Fraudulent Behavior Research Articles

Knocking sovereign customers off their pedestals? When contact staff educate, amateurize, and penalize deviant customers

Promoted by marketing discourses, customer sovereignty is characterized by the cult of the customer and the belief that contact staff have to serve the customer. However, research shows that customers adopt improper conduct, such as fraudulent or aggressive behaviors. While largely tolerated, these behaviors prove damaging for contact staff and could eventually lead them to react. How do frontline actors react to such behaviors, which prevent them from developing customer relations in accordance with the mythical discourse? This is the question our article explores. To do so, we use Becker’s interactionism approach to deviance, and investigate how frontline actors in five organizations deal with customer complaints they consider as ‘deviant’. Our results show that when faced with behaviors that they no longer wish to tolerate, contact staff educate, amateurize, or penalize the customer. This research contributes by conceptualizing three alternative forms of relations to customer sovereignty, which contact staff attempt to legitimize through internal and external resources.

Corporate governance: five-factor theory-based financial fraud identification

The frequent occurrences of financial fraud in listed companies have had a serious impact on the stable development of the capital market. The Chinese company, Luckin Coffee, listed in the USA, recently confessed to fabricating transactions worth RMB2.2 billion and has received a delisting notice from NASDAQ. It can be seen that the detection and analysis of financial fraud behavior is very important not only for the internal governance of companies and for their external investors but also for regulatory agencies. This article uses a research method combining normative analysis with empirical research, utilizes a targeted selection of data from the listed companies penalized due to fictitious profits, uses the CRIME theory as the basis for normative analysis, and establishes a financial fraud identification model by means of empirical analysis. Finally, based on the research results of this article, we propose rational governance measures for countering the problems of fraud in financial statements of listed companies.

Inclusion of Emotional Support Animals as Service Animals Under the ADA: Creating the Right to Use Dogs to Assist People Living with Mental Health Issues

This article asserts that Congress should amend the Americans with Disabilities Act (“ADA”) to recognize emotional support animals as service animals. The article analyzes laws and policies from other arenas such as transportation and higher education to demonstrate the need for and potential structure of such change. Indeed, the article proposes specific amendment language based upon this analysis. Providing clarity for all Americans, this expanded, clear language will benefit our society and its goals for inclusion and breaking the stigma of mental illness. The use of emotional support animals to alleviate or mitigate symptoms associated with mental health issues has been a topic of debate since its inception. On one hand, there is the community of people who have expressed a need to use support animals to help them to participate in society, including while traveling by airplane. On the other hand, the Department of Transportation has had to assess whether allowing support animals on airplanes would pose a direct threat to the safety or health of others. In the air travel context, support animals have been treated as service animals and special rules have been created to manage the situation. Nonetheless, in most other contexts, support animals are not treated as service animals, so therein lies the confusion. Between the ongoing debate, the need for clarification under the laws, and people’s desire to use emotional support animals to facilitate their participation in society on a daily basis, the law in this area is in a state of flux. Section II of this article provides the legal background on this issue and describes the current controversy over how to treat service animals and emotional support animals under federal law. Section III is an overview of the alternative approaches to defining service animal. Specifically, this section looks at the broader definitions of service animal in the contexts of transportation, higher education, and cities and states. Section IV of this article proposes language that can be used to redraft the ADA’s definition of service animal through the lens of the alternative approaches discussed in this article. This new definition includes the foundational pieces of the current definition regarding traditional service animals plus the inclusion of emotional support animals to provide parity among people with physical disabilities and people with mental health issues. Section V provides predictions for the future and how the inclusion of emotional support animals as service animals under the ADA may affect society at large. Broadening the ADA’s definition of service animal to include emotional support animal will have both positive and negative consequences. Nonetheless, the risk that comes with positive change will be worth it in the end. The biggest issue will most likely be how to ensure that users of emotional support animals are legitimate, meaning there needs to be a mechanism in place to handle issues of fraudulent behavior. With the carefully crafted definition of emotional support animal and the robust fraud mechanisms outlined in this article in place, people with mental health disabilities can have the promise of the ADA fulfilled and be fully integrated into society while still protecting the interests of businesses and others.

Profiling high leverage points for detecting anomalous users in telecom data networks

Fraud in telephony incurs huge revenue losses and causes a menace to both the service providers and legitimate users. This problem is growing alongside augmenting technologies. Yet, the works in this area are hindered by the availability of data and confidentiality of approaches. In this work, we deal with the problem of detecting different types of unsolicited users from spammers to fraudsters in a massive phone call network. Most of the malicious users in telecommunications have some of the characteristics in common. These characteristics can be defined by a set of features whose values are uncommon for normal users. We made use of graph-based metrics to detect profiles that are significantly far from the common user profiles in a real data log with millions of users. To achieve this, we looked for the high leverage points in the 99.99th percentile, which identified a substantial number of users as extreme anomalous points. Furthermore, clustering these points helped distinguish malicious users efficiently and minimized the problem space significantly. Convincingly, the learned profiles of these detected users coincided with fraudulent behaviors.

Competition Dynamics and Fraudulent Behavior – Evidence from a Multi-Period Experiment

The idea of a relationship between competition and fraudulent behavior is well-anchored in the management and adjacent literature. Empirical evidence suggesting that fraudulent behavior is more prevalent under severe competition has a taken-for-granted quality. However, these findings are widely based on a static perspective on the link between competition and fraudulent behavior, in which competition is considered as constantly high or low. Acknowledging the validity of these findings for stable industry environments prevailing in the past, we argue that assuming constant competition over longer periods of time seems outdated in light of today’s increasingly volatile industries. Thus, we introduce a dynamic perspective, in which we investigate how varying extents of competition over time, or competition dynamics, affect fraudulent behavior. Running a laboratory experiment, we analyze abrupt changes from high to low competition over time and vice versa. By this, we offer a more comprehensive and up-to-date understanding of the link between competition and fraudulent behavior.

Functional principal component analysis for near-infrared spectral data: a case study on Tricholoma matsutakeis

Abstract Tricholoma matsutakeis (TM) is the most expensive edible fungi in China. Given its price and exclusivity, some dishonest merchants will sell adulterated TM by combining it with cheaper fungi in an attempt to earn more profits. This fraudulent behavior has broken food laws and violated consumer trust. Therefore, there is an urgent need to develop a rapid, accurate, and nondestructive tool to discriminate TM from other edible fungi. In this work, a novel detection algorithm combined with near-infrared spectroscopy (NIR) and functional principal component analysis (FPCA) is proposed. Firstly, the raw NIR data were pretreated by locally weighted scatterplot smoothing (LOWESS) and multiplication scatter correction (MSC). Then, FPCA was used to extract valuable information from the preprocessed NIR data. Then, a classifier was designed by using the least-squares support-vector machine (LS-SVM) to distinguish categories of edible fungi. Furthermore, the one-versus-one (OVO) strategy was included and the binary LS-SVM was extended to a multi-class classifier. The 166 samples of four varieties of fungi were used to validate the proposed method. The results show that the proposed method has great capability in near infrared spectra classification, and the average accurate of FPCA-LSSVM is 97.3% which is greater than that of PCA-LSSVM (93.5%).

Clinical trials and the origins of pharmaceutical fraud: Parke, Davis & Company, virtue epistemology, and the history of the fundamental antagonism

This paper describes one possible origin point for fraudulent behavior within the American pharmaceutical industry. We argue that during the late nineteenth century therapeutic reformers sought to promote both laboratory science and increasingly systematized forms of clinical experiment as a new basis for therapeutic knowledge. This process was intertwined with a transformation in the ethical framework in which medical science took place, one in which monopoly status was replaced by clinical utility as the primary arbiter of pharmaceutical legitimacy. This new framework fundamentally altered the set of epistemic virtues-a phrase we draw from the philosophical field of virtue epistemology-considered necessary to conduct reliable scientific inquiry regarding drugs. In doing so, it also made possible new forms of fraud in which newly emergent epistemic virtues were violated. To make this argument, we focus on the efforts of Francis E. Stewart and George S. Davis of Parke, Davis & Company. Therapeutic reformers within the pharmaceutical industry, such as Stewart and Davis, were an important part of the broader normative and epistemic transformation we describe in that they sought to promote laboratory science and systematized clinical trials toward the twin goals of improving pharmaceutical science and promoting their own commercial interests. Yet, as we suggest, Parke, Davis & Company also serves as an example of a company that violated the very norms that Stewart and Davis helped introduce. We thus seek to describe one possible origin point for the widespread fraudulent practices that now characterize the pharmaceutical industry. We also seek to describe an origin point for why we conceptualize such practices as fraudulent in the first place.

Computational Simulation of Benefit Fraud and Community Resilience in the Wake of Disaster

AbstractThe monetary assistance provided for disaster relief creates opportunities for fraudulent behavior. Historical records have shown that the loss of recovery funds due to improper and fraudul...

Behavior in cheating paradigms is linked to overall approval rates of crowdworkers

AbstractDishonest and fraudulent behavior poses a serious threat to both individuals and societies. Many studies investigating dishonesty rely on (one of) a few well‐established lab and online cheating paradigms. Quite surprisingly, though, the external validity of these paradigms has only been investigated in a small number of studies, raising the question of whether behavior in these paradigms is related to real‐life dishonesty or, more broadly, socially questionable behavior. Tackling this gap, we link observed behavior in two widely used cheating paradigms to approval rates on two crowdworking platforms (namely, Prolific and Amazon Mechanical Turk) using data from four studies (overall N = 5,183). Results indicate that lower approval rates are associated with higher proportions of dishonest individuals. Importantly, this relation also holds for crowdworkers who exceed commonly used thresholds for study inclusion. The results thus support the external validity of (two widely used) cheating paradigms. Further, the study identifies approval rates as a variable that explains dishonesty on crowdworking platforms.

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PROCUREMENT FRAUD: SEBUAH KAJIAN DARI PERSPEKTIF PERSEPSIAN AUDITOR INDEPENDEN PEMERINTAH

Procurement fraud is fraud that occurs in the public sector in the form of embezzlement, misappropriation of assets, and false explanations. This study aims to examine the factors that influence procurement fraud: a perspective study of perceived independent government auditors. The population in this study were all auditors at the BPK Office of the Republic of Bali Province Representative, while 40 people were selected as research objects. The sampling technique uses a purposive sampling method. Data were tested using validity test, reliability test, non response bias test, multicollinearity test, heteroscedasticity test, multiple regression analysis, hypothesis test and coefficient of determination. The results showed that the financial pressure variable had a positive and significant effect on procurement fraud. Weaknesses in procurement systems and procedures have a negative and significant effect on procurement fraud. The quality of the procurement committee has no significant effect on procurement fraud. Attitudes towards fraud behavior do not significantly influence procurement fraud. Subjective norms have a positive and significant effect on procurement fraud. The perceived behavioral control has no significant effect on procurement fraud.

Prediction of pellet quality through machine learning techniques and near-infrared spectroscopy

In recent years, pellet has received increasing attention among other biofuels due to its low storage costs and high combustion efficiency. The traceability of pellet quality along the entire supply chain is a critical issue, since fraudulent behaviours, such as the replacement with lower quality pellet, may both cause an economic damage and harm consumers’ health. Traditionally, pellet quality is evaluated through laboratory analysis, which is costly and time-consuming. To overcome these limitations, in this work we define a methodology for quick and low-cost evaluation of pellet quality, which may be used along the entire supply chain. The proposed technique is based on the classification of pellet spectra through machine learning techniques. Spectra are obtained by means of a near-infrared (NIR) spectrophotometer, which is a relatively cheap instrument of small dimensions (even portable) that is suitable for on-site analysis at any phase of the supply chain. We propose two different approaches, namely an automatic classification of pellet, which does not require laboratory analysis, and a semi-automatic approach, that increases the overall accuracy but requires laboratory analysis for uncertainly classified samples. We validate the methodology by performing several experiments on real-world data, by training different machine learning algorithms and evaluating the impact of several transformations introduced to reduce the scattering effect, which is a well-known issue related to NIR data.

NEVA: Visual Analytics to Identify Fraudulent Networks.

Trust‐ability, reputation, security and quality are the main concerns for public and private financial institutions. To detect fraudulent behaviour, several techniques are applied pursuing different goals. For well‐defined problems, analytical methods are applicable to examine the history of customer transactions. However, fraudulent behaviour is constantly changing, which results in ill‐defined problems. Furthermore, analysing the behaviour of individual customers is not sufficient to detect more complex structures such as networks of fraudulent actors. We propose NEVA (Network dEtection with Visual Analytics), a Visual Analytics exploration environment to support the analysis of customer networks in order to reduce false‐negative and false‐positive alarms of frauds. Multiple coordinated views allow for exploring complex relations and dependencies of the data. A guidance‐enriched component for network pattern generation, detection and filtering support exploring and analysing the relationships of nodes on different levels of complexity. In six expert interviews, we illustrate the applicability and usability of NEVA.

Effects of Career Horizon and Corporate Governance in China’s Construction Industry: Multilevel Study of Top Management Fraud

AbstractTo investigate the drivers of fraudulent behavior in the construction industry, this study focused on top managers and explored whether individual-level and firm-level characteristics would...

PHENOMENA BEHAVIOR FRAUD IN GOVERNMENT

This research is based on government civil state apparatus as the government’s front guard that reflects the healthy and strong government but the facts showed that there are cases of government doing fraudulent behavior from mild to severe. Also, it aims to reveal the phenomenon of fraud behavior of the civil apparatus. This is the preliminary research obtained from interviews and observation in the field by actively participating in every government activity. The result of the research shows that the mild cheating fraud behavior in each unit of the regional apparatus is handled by the superior of the agency and they only make a report of doing coaching to the employment agency and the human resource development. For the medium and heavy fraud behavior, the coaching is done by the employment agency and human resource development together with the inspectorate agency by making a coaching team. Coaching is done based on complaints from the number of Regional Work Unit (SKPD), community complaints, and monthly attendance monitoring. The phenomenon of fraud behavior in the government environment. Furthermore, the results of this study can act also as consideration matters to change the system, procedures, and policies to prevent fraud behavior and suppress the culture. For further researchers to make a comparison of methods and mix methods also find the factors that cause and prevent potential violations

Tracking Fraudulent and Low-Quality Display Impressions

Display advertising is traded in a complex market with multiple sides and intermediaries, where advertisers are exposed to several forms of potentially fraudulent behavior. Intermediaries often claim to implement measures to detect fraud but provide limited information about those measures. Advertisers are required to trust that self-regulation efforts effectively filter out low-quality ad impressions. In this article, we propose an approach for tracking key display impression metrics by embedding a light JavaScript code in the ad to collect the necessary information to help detect fraudulent activities. We explain these metrics using the campaign cost per thousand (CPT) and the number of impressions per publisher. We test the approach through six display ad campaigns. Our results provide a counterargument against the industry claim that it is effectively filtering out display fraud and show the utility of our approach for advertisers.

Computational Intelligent Approaches for Non-Technical Losses Management of Electricity

This paper presents an intelligent system for the detection of non-technical losses of electrical energy associated with the fraudulent behaviors of system users. This proposal has three stages: a non-supervised clustering of consumption profiles based on a hybrid algorithm between self-organizing maps (SOM) and genetic algorithms (GA). A second stage for demand forecasting is based on ARIMA (autoregressive integrated moving average) models corrected intelligently through neural networks (ANN). The final stage is a classifier based on random forests for fraudulent user detection. The proposed intelligent approach was trained and tested with real data from the Colombian Caribbean region, where the utility reports energy losses of around 18% of the total energy purchased by the company during the five last years. The results show an average overall performance of 82.9% in the detection process of fraudulent users, significantly increasing the effectiveness compared to the approaches (68%) previously applied by the utility in the region.

Determinants of Whistleblowing Intention of Employees in Universities: Evidence from Indonesia

Corruption in higher education institutions (HEI) is serious issue that has become a focus by many parties. The amount of state losses caused by fraudulent behavior in the management of university finances makes research related to whistleblowing at universities very urgent. Hence, this study aims to examine how perceived personal costs, perceived fraud seriousness, and attitude influence whistleblowing intention of university employees. This research was conducted in two universities in Manado, North Sulawesi, Indonesia. The research samples were permanent employees including lecturers and staffs. Data obtained by distributing questionnaires directly to the respondents. Hypothesis testing uses multiple regression analysis techniques. This study found that perceived personal costs have a negative effect on whistleblowing intention. Meanwhile, perceived fraud seriousness and attitude have a positive effect on whistleblowing intention. Discussion, implications and further research suggestions are presented in this paper.

Regulation and Supervision of Banks and Financial Institutions

Basel I, Basel II and Basel III Accord are important instruments to develop regulatory and supervisory principles and standards applicable for global community. Earlier, credit system was only the target of the authority but with the establishment of Basel Committee on Bank Supervision in Bank for International Settlement it has been developing and updating new and new standards, framework and guideline in regular interval of time. With the financial crisis of 2009-2011, it developed enhanced system of ‘Basel II Accord’ under ‘Basel III Accord’ which is in implementation process across the globe. In 2011, Basel Committee on Bank Supervision developed Core Principle of Bank Supervision which is implemented by the global community in their supervisory framework. Nepal also implements same principles for banking supervision. As the crisis occurred with economic depression and natural calamities like Corona Virus pandemic, it may need more resilient method for the banking operation because all the country of the world is badly affected by it. Still the loss of it cannot be determined. Economic activities are neutralized and banking activities are only limited in withdrawal of deposit. It can be worst situation than the past economic crisis of the history if it prolongs. It shows that it may establish new world economic order and new economic and banking principles and practices. In such case, time specific banking operation, regulation and supervision system with relief packages requires to develop. This paper aims to mention the role of Basel Accords in regulatory and supervisory practices of Nepali Central Bank. Additionally, as regulatory and supervisory perspective, Nepal follows onsite and offsite bank supervision method; under onsite approach, consolidated supervision, special supervision, targeted supervision and follow up supervision are used whereas under offsite supervision approach Cash Reserve Ratio (CRR), Statutory Liquidity Ratio (SLR), Deprived Sector Lending Ratio (DSLR), Capital Adequacy Ratio (CAR) and Credit to Core Capital and Deposit Ratio (CCD) are monitored. This approach is regularly changed and extended as per necessity of the market. Assurance of good governance, credit information system, credible banking transactions and fraudulent behavior control are the purpose of banks and financial institutions’ regulation and supervision.

Initial Coin Offerings: Risk or Opportunity?

Initial coin offerings (ICOs) are one of the several by-products in the world of the cryptocurrencies. Start-ups and existing businesses are turning to alternative sources of capital as opposed to classical channels like banks or venture capitalists. They can offer the inner value of their business by selling “tokens,” i.e., units of the chosen cryptocurrency, like a regular firm would do by means of an IPO. The investors, of course, hope for an increase in the value of the token in the short term, provided a solid and valid business idea typically described by the ICO issuers in a white paper. However, fraudulent activities perpetrated by unscrupulous actors are frequent and it would be crucial to highlight in advance clear signs of illegal money raising. In this paper, we employ statistical approaches to detect what characteristics of ICOs are significantly related to fraudulent behavior. We leverage a number of different variables like: entrepreneurial skills, Telegram chats, and relative sentiment for each ICO, type of business, issuing country, team characteristics. Through logistic regression, multinomial logistic regression, and text analysis, we are able to shed light on the riskiest ICOs.

Detection of Item Preknowledge Using Response Times.

Benefiting from item preknowledge is a major type of fraudulent behavior during educational assessments. This article suggests a new statistic that can be used for detecting the examinees who may have benefited from item preknowledge using their response times. The statistic quantifies the difference in speed between the compromised items and the non-compromised items of the examinees. The distribution of the statistic under the null hypothesis of no preknowledge is proved to be the standard normal distribution. A simulation study is used to evaluate the Type I error rate and power of the suggested statistic. A real data example demonstrates the usefulness of the new statistic that is found to provide information that is not provided by statistics based only on item scores.