People can use credit cards for online transactions as it provides an efficient and easy-to-use facility. With the increase in usage of credit cards, the capacity of credit card misuse has also ...enhanced. Credit card frauds cause significant financial losses for both credit card holders and financial companies. In this research study, the main aim is to detect such frauds, including the accessibility of public data, high-class imbalance data, the changes in fraud nature, and high rates of false alarm. The relevant literature presents many machines learning based approaches for credit card detection, such as Extreme Learning Method, Decision Tree, Random Forest, Support Vector Machine, Logistic Regression and XG Boost. However, due to low accuracy, there is still a need to apply state of the art deep learning algorithms to reduce fraud losses. The main focus has been to apply the recent development of deep learning algorithms for this purpose. Comparative analysis of both machine learning and deep learning algorithms was performed to find efficient outcomes. The detailed empirical analysis is carried out using the European card benchmark dataset for fraud detection. A machine learning algorithm was first applied to the dataset, which improved the accuracy of detection of the frauds to some extent. Later, three architectures based on a convolutional neural network are applied to improve fraud detection performance. Further addition of layers further increased the accuracy of detection. A comprehensive empirical analysis has been carried out by applying variations in the number of hidden layers, epochs and applying the latest models. The evaluation of research work shows the improved results achieved, such as accuracy, f1-score, precision and AUC Curves having optimized values of 99.9%,85.71%,93%, and 98%, respectively. The proposed model outperforms the state-of-the-art machine learning and deep learning algorithms for credit card detection problems. In addition, we have performed experiments by balancing the data and applying deep learning algorithms to minimize the false negative rate. The proposed approaches can be implemented effectively for the real-world detection of credit card fraud.
Predicting Federal Contractor Misconduct Alford, Laura C.; Hansen, Stephen C.; Hermis, Judith M.
Journal of forensic accounting research,
12/2023, Volume:
8, Issue:
1
Journal Article
Peer reviewed
Open access
ABSTRACT
Between 1995 and 2021, the United States’ Federal Government imposed $162.5 billion in penalties upon government contractors who had engaged in improper behavior as part of the procurement ...process. Despite the enormity of contractor misbehavior, the characteristics associated with contractor misconduct are relatively underexplored in academic literature. In this study, we examine whether and to what extent firm characteristics predict federal government contractor misbehaviors, which range from minor statutory violations to fraud. We document a consistent association between contractor characteristics (size and total amount of government contracts received), contract-specific characteristics (service-type contracts and awarding agencies GSA and DOE), and the act of committing misconduct. Misconduct severity increases in size and total amount of government contracts, is not affected by service contracts, and has an inverse U-shape for government agencies. Taken together, our results suggest that characteristics of the contractor, contract, and government agency are predictably associated with committing procurement misconduct.
Data Availability: Data are available from the public sources cited in the text.
JEL Classifications: H11; H57; M41.
Based on evidence from press articles covering 39 corporate fraud cases that went public during the period 1992-2005, the objective of this article is to examine the role of managers' behavior in the ...commitment of the fraud. This study integrates the fraud triangle (FT) and the theory of planned behavior (TPB) to gain a better understanding of fraud cases. The results of the analysis suggest that personality traits appear to be a major fraud-risk factor. The analysis was further validated through a quantitative analysis of keywords which confirmed that keywords associated with the attitudes/rationalizations component of the integrated theory were predominately found in fraud firms as opposed to a sample of control firms. The results of the study suggest that auditors should evaluate the ethics of management through the components of the TPB: the assessment of attitude, subjective norms, perceived behavioral control and moral obligation. Therefore, it is potentially important that the professional standards that are related to fraud detection strengthen the emphasis on managers' behavior that may be associated with unethical behavior.
Purpose
The criminalization of online financial fraud is examined by analyzing the existing literature, policies and state statutes within the context of the cybercrime ecosystem. Therefore, this ...paper aims to investigate online fraud policies within the USA and the prevalence of such incidents to explore the effectiveness of current fraud policies.
Design/methodology/approach
This examination explores policies related to online fraud within the USA by defining online financial fraud incidents within the context of the cybercrime ecosystem and analyzing such incidents with routine activities theory to emphasize the current legislative inadequacies with provisional policy recommendations.
Findings
This research suggests online financial fraud is not unanimously conceptualized among regulating or criminal institutions. Although federal regulators have governed financial institutions, federal institutions have failed to account for the capabilities of computer-mediated and technological device use (12 USC §1829).
Research limitations/implications
The limited research analyzing the effectiveness of guardianship that prevents or deters internet-mitigated or dependent financial fraud crimes.
Practical implications
Policy recommendations include but are not limited to mandating federal and privatized financial institutions to disclose all fraudulent activity to all stakeholders (e.g. customers and local and federal criminal justice agencies).
Originality/value
This paper provides an innovative approach using a criminological theory and policy framework to examine the prevalence of online fraud and the regulations enacted to counteract such violations.
A comprehensive taxonomy of fraud is presented based on morphological analysis, attribute listing and matrix analysis. Fraud matrix and tree classification frameworks are presented and discussed. ...They are then utilized to classify and explain a number of the different types of frauds, shown in the fraud matrix classification framework. First, triangular attributes of fraud are formulated, followed by fraud channels and elementary fraud features. Several well-known fraud types are identified using the proposed fraud classification framework. Further, new fraud types are discovered using the framework, for example, transactional frauds, automated frauds, synchronized fraud, unwitting accomplice, and ‘Robin Hood’ fraud. The importance of the taxonomy is that it can be used to classify both existing and newly identified fraud types in a way and manner that has not been previously reported; that is, it offers understanding to the different classes of frauds, the inherent threat actors behind such frauds, their capabilities, intent and the resulting nature of the frauds. This taxonomy has potential to offer insight in how appropriate countermeasures to mitigating the different types of frauds could be formulated.
Hospice fraud is a growing concern around the world. Yet, little attention has been given to the study of hospice fraud in the extant literature. Existing literature highlights fraud exposure related ...to hospice payment structures, the factors that contribute to fraud, and the innate personality traits of fraudsters. Typically, however, the traits of fraudsters do not align with the public image of hospice professionals. This misalignment suggests the need for valid and reliable instruments designed to measure fraud ability and intent. In this article, the psychometric properties of two valid and reliable tools are examined, one designed to measure fraud rationalization, and the other was designed to measure fraud intent. Both tools are psychometrically sound, but further investigation into the phenomenon of hospice fraud using these tools is warranted as they are newly developed. Investigation into the use of the tools in practice settings is also an avenue for further inquiry.
Is the Macau scam a fraud? Ismail, Nurbazla; Ramlee, Zulfakar; Abas, Afridah
Journal of financial crime,
01/2022, Volume:
29, Issue:
1
Journal Article
Peer reviewed
Purpose
There is a broad description of fraud debated by academics around the world. The definition of fraud differs between governments, criminal justice departments and private entities. Some ...questions can make this study important to explain the concept of fraud. This study aims to define the legal concept of fraud. The concept of a word is important to discuss because it explains the meaning of a word and that could answer the question on Macau scam – a fraud?
Design/methodology/approach
The content analysis is the research design of this study. Data were obtained by document analysis, including books, papers, journals, case reports and other records relating to fraud. The methods used to interpret the data for this qualitative research are empirical, deductive and inductive.
Findings
This study found that the concept of fraud has not yet been defined. This can give rise to a broad interpretation, depending on the action taken by the parties in the cases. On the basis of the context of the dictionary, fraud may be said to be the same thing as deception. Sometimes, the use of words to convey things that are different from, and even at odds with, the actual sense of words. Whereas, from a legal point of view, fraud still occurs as a matter of fact to be determined. This study showed that Macau scam is a fraud.
Originality/value
The implication of this analysis is for scholars and legal professionals to assess the principle of fraud prior to the accusation.
Abstract
Romance fraud affects thousands of victims globally, yet few scholars have studied it. The dynamics of relationships between victims and offenders are not well understood, and the effects ...are rarely discussed. This article adapts the concept of psychological abuse from studies of domestic violence to better understand romance fraud. Using interviews with 21 Australian romance fraud victims, we show how offenders use non-violent tactics to ensure compliance with ongoing demands for money. This article identifies similarities and differences between domestic violence and romance fraud. We argue that thinking through domestic violence and romance fraud together offers potential benefits to both bodies of research.
Credit card fraud detection is a challenging task since fraudulent actions are hidden in massive legitimate behaviors. This work aims to learn a new representation for each transaction record based ...on the historical transactions of users in order to capture fraudulent patterns accurately and, thus, automatically detect a fraudulent transaction. We propose a novel model by improving long short-term memory with a time-aware gate that can capture the behavioral changes caused by consecutive transactions of users. A current-historical attention module is designed to build up connections between current and historical transactional behaviors, which enables the model to capture behavioral periodicity. An interaction module is designed to learn comprehensive and rational behavioral representations. To validate the effectiveness of the learned behavioral representations, experiments are conducted on a large real-world transaction dataset provided to us by a financial company in China, as well as a public dataset. Experimental results and the visualization of the learned representations illustrate that our method delivers a clear distinction between legitimate behaviors and fraudulent ones, and achieves better fraud detection performance compared with the state-of-the-art methods.