economic sector. The dataset comprised approximately 2,000 customers and encompassed 14 years of monthly electricity usage in Bejaia, Algeria. The results of the experiments demonstrate promising performance, underscoring the efficacy of our proposed solution in effectively detecting instances of fraud, leading us to conclude that this proposition is robust and can help improve the accuracy of locating abnormal consumer behaviour and increase the company's profits.

The economic impacts of social activism and corporate social responsibility on food fraud.

The study examines the relationship between the corporate social responsibility (CSR) investments of a food firm, an activist's incentive to target the firm to uncover and deter fraudulent behavior, and the firm's incentive to commit food fraud. Specifically, we develop a game theoretic model to analyze the strategic interaction between a food firm that decides whether to provide a credence food attribute and whether to misrepresent the quality of its product, and an activist who decides whether to monitor the firm and launch a campaign to uncover and remove false/misleading quality claims. We further examine the effect of CSR and the activist's presence on the level of quality the firm provides. We derive the conditions under which an activist will find it optimal to monitor the firm to uncover fraudulent quality claims and the firm will find it optimal to misrepresent its product quality. Analytical results show that the greater the firm's CSR investments, the less likely it is that the activist will find it optimal to monitor the firm, and the more likely it is that the firm will find it optimal to misrepresent its product quality. Results also show that the firm is more likely to misrepresent its product quality when its effectiveness in contesting the activist's campaign is relatively high, and more likely to actually provide a high-quality product when the cost of the credence attribute is relatively low.

Cultivating Honest Character in Social Context: The Basis for Realizing Academic Integrity

Technological advances have a big impact on every line of life, including education. Everyone in the world of education can easily access information from various sources on the internet, this causes a lot of academic fraud to occur, including acts of plagiarism. GONE Theory, discovered by Jack Bologne in 1993, explains a theory about the factors that underlie someone's fraudulent or deceptive behavior. GONE is an abbreviation of Greed (greed), Opportunity (opportunity), Need (need and Exposure). The aim of this research is to determine the dominant influence between the 4 cheating factors. This type of research uses ex post facto with the population being active students in the Province Bali in 2023 who are studying under the auspices of the Ministry of Education, Research and Technology, namely from Ganesha Education University, Udayana University, Bali State Polytechnic, and the Indonesian Institute of Arts, based on data obtained from the Central Statistics Agency, there are 58,588 students (BPS, 2023). table from Krejcie and Morgan, the number of samples for a population of 50,000-75,000 is 382 (taken from N = 50,000-75,000 in Morgan's table) with an accuracy level (d2) of 95% and a significance level (z2) of 5 %. The research results show that the disclosure variable has the greatest influence on academic cheating, namely 39%. Based on these results, honest character is the best solution to create academic integrity among students.

Evaluating the Problem of Fraudulent Participants in Health Care Research: Multimethod Pilot Study.

The shift toward online recruitment methods, accelerated by the COVID-19 pandemic, has brought to the forefront the growing concern of encountering fraudulent participants in health care research. The increasing prevalence of this issue poses a serious threat to the reliability and integrity of research data and subsequent findings. This study aims to explore the experiences of health care researchers (HCRs) who have encountered fraudulent participants while using online recruitment methods and platforms. The primary objective was to gain insights into how researchers detect and mitigate fraudulent behavior in their work and provide prevention recommendations. A multimethod sequential design was used for this pilot study, comprising a quantitative arm involving a web-based survey followed by a qualitative arm featuring semistructured interviews. The qualitative description approach framed the qualitative arm of the study. Sample sizes for the quantitative and qualitative arms were based on pragmatic considerations that in part stemmed from encountering fraudulent participants in a concurrent study. Content analysis was used to analyze open-ended survey questions and interview data. A total of 37 HCRs participated, with 35% (13/37) of them engaging in qualitative interviews. Online platforms such as Facebook, email, Twitter (subsequently rebranded X), and newsletters were the most used methods for recruitment. A total of 84% (31/37) of participants indicated that fraudulent participation occurred in studies that mentioned incentives in their recruitment communications, with 71% (26/37) of HCRs offering physical or electronic gift cards as incentives. Researchers identified several indicators of suspicious behavior, including email surges, discrepancies in contact or personal information, geographical inconsistencies, and suspicious responses to survey questions. HCRs emphasized the need for a comprehensive screening protocol that extends beyond eligibility checks and is seamlessly integrated into the study protocol, grant applications, and research ethics board submissions. This study sheds light on the intricate and pervasive problem of fraudulent participation in health care research using online recruitment methods. The findings underscore the importance of vigilance and proactivity among HCRs in identifying, preventing, and addressing fraudulent behavior. To effectively tackle this challenge, researchers are encouraged to develop a comprehensive prevention strategy and establish a community of practice, facilitating real-time access to solutions and support and the promotion of ethical research practices. This collaborative approach will enable researchers to effectively address the issue of fraudulent participation, ensuring the conduct of high-quality and ethically sound research in the digital age.

The Effect of Pressure, Opportunity, Rationalization, Religiousness on Fraud Behavior (PT. Mayora Indah Tbk Jatake 1)

This study aims to examine the effect of pressure, opportunity, rationalization, and rationalization on employee fraud at PT Mayora Indah Tbk Jatake 1. This type of research is classified as survey research with a quantitative approach. The population in this study were employees of PT Mayora Indah Tbk Jatake 1. The research sample was determined by purposive sampling method so that a sample of 88 was obtained from the questionnaires. Data was analyzed by using multiple regression, intention to commit employee fraud as the dependent variable and pressure, opportunity, rationalization and religion as independent variables. The results of this study indicate that: (1) pressure has a significant positive effect on the intention to commit fraud, (2) opportunity has a significant positive effect on the intention to commit employee fraud, (3) rationalization has a significant positive effect on employee fraud intentions, (4) religion has a significant negative effect on employee fraud intentions. So it can be concluded that opportunity, opportunity, rationalization, and religion have a significant influence on the fraudulent intentions of employees of PT Mayora Indah Tbk Jatake 1.