This is a theoretical treatment of the term "Sha Zhu Pan" (杀猪盘) in Chinese, which translates to “Pig-Butchering” in English. The article critically examines the propagation and validation of "Pig Butchering," an animal metaphor, and its implications for the dehumanisation of victims of online fraud across various discourses. The study provides background information about this type of fraud before investigating its theoretical foundations and linking its emergence to the dehumanisation of fraud victims. The analysis highlights the disparity (...) between academic literature, subjected to rigorous peer-review processes, and sensationalised narratives prevalent in the media. While academic works subject "pig butchering" to critical scrutiny and refrain from endorsing derogatory terms to depict fraud victims, numerous media outlets employ this term uncritically, further worsening the predicament of these victims. "Pig butchering" is firmly rooted in the concept of dehumanisation, and this article underscores how language moulds perceptions of fraud and behaviour, extending to the development of preventive strategies. The role of law enforcement agencies in generating and disseminating materials is also a central theme, emphasising their responsibility as trusted sources of information. We suggest that these agencies should adopt non-victim shaming language to encourage victims to report crimes and alleviate the stigma attached to victimisation. Additionally, the article offers valuable cross-cultural insights by comparing metaphors from Chinese and Nigerian contexts. This comparative analysis enriches our comprehension of the global dimensions of online fraud and its cultural diversities, highlighting the substantial impact of language on perceptions and behaviours. We advocate for a departure from victim-blaming tendencies perpetuated by select media outlets, urging a more compassionate and accurate portrayal of those affected by online fraud. We, therefore, call for a more empathetic and accurate portrayal of individuals affected by online fraud, aligning with the broader objective of promoting understanding and support for these victims. (shrink)

In response to recent controversies about racial transitioning, I provide an argument that deceptions about ancestry may sometimes constitute fraud. In order to arrive at this conclusion, I criticize the arguments from analogy made famous by Rebecca Tuvel and Christine Overall. My claim is that we should not think of racial transitioning as similar to gender transitioning, because different identity groups possess different kinds of obstacles to entry. I then provide historical surveys of American racial categories and the various (...) types of passing common in American history, in order to distinguish the potentially fraudulent from the relatively innocent styles of passing. (shrink)

Using research grants administrators and their clients (academic researchers) as the lens, this paper investigated the relevance and implication of a fraud prevention policy at a University of Technology (UoT) in South Africa. The paper adopted a quantitative approach in which closed-ended questions were complemented by open-ended questions in the survey questionnaire in the attempt to capture the perceptions of both research grants administrators and their clients on the relevance and implications of a fraud and irregularity prevention policy. (...) The results indicate that both research grants administrators (71.4 %), and their clients (73%) do not know if UoTx has a fraud and irregularity policy. While only 36% of research grants administrators indicated that they would feel safe reporting deceitful activities, a slight majority (59%) of the clients reported same. With regards to the steps to follow to report fraudulent activity, it was noted that while all (100%) the research grants administrators noted that they were clueless, ironically an overwhelming majority of their clients indicated otherwise. Notwithstanding, both research grants administrators and their clients (93% and 95% respectively) concurred that a fraud prevention policy was necessary for UoTx. The implication is that having phenomenal controls that are not effectively publicized, monitored or worse still overridden by someone are useless. (shrink)

Given the growing dependence on digital systems and the escalation of financial fraud occurrences, it is imperative to implement efficient cyber security protocols and fraud detection methodologies. The threat's dynamic nature often challenges conventional methods, necessitating the adoption of more sophisticated strategies. Individuals depend on pre-established regulations or problem-solving processes, which possess constraints in identifying novel and intricate fraudulent trends. Conventional techniques need help handling noise data and the substantial expenses incurred by false positives and true positives. To (...) tackle these obstacles, the present study introduces Deep Fraud Net, a framework that utilizes deep learning to detect and classify instances of financial fraud and cyber security threats. The Deep Fraud Net system model entails the utilization of a deep neural network to acquire intricate patterns and characteristics from extensive datasets through training. The framework integrates noise reduction methods to enhance the precision of fraud detection and improve the quality of input data. The Deep Fraud Net method attains a precision of 98.85%, accuracy of 93.35%, sensitivity of 99.05%, specificity of 93.16%, false positive rate of 7.34%, and true positive rate of 89.58%. The findings suggest that Deep Fraud Net can effectively detect and categorize instances of fraudulent behavior with a reduced occurrence of misclassifications. The method exhibits potential implications for diverse domains that prioritize robust security and fraud detection, including but not limited to banking, e-commerce, and online transactions. (shrink)

Fraudulent activities in insurance claims have become a significant challenge for the insurance industry, leading to substantial financial losses annually. This project, titled "Fraud Detection and Analysis for Insurance Claim using Machine Learning" aims to develop a robust and an efficient system to identify and analyze fraudulent claims. The system leverages machine learning techniques to analyze patterns, anomalies, and inconsistencies in claim data, enabling early detection of potentially fraudulent activities.

In this essay, we advocate that the issue of health data ethics should no longer be considered on the level of individual scientists or research labs, but rather as a problem involving all stakeholders, from publishers, funders, ethical committees to governments, for the sake of research integrity.

The study aimed to identify the effect of applying detection and prevention tools for career fraud in combating and preventing fraud and reducing its risks through an applied study on Palestinian Ministry of Health in Gaza Strip, Palestine. To achieve the objectives of the study, the researchers used the questionnaire as a main tool to collect data, and the descriptive and analytical approach to conducting the study. The study population consisted of (501) supervisory employees working at MOH in (...) Gaza Strip, Palestine. The researchers used the stratified random sample method and the multiple regression method to measure the effect. The study concluded a set of results, the most important of which is a positive evaluation among respondents about the levels of application of tools to detect and prevent job fraud within MOH, and the presence of a high interest in tools to prevent job fraud during the implementation of its various work. The study recommended the necessity for the Palestinian National Authority to develop and approve laws regulating health sector, so that those laws guarantee the prevention of conflicts of interest, especially for the category of doctors, by preventing job duplication of doctors working in the government sector. Also study recommended the need for MOH to adopt principles of health sector governance and begin immediately to implement them. This process to ensure transparency, disclosure and accountability in the business framework in a manner that realizes the effective protection of stakeholders and does not compromise or discriminate in the application of these principles, which ensures that all forms of job fraud are organized in an organized manner and within fixed legal frameworks. (shrink)

Detecting fraud in financial transactions is crucial for guaranteeing the integrity and security of financial systems. This paper presents an integrated approach for detecting fraudulent activities that incorporates Support Vector Machines (SVM) and Feedforward Neural Networks (FFNN). The proposed methodology utilizes the strengths of SVM and FFNN to distinguish between classes and capture complex patterns and relationships, respectively. The SVM model functions as a feature extractor, supplying the FFNN with high-level representations as inputs. Through an exhaustive evaluation utilizing labeled (...) financial transaction data, the integrated SVM-FFNN model shows promise in detecting fraud with increased accuracy and precision. This research contributes to the development of innovative techniques for enhancing financial fraud detection systems. (shrink)

This short article introduces the notion that there is a historical relationship between technology and fraud, that two opposing viewpoints argue whether technology is or is not capable of harm, and lastly that platforms can in fact benefit from fraudsters operating on them parasitically.

Credit card fraud has become a significant challenge in the financial sector. The use of machine learning techniques has shown promising results in detecting fraudulent transactions efficiently. This paper discusses the implementation of a credit card fraud detection system using various machine learning algorithms, including Logistic Regression, Decision Trees, Random Forest, and Neural Networks. We evaluate the performance of these models based on accuracy, precision, recall, and F1-score.

The main aim of this project is to detect fraudulent credit card transactions by utilizing credit card details. As financial transactions grow in volume and complexity, it becomes increasingly critical for credit card companies to identify fraudulent activities to protect customers from unauthorized charges. Although instances of fraud are relatively infrequent, they present substantial financial risks to both consumers and financial institutions. This research employs three machine learning techniques—One-Class SVM, Local Outlier Factor, and Isolation Forest—to analyse transaction data in (...) real-time, addressing the challenges posed by imbalanced datasets and the sophistication of fraud schemes. By implementing a comprehensive detection system using these models on a credit card transaction dataset, the study aims to enhance the accuracy of fraud detection and provide timely alerts to prevent financial losses. Key results indicate that the proposed methodology significantly improves the identification of fraudulent transactions, ultimately leading to more secure credit card usage for consumers. The conclusions drawn from this research emphasize the necessity for ongoing innovation in fraud detection methodologies to keep pace with the ever- changing landscape of financial fraud. (shrink)

In today’s rapidly evolving financial landscape, the adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies, coupled with the deployment of Business Rules Management Systems (BRMS), has transformed how financial transactions are conducted, monitored, and secured. With fraud, particularly in check deposit transactions, becoming increasingly sophisticated, financial institutions are turning to AI and ML to enhance their risk management strategies. This paper explores the integration of AI-driven models and business rules in financial transactions, focusing on their application in (...) fraud detection and prevention. We also examine the associated challenges, such as data privacy, ethical concerns, and the need for regulatory frameworks, while outlining the opportunities that lie ahead for future financial innovation. (shrink)

We aimed to identify the critical insights from empirical peer-reviewed studies on online romance fraud published between 2000 and 2021 through a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. The corpus of studies that met our inclusion criteria comprised twenty-six studies employing qualitative (n = 13), quantitative (n = 11), and mixed (n = 2) methods. Most studies focused on victims, with eight focusing on offenders and fewer investigating public perspectives. All (...) the victim-focused studies relied on data from the Global North, except for Malaysia. Five offender-focused studies used online data available in the public domain, and three derived their data from West Africa. Our review highlights offenders' techniques to deceive and manipulate victims, as revealed in these studies, and highlights some limitations of offender- and victim-focused studies. The dominant framework used across the studies was found to be the “Scammers Persuasive Techniques Model.” While this framework provides a helpful way of considering the stages of victim involvement, it also faces some limitations, which we highlight. Our study reviews the current state of empirical knowledge on romance fraud and identifies certain gaps and biases in the literature. We argue there is a need for further research into online romance fraud to enhance our understanding of it both from the perspective of the offender as well as the experience of the victim. We also highlight the need for a more inclusive and greater range of regional and global diverse range of data sources and perspectives. Given the scale and impact of online romance fraud, we conclude that its study would benefit from a richer empirical engagement that recognizes it as both a regional and global phenomenon. (shrink)

This paper revisits the “Hwang case,” which shook Korean society and the world of stem cell research in 2005 with the fraudulent claim of creating patient-specific embryonic stem cells. My goal is to overcome a human-centered, Korea-oriented narrative, by illustrating how materials can have an integral role in the construction and judgment of fraud. To this end, I pay attention to Woo Suk Hwang’s lab at Seoul National University as a whole, including human and nonhuman agents, that functioned as (...) what I call sociomaterial technology, and Gerald P. Schatten at the University of Pittsburgh, Hwang’s collaborator, who played a crucial role in demonstrating the potency of this technology to the members of the scientific community. By recasting the whole event as the “case of Hwang and Schatten,” I argue that fraud is, like all knowledge claims, a sociotechnical construct, and that matters of fraud are locally judged. Fraud leaves its mark on materials, but I show that material evidence alone never tells the whole story and instead can be used to limit the range of responsibility. (shrink)

This research paper investigates the transformative applications of data visualization techniques in the realm of financial crime detection, with a specific emphasis on addressing the challenges posed by credit card fraud and money laundering. The abstract explores the intricate landscape of visualizing financial data to uncover patterns, anomalies, and potential illicit activities. Through a comprehensive review of existing methodologies and case studies, the paper illuminates the pivotal role data visualization plays in enhancing the efficiency and accuracy of fraud (...) detection systems. By synergizing advanced visualization tools with machine learning algorithms, the study aims to provide insights into how financial institutions can bolster their defenses against evolving threats. Ethical considerations, usability, and the real-world impact of data visualization in combating financial crime are also scrutinized. This research contributes to the evolving discourse on leveraging visualization technologies to fortify financial systems against illicit activities, fostering a proactive and responsive approach to safeguarding economic ecosystems. (shrink)

The United Kingdom's Parliamentary Bill 'Fraud Trials (Without a Jury) 2007', failed. Nevertheless, fraud trials without a jury do take place and there is much evidence to support this. Today the UK still does not support fraud trials without a jury, even though fraud in the UK today is the highest amount of fraud globally. The longer version of this paper is submitted here since it has become urgent that UK fraud trials be examined (...) as a matter of urgency. On page 87 of this complete paper (cut down for The Criminal Lawyer in 2008) a U.S study of 46 corporate fraud trials revealed that the defendants were CEOs, President, Chairman, Senior Vice Presidents, Chief Financial Officers, but only one entity reach trial stage. After the ce Arthur Anderson LLP v. United States, 544 U.S. 696 (2005), and the Lehman Brothers SEC case and the SEC v. Bank of America Corp., 653 F. Supp. 2d 507 (S.D.N.Y. 2009, and the Report by the U.S. Financial Crisis Inquiry on the 2008 financial crash, a global financial disaster was predicted and George Osborne, UK Chancellor pleaded for leniency for HSBC Bank frauds, threatening a global meltdown. The U.S. judiciary increased its volume of Deferred Prosecution Agreements and the UK followed suit. So, in year 2022, there is global financial meltdown and the UK has the highest rate of fraud in the world with few successful convictions. This paper is very relevant today as we must stop using deferred prosecution agreements and seek more convictions and harsh jail sentences for those financial fraudsters who have created this meltdown. -/- *When this paper was written, UK fraud was estimated at £40 million and some experts suspected twice that amount. Today UK fraud is in the billions of pounds annually. (shrink)

All things considered, there are many public assistance recipients for whom there are compelling moral reasons to engage in welfare fraud. For many people, failure to defraud the welfare system, should they find themselves in a position to do so with impunity, would constitute a serious moral offense. This conclusion seems to fly in the face of prevailing notions of common sense. But this is misleading, since it is at the same time implied by principles that are widely embraced, (...) assuming a set of circumstances that can be readily shown to obtain in many cases. Under that set of circumstances, and given our affirmation of certain basic moral convictions, we cannot consistently blame the practitioner of welfare fraud, or excuse, without special justifications, the legal conformist. (shrink)

The study ascertained the perception of lecturers and students on the role of social support and psychological first aid in assisting financial fraud victims in South East Nigeria. The study adopted a descriptive survey design. The study was carried out in three Universities in the South East, Nigeria: the University of Nigeria, Nsukka; Nnamdi Azikiwe University, Awka; and Michael Okpara University of Agriculture, Umudike. The population comprises of 135 students and 52 lecturers in Home Economics programme of the three (...) Universities, making a total of 187 respondents. The entire population is used as the sample of the study because of the manageable size. A 32-item Questionnaire was used as instrument for data collection. The instrument is validated by three experts. Data collected is analyzed using mean and standard deviation to answer research questions. Decision on research questions is taken based on real limits of numbers. For the test of significance, the probability (p) value is used in comparison with the alpha value of 0.05, and at 90 degree of freedom (df). The study found that social support and psychological first aid can be used to help financial fraud victims by reaching out to them to help them cope with stress and psychological trauma associated with loss of properties. The study recommended that government at all levels should establish social support and psychological first aid units that will help to cater for the emotional, psychological and other needs of financial fraud victims in order to enable them recover efficiently. (shrink)

This paper investigates how the credit incentive to engage in questionable research practices interacts with cumulative advantage, the process whereby high-status academics more easily increase their status than low-status academics. I use a mathematical model to highlight two dynamics that have not yet received much attention. First, due to cumulative advantage, questionable research practices may pay off over the course of an academic career even if they are not attractive at the level of individual publications. Second, because of the role (...) of bottleneck moments in academic careers, questionable research practices may be selected for even if they do not provide a benefit in expectation. I also observe that, within the model, the most successful academics are the most likely to have benefited from fraud. (shrink)

This paper critically evaluates the classification of research-related fraudulent activities, with an emphasis on the specific misconduct falsification. The analysis begins by interrogating the assumption that all acts of fraud in research are intentional, suggesting that some instances may inadvertently arise during the course of scholarly activities. Misconducts like fabrication and falsification are categorized as fraudulent primarily due to their generation during research activities and their direct contribution to the distortion of scientific knowledge. Plagiarism, while deceptive, does not necessarily (...) originate from the research process nor lead directly to such distortion, and therefore is not classified as de facto fraud. The paper proposes that the definition of falsification – as established by the PHS – requires refinement to prevent wrongful allegations and convictions, enhance transparency, and offer clearer guidelines. This nuanced understanding is vital for safeguarding the credibility of the research process and protecting scientists from unfounded career-damaging accusations. Ultimately, this paper advocates for a clearer definition of falsification to protect the integrity of scientific research and prevent the miscarriage of justice. (shrink)

The internet has made the world more linked than ever before. While taking advantage of this online transition, cybercriminals target flaws in online systems, networks, and infrastructure. Businesses, government organizations, people, and communities all across the world, particularly in African countries, are all severely impacted on an economic and social level. Many African countries focused more on developing secure electricity and internet networks; yet, cybersecurity usually receives less attention than it should. One of Africa's major issues is the lack of (...) adequate digital security infrastructure, which has harmed businesses, governmental institutions, and individual communities more than it has helped. The majority of African countries operate without cybersecurity measures in place to combat cyberattacks. Only a few examples of today's cyber risks include digital extortion, business email intrusion, data breaches, online fraud, ransomware, and phishing, and new types of cybercrime are always developing. Due to the advent of new technology, cybercriminals have become more organized and quicker in their attacks and alliance creation. To maintain a secure digital environment for all internet users, this study focused on the challenges, solutions, and need for African countries to improve their online safety by tackling cybercrime, online fraud, and cybersecurity concerns. The objective of this study is to offer practical and long-term answers to the problems posed by cybercrime, with a continuing emphasis on enhancing online safety. It will assess the effectiveness of cutting-edge cybersecurity measures, legislative frameworks, and cross-border cooperative efforts, as well as potential areas for improvement. Additionally, the study will examine cutting-edge methods like blockchain technology, machine learning, and other cutting-edge methods that could improve our using digital defences to stop cybercrime. (shrink)

The COVID-19 pandemic has coincided with the proliferation of ethical guidance documents to assist public health authorities, health care providers, practitioners and staff with responding to ethical challenges posed by the pandemic. Like ethical guidelines relating to infectious disease that have preceded them, what unites many COVID-19 guidance documents is their dependency on an under-developed approach to bioethical principlism, a normative framework that attempts to guide actions based on a list of prima facie, unranked ethical principles. By situating them in (...) relation to the key philosophical debates concerning bioethical principlism, we aim to explore the limits and limitations of pandemic ethical guidance documents as, specifically, ethics documents – documents that fulfil the functions of ethics as a fundamentally normative discipline. This means not only determining whether such ethical guidance documents can, in principle, provide adequate action guidance and action justification, but also, more importantly where pandemics are concerned, determining whether they support consistent decision making and transparent processes of justification. Having highlighted the problems with merely furnishing ethical guidelines with substantive ethical content in terms of principles and values, we argue that organizations that develop these documents should, instead, focus on the procedural dimensions of action guidance and action justification, which extend to questions regarding the make-up of the committees, panels and groups that develop such guidelines, the public transparency of justifications for specific pandemic-related advice or interventions and the development of explicit procedures for transparent and consistent decision making. (shrink)

This article is a review of R.L Park's Voodoo Science: The Road from Foolishness to Fraud.

A work of Vietnamese art crossed a million-dollar mark in the international art market in early 2017. The event was reluctantly seen as a sign of maturity from the Vietnamese art amidst the many existing problems. Even though the Vietnamese media has discussed the issues enthusiastically, there is a lack of literature from the Vietnamese academics examining the subject, and even rarer in from the market perspective. This paper aims to contribute an insightful perspective on the Vietnamese art market, and (...) hesitantly the Vietnamese art as well, through the lens of fake, forgery and copy artworks. 35 cases of fake, forgery and copy paintings were found on the news and from the experts' wisdom. Through the examples, we argue that the Vietnamese art market is a temporary reaction to the immaturely rising of the Vietnamese art and the economy. Therefore, the art market is unable to function healthily unless the Vietnamese art and the economy developed. (shrink)

Charge card extortion is a difficult issue in monetary administrations. Billions of dollars are lost because of charge card misrepresentation consistently. There is an absence of research concentrates on dissecting true Mastercard information attributable to classification issues. In this paper, AI calculations are utilized to identify charge card misrepresentation. Standard models are utilized. At that point, hybrid techniques which use AdaBoost and Majority Voting are applied. To assess the model viability, a freely accessible charge card informational collection is utilized. At (...) that point, a true charge card informational index from a budgetary organization is investigated. Moreover, noise is added to the information tests to additionally survey the heartiness of the calculations. The exploratory outcomes decidedly demonstrate that the dominant part casting a ballot technique accomplishes great exactness rates in recognizing misrepresentation cases in chargecards. (shrink)

This abstract summarizes, in essence, what generative AI means to the insurance industry. The kind of promise generated AI offers to insurance is huge: in risk assessment, customer experience, and operational efficiency. Natural disaster impact, financial market volatility, and cyber threat are augmented with techniques of real time scenario generation and modeling as well as predictive simulation based on synthetic data. One of the challenges that stand in the way of deploying these AI methods, however, is data privacy, model reliability (...) and interpretability. The insurance industry must address these issues if it is to comply with regulations like GDPR and CCPA or mitigate reputational risks, as anybody can make complaints about any company based on any perceived data breach. Indeed, generative AI models, often convoluted and biased, can propagate unfair outcomes, especially in pricing and policy access. Navigating these challenges requires a whole new frayed society of AI specialists in collaboration with the industry’s insurers to offer bespoke solutions that address the firm’s needs. Based on this work, future developments will center on designing and implementing ethical and regulatory frameworks around AI-driven decisions that are transparent, fair and sustainable. Generative AI has historically been the most feared phenomenon in the history of western civilization, but with predictive analytics and risk simulation capabilities taking shape, generative AI is set to disrupt the insurance industry and add real-time decision support, automating claims processing and personalized interaction. To successfully integrate generative AI, technical, ethical and regulatory challenges will need to be addressed, and a trust-driven ecosystem will emerge to serve evolving customer needs. (shrink)

It has often been noted that Socratic cross-examination is problematic as a method of inquiry, i.e., as a method for 'acquiring' knowledge. Rarely has it been noticed that there are problems with cross-examination when used for the purposes of 'testing' for knowledge. In the 'Charmides', Socrates commits himself to the following principle: In order to discriminate between the person who knows and the person who does not know the subject matter covered by a particular discipline (technê), one must have mastered (...) that discipline. But if Socrates' disavowals of moral knowledge are sincere, it would seem to follow from this principle that, contrary to what Socrates says in many early dialogues, he cannot successfully test claims to moral expertise through cross-examination. Through an examination of the conditions that Socrates places on knowledge and on mastering a 'technê', I show how this problem can be resolved. (shrink)

Who is a child’s father? Is it the man who raised her, or the one whose genes she carries—or both? We look at the view that men who have raised children they falsely believed to be ‘their own’ have been victims of a form of fraud or are ‘false fathers’. We consider the question of who has been harmed in such cases, and in what the harm consists. We use conceptual analysis, a philosophical method of investigating the use of (...) a concept and the logical implications of its various interpretations. We devise and discuss a number of possible scenarios in which a couple (arguably) become the parents of a child. We use these scenarios to illustrate the tenuousness of the claim that we can simply rely on biology to clarify parent-child relationships. We also discuss some of the underpinnings and implications of the language in which the debate on ‘paternity fraud’ has been framed: ‘duped’ or ‘false’ fathers and ‘cuckoo children’. (shrink)

Abstract: This research paper presents a novel approach to predict audit risks using a neural network model. The dataset used for this study was obtained from Kaggle and comprises 774 samples with 18 features, including Sector_score, PARA_A, SCORE_A, PARA_B, SCORE_B, TOTAL, numbers, marks, Money_Value, District, Loss, Loss_SCORE, History, History_score, score, and Risk. The proposed neural network architecture consists of three layers, including one input layer, one hidden layer, and one output layer. The neural network model was trained and validated, achieving (...) an impressive accuracy of 100% and an average error of 0.000015, indicating its robust predictive capability. Moreover, we conducted feature importance analysis to identify the most influential features for predicting audit risk. The key features found to be critical for classifying fraudulent activities in audit risk prediction are Sector_score, PARA_A, SCORE_A, PARA_B, SCORE_B, TOTAL, numbers, marks, Money_Value, District, Loss, Loss_SCORE, History, and History_score. This research contributes to the field of audit risk prediction by demonstrating the effectiveness of a neural network-based approach and highlighting the importance of specific features in detecting fraudulent activities. The findings have significant implications for auditors and organizations seeking to enhance their audit risk assessment processes, ultimately leading to improved financial transparency and fraud detection. (shrink)

Most regulations and guidelines require that potential research participants be told a great deal of information during the consent process. Many of these documents, and most of the scholars who consider the consent process, assume that all this information must be disclosed because it must all be understood. However, a wide range of studies surveying apparently competent participants in clinical trials around the world show that many do not understand key aspects of what they have been told. The standard view (...) of the conditions for valid consent therefore implies that these people have failed to give valid consent to research participation. In this paper we argue that the standard view is false. The primary function of the requirement that researchers disclose information about a study is the avoidance of illegitimate control over someone’s consent decision, which is a form of fraud.We derive the content and manner of appropriate disclosure by analysing the ways in which the manipulation of information can invalidate consent. Our analysis shows that the informational requirements for valid consent are conceptually distinct and thus unlikely to have identical contents. This implies that consent can be valid when not everything that ought to be disclosed by the person asking for consent is understood by the person who proffers it. (shrink)

The use of deception and dishonesty is widely accepted as a fact of life in policing. This paper thus defends a counterintuitive claim: Good faith is a normative foundation for the police as a political institution. Good faith is a core value of contracts, and policing is contractual in nature both broadly (as a matter of social contract theory) and narrowly (in regard to concrete encounters between law enforcement officers and the public). Given the centrality of good faith to policing, (...) dishonesty and deception on par with fraud are justified only as a narrowly circumscribed investigative tool that is constrained by institutional commitments to the fair distribution of security and the rule of law. The practical upshot is the preclusion of most dishonest and deceptive police tactics on par with fraud, leading to an institution that is less proactive and more reactive. (shrink)

Cooperative relations steeped in honesty and good faith are a necessity for any viable society. This is especially relevant to the police institution because the police are entrusted to promote justice and security. Despite the necessity of societal honesty and good faith, the police institution has embraced deception, dishonesty, and bad faith as tools of the trade for providing security. In fact, it seems that providing security is impossible without using deception and dishonesty during interrogations, undercover operations, pretextual detentions, and (...) other common scenarios. This presents a paradox related to the erosion of public faith in the police institution and the weakening of the police's legitimacy. -/- The book seeks to solve this puzzle by showing that many of our assumptions about policing and security are unjustified. Specifically, they are unjustified in the way many of our assumptions about security were unjustified after the 9/11 terrorist attacks, when state institutions embraced a variety of brutal rules and tactics in pursuit of perceived security enhancements. The police are likewise unjustified in their pursuit of many supposed security enhancements that rely on proactive deception, dishonesty, and bad faith. -/- There are compelling reasons to think that the police's widespread use of proactive deception and dishonesty is inconsistent with fundamental norms of political morality regarding fraud and the rule of law. Although there are times and places for such tactics in policing, those times and places should be much more limited than current practices suggest. (shrink)

This study sets out to examine the ways Nigerian cyber-fraudsters (Yahoo-Boys) are represented in hip-hop music. The empirical basis of this article is lyrics from 18 hip-hop artists, which were subjected to a directed approach to qualitative content analysis and coded based on the moral disengagement mechanisms proposed by Bandura (1999). While results revealed that the ethics of Yahoo-Boys, as expressed by musicians, embody a range of moral disengagement mechanisms, they also shed light on the motives for the Nigerian cybercriminals' (...) actions. Further analysis revealed additional findings: “glamorization/de-glamorization of cyber-fraud” and “sex-roles-and-cultures”. Having operated within the constraint of what is currently available (a small sample size), this article has drawn attention to the notion that Yahoo-Boys and some musicians may be “birds of a feather.” Secondly, it has exposed a “hunter-and-antelope-relationship” between Yahoo-Boys and their victims. Thirdly, it has also highlighted that some ethos of law-abiding citizens is central to Yahoo-Boys’ moral enterprise. Yahoo-Boys, therefore, represent reflections of society. Arguably, given that Yahoo-Boys and singers are connected, and the oratory messages of singers may attract more followers than questioners, this study illuminates the cultural dimensions of cyber-fraud that emanate from Nigeria. In particular, insights from this study suggest that cyber-fraud researchers might look beyond traditional data sources (e.g., cyber-fraud statistics) for the empirical traces of “culture in action” that render fraudulently practices acceptable career paths for some Nigerian youths. (shrink)

The police are required to establish probable cause before engaging in custodial interrogation. Much custodial interrogation relies on a fraudulent epistemic environment (FEE) in which the police knowingly use deception and dishonesty to gain an advantage over a suspect regarding a material issue, injuring the interests of the suspect. Probable cause, then, is a sort of evidentiary and epistemic standard that legally justifies the police’s use of deceptive and dishonest custodial interrogation tactics that are on par with fraud. However, (...) there are both deontological and consequentialist considerations that show why the police’s use of an FEE is often unjustified. Accordingly, the paper argues that even if the use of an FEE is based on probable cause, there are other (non-epistemic) reasons to think evidence with probative value (such as a confession) should be excluded when derived from an FEE and there is no acute threat of harm to others. (shrink)

This paper examines how predictive analytics enhances risk management in financial institutions. Advanced tools like machine learning and statistical modeling help predict risks, identify trends, and implement strategies to prevent losses by analyzing historical and real-time data. It covers the use of predictive analytics for credit risk, market risk, operational risk, and fraud detection, with practical case studies. Additionally, it discusses challenges, ethical issues, and prospects in this field.

Allegations of fraud involving falsification as research misconduct may result in severe consequences for those convicted. The focus of this article is the Public Health Service’s (PHS) definition of falsification . A well-articulated revised definition is required for veritable instances of falsification as misconduct to be consistently identified and potentially offer a framework for elucidation. A philosophical critique of the explicit definition is undertaken to determine what comprises falsification at its core, which could substantially reduce the number of allegations (...) of fraud as suspected instances of misconduct. The flaw in the PHS definition of falsification is due to circular logic, which allows anything to be proven according to it. Furthermore, to be confident that falsification has occurred, one must be certain of what is true when it has not occurred, which is demonstrated not to be plausible. falsification was found to be the most common type of fraud as misconduct alleged yet the rarest to be determined to occur because the flawed definition confounds what constitutes an occurrence of it. In addition to conceptual ambiguity and ignorance, allegations of falsification are suggested to occur strategically as maneuvers by researchers who may exploit the inherent flaw in the definition to eliminate rival competitors. -/- The purpose of part two is to critique the definition of falsification as research misconduct according to the Public Health Service (PHS) in order to better understand what it entails. In support of this purpose, the approach decided upon for analysis was philosophical including framing the issue borrowing from both mereological and epistemological perspectives. Through the consideration given to parthood relations of mereology, we gained insight from a cognitive imperfection standpoint about similarities that exist between the epistemic constraints on knowledge and the nature of violations concerning research misconduct. Findings from the examination of a case study include the significance of accuracy in representation in falsification as misconduct and the core dimensions comprising an instance of falsification, which are Deliberateness, Alteration, and Inclusion. Given that either behavior or actions must occur that violate these three aspects in order to qualify as an instance of misconduct under falsification, the author proposes that, at a minimum, any revisions made to the definition of falsification stipulate what he refers to as the Violation Imperative. (shrink)

Artificial Intelligence (AI) and Machine Learning (ML) are transforming the insurance industry by optimizing risk assessment, fraud detection, and customer service. However, the rapid adoption of these technologies raises significant ethical concerns, particularly regarding bias and fairness. This chapter explores the ethical challenges of using AI and ML in insurance risk management, focusing on bias mitigation and fairness enhancement strategies. By analyzing real-world case studies, regulatory frameworks, and technical methodologies, this chapter aims to provide a roadmap for developing ethical (...) AI/ML systems in the insurance sector. It highlights the importance of transparency, accountability, and inclusivity in ensuring equitable outcomes. (shrink)

Generative artificial intelligence (Gen AI) and machine learning (ML) technologies are changing the way the insurance industry looks, particularly by integrating Gen AI & ML technologies. As a leading platform for property and casualty insurance, Guidewire provides a perfect platform for deploying intelligent claims processing workflows that can dramatically improve efficiency, accuracy and customer satisfaction. The seamless integration of Gen AI and ML capabilities into Guidewire to autonomously process claims is explored in this paper. Insurers can use advanced models to (...) drive self-driving workflows that are capable of automating tasks like claims triage, fraud detection, damage assessment and settlement optimization. But most importantly, these technologies reduce operational costs, and reduce the human intervention involved such that claims can be handled faster and with more accuracy. In this work, we discuss what technical and strategic considerations need to be taken into account when implementing such workflows, such as data integration, model training, and ethical AI practices. This paper also demonstrates several real-world use cases, the challenges you in each, and the potential to scale these solutions across lines of business. With an eye on the future, autonomous claims processing enables insurers to find their next competitive edge by providing innovative solutions that alter the course of expectations of customers while qualifying to regulatory and compliance standards. Self-driving workflows powered by Gen AI and ML in claims are the future of insurance and their ability to transform the entire process of claims management. (shrink)

In 2001 soon after the Asian Crises of 1997-1998, the DotcomBubble, 9/11, the Enron crises triggered a fraud crisis in Wall Street that impacted the market to the core. Since then scandals such as the Lehman Brothers and WorldCom in 2007-2008 and the Great Recession have surpassed it, Enron still remains one of the most important cases of fraudulent accounting. In 2000’s even though the financial industry had become highly regulated, deregulation of the energy industry allowed companies to place (...) bets on future prices. At the peak of the dotcom bubble Enron was named as a star innovator but when the dotcom bubble burst, Enron’s plan to build high speed internet did not flourish and investors started to realize losses. Furthermore, the financial losses of the operations were hid using the market to market accounting technique instead of book value and using special purpose entities to hide debt. The root cause that was identified as a company with a toxic corporate culture focused on officer compensation rather than social responsibility and hence faulty leadership. Is it possible then that; ethical accounting practices, social responsibility and ethics all become inferior goods as income rises in an ‘irrationally exuberant’era? (shrink)

In today’s fast moving insurance environment, efficient claim management is a vital business practice to improve operational effectiveness and provide an exceptional customer experience. Based on the first notice of loss (FNOL), Guidewire Claim Center, the leading claims management platform, gives insurers the thorough, scalable, and customizable option to accelerate the claims process from FNOL to final resolution. In this paper, we explore how insurers adapt Guidewire Claim Center to enable effective utilization of Guidewire Claim Center to optimize and transform (...) their claim management process, making better decisions, and delivering better customer experience. Advanced automation features, their role in reducing manual footprint, and the integration of the platform with external systems for a smooth data flow and analytics driven insights are key things covered. Finally we see real world case studies detailing where Guidewire's predictive analytics are in use for fraud detection, expedited claims processing and building proactive relationships between the claimant and the Carrier. We also look at best practices for implementation and ways to work around typical problems, including change management, system customization, and others. Framed around the dual aims of operational efficiency and customer satisfaction, this blueprint offers practical advice for insurers navigating a more and more digitalized industry. Guidewire Claim Center is agile, flexible foundations that can help insurers transform their claims operations, while also creating lasting trust and loyalty with policyholders. (shrink)

As the integration of Artificial Intelligence (AI) and cloud computing transforms the insurance industry, it is undergoing a major breakthrough. With these technologies, insurers can modernize operations, improve the customer experience and make better decisions using real time data and predictive analytics. This paper aims to explore why AI and cloud play such critical roles in shifting insurance practice from legacy systems modernization, to data governance and regulatory compliance to workforce readiness. Today, world-class AI powered tools and cloud platforms such (...) as AWS and Snowflake provide hyper personalization, one-touch automated claims, fraud detection, etc. IoT data can be used to perform dynamic risk assessment for insurers and even to offer products that start with low code and no code solutions to make technology available across an organization. Edge computing, as well as sustainability across insurance products, shows that there is more innovation potential. Yet, these technologies cannot be fully integrated. However, the industry must figure out how to navigate evolving regulations, employ explainability in AI-driven decisions, and address vendor dependency issues. Governance frameworks need to be strengthened;the workforce needs to be upskilled, collaborate with InsurTech startups, and so on. The paper ends with a forward-looking view, offering potential expansion into underserved markets, more advanced predictive analytics, and better customer contact through omnichannel support via AI enabled risk coaching. Embracing these advances, insurers can chart a new course and lead the digital transformation era by providing more value to stakeholders in an evolving environment. (shrink)

The rise in cyber threats targeting financial institutions has led to the adoption of artificial intelligence (AI) and deep learning models to mitigate risks and detect fraud in real-time. This paper explores AI-powered cybersecurity frameworks that enhance fraud detection, risk analytics, and compliance automation in financial transactions.

Artificial Intelligence (AI) is increasingly adopted in society, creating numerous opportunities but at the same time posing ethical challenges. Many of these are familiar, such as issues of fairness, responsibility and privacy, but are presented in a new and challenging guise due to our limited ability to steer and predict the outputs of AI systems. This chapter first introduces these ethical challenges, stressing that overviews of values are a good starting point but frequently fail to suffice due to the context (...) sensitivity of ethical challenges. Frequently, additional (ethical) values emerge for specific applications, as e.g. challenges with fraud detection are very different from those around language technologies. Second, methods to tackle these challenges are discussed. Main ethical theories (virtue ethics, consequentialism, and deontology) are shown to provide a starting point, but often lack the details needed for actionable AI Ethics. Instead, mid-level philosophical theories coupled to design-approaches such as Design for Values, together with interdisciplinary working methods, offer the best way forwards. The chapter aims to show how these approaches can lead to an ethics of AI that is actionable and that can be proactively integrated in the design of AI systems. (shrink)

Generative AI is reshaping sectors like banking and healthcare by enabling innovative applications such as personalized service offerings, predictive analytics, and automated content generation. In banking, generative AI drives customer engagement through tailored financial advice, fraud detection, and streamlined customer service. Meanwhile, in healthcare, it enhances medical imaging analysis, drug discovery, and patient diagnostics, significantly impacting patient care and operational efficiency. This paper presents an experimental study examining the implementation and effectiveness of generative AI in these sectors.

Abstract: This research focuses on utilizing Artificial Neural Networks (ANNs) to predict Audit Risk accurately, a critical aspect of ensuring financial system integrity and preventing fraud. Our dataset, gathered from Kaggle, comprises 18 diverse features, including financial and historical parameters, offering a comprehensive view of audit-related factors. These features encompass 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' 'History_score,' 'score,' and 'Risk,' with a total of 774 samples. Our proposed neural network architecture, consisting of (...) three layers (1 input, 1 hidden, and 1 output), forms the core of this study. While it may seem simple, the power of ANNs lies not in complexity but in their ability to uncover intricate data patterns. The model underwent rigorous training and validation, resulting in remarkable outcomes—an accuracy of 100% and an average error rate of 0.000015. In addition to performance metrics, our research investigates feature importance, revealing the key contributors to Audit Risk prediction. Notably, 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' and 'History_score' emerged as the most influential factors, shedding light on the elements crucial for precise risk assessment. This study advances Audit Risk prediction models and highlights the potential of ANNs in strengthening financial system integrity and fraud prevention. The insights gained from our findings offer practical guidance for stakeholders in the audit and financial sectors. (shrink)

Deception sometimes results in nonconsensual sex. A recent body of literature diagnoses such violations as invalidating consent: the agreement is not morally transformative, which is why the sexual contact is a rights violation. We pursue a different explanation for the wrongs in question: there is valid consent, but it is not consent to the sex act that happened. Semantic conventions play a key role in distinguishing deceptions that result in nonconsensual sex (like stealth condom removal) from those that don’t (like (...) white lies). Our framework is also applicable to more controversial cases, like those implicated in so-called “gender fraud” complaints. (shrink)

Artificial intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and (...) inherently interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space. (shrink)

Preregistration has been proposed as a useful method for making a publicly verifiable distinction between confirmatory hypothesis tests, which involve planned tests of ante hoc hypotheses, and exploratory hypothesis tests, which involve unplanned tests of post hoc hypotheses. This distinction is thought to be important because it has been proposed that confirmatory hypothesis tests provide more compelling results (less uncertain, less tentative, less open to bias) than exploratory hypothesis tests. In this article, we challenge this proposition and argue that there (...) are several advantages of exploratory hypothesis tests that can make their results more compelling than those of confirmatory hypothesis tests. We also consider some potential disadvantages of exploratory hypothesis tests and conclude that their advantages can outweigh the disadvantages. We conclude that exploratory hypothesis tests avoid researcher commitment and researcher prophecy biases, reduce the probability of data fraud, are more appropriate in the context of unplanned deviations, facilitate inference to the best explanation, and allow peer reviewers to make additional contributions at the data analysis stage. In contrast, confirmatory hypothesis tests may lead to an inappropriate level of confidence in research conclusions, less appropriate analyses in the context of unplanned deviations, and greater bias and errors in theoretical inferences. (shrink)