Different Types Of Fraud Research Articles

Lessons learned from Dread darknet communities: How and why are fraudsters targeting the elderly to be victims or accomplices?

AbstractResearch SummaryWe examined darknet user discussions on the Dread forum to identify key themes and emerging topics in fraud planning, focusing additionally on elderly victimization. Using the conceptual framework of criminogenic learning to study the process of fraud planning in darknet communities of practice, we analyzed the content of original user posts (n = 818) and comments (n = 1365) collected from the Dread forum. We identified nine unique fraud categories, of which payments‐related fraud was the most‐discussed fraud category and accounted for 25% of original user posts. We further found our sampled forum content to be dominated by the theme of learning or knowledge sharing in eight of the nine fraud categories, which appeared in more than 44% of original user posts. Our content analysis revealed specific insights into why and how darknet forum users may target people, including the elderly subpopulation, for different types of fraud. Overall, our research demonstrates the diversity of opinion and knowledge sharing among darknet forum users in relation to planning and committing fraud against the elderly, views on who is a suitable target and why, and what veteran and aspiring fraudsters consider to be important information for success in fraud.Policy ImplicationsUtilized independently or as part of a multistage strategy of darknet data analysis, our research method can be used to monitor criminally active darknet forums for current and emerging themes in fraud against general populations and vulnerable subpopulations, such as the elderly, and to develop strategies to identify, disrupt, or destroy hubs of criminal planning and knowledge sharing. Our study additionally informs policy makers of certain elder‐specific vulnerabilities that might be addressed by more up‐to‐date elder cybercrime awareness campaigns and initiatives. Our findings also highlight the presence of insider threats that may inform discussions on how health and financial institutions can better regulate these cybersecurity risks.

Exploring spatiotemporal Dynamics and influencing factors of cyber-fraud: A quantile regression approach in Xiaoshan District, China

This study utilizes data on cyber-fraud crimes from the Public Security Bureau in Xiaoshan District for the year 2021 as its case study. It examines the spatiotemporal distribution of various types of cyber-fraud and investigates the influencing factors from social and built environments. Additionally, quantile regression models are employed to analyze the variation in the number of cases across different quantiles of the influencing factors. The study reveals significant differences in individual characteristics among victims of different types of fraud. Cyber-fraud occurrences exhibit distinct temporal patterns across various temporal scales, with significant differences in the duration of crimes among different fraud types. Cyber-fraud demonstrates significant spatial clustering, mainly concentrated in residential areas. The results of quantile regression indicate that cyber fraud is influenced by both the built environment and social environment, with noticeable variations in the coefficient of influence across different quantiles of the independent variables.

Overconfidence, short selling, and corporate fraud: Evidence from China

Using data on Chinese A-share listed firms from 2010 to 2020, this study employs a partial observable bivariate probit model and introduces fraud triangle theory to explain the mechanisms of overconfidence, short selling, and corporate fraud. Our findings show that overconfidence offers rationalization to investors and corporations, reduces fraud detection, and increases corporate incentives to commit fraud. Short selling promotes information transparency, increases fraud detection, and reduces the opportunities to commit fraud. Moreover, it moderates the relationship between overconfidence and corporate fraud. In addition, overconfidence and short selling affect different types of fraud (operational, executive, and information disclosure fraud). Furthermore, our results show heterogeneity among the ownership types. This study provides a theoretical basis for corporate fraud governance in China’s stock market.

Exploring Cyber Fraud within the South African Cybersecurity Legal Framework

All countries are globally struggling with the challenges cybercrime presents to the cybersecurity legal framework. Fraud is not a new crime and existed long before the internet. The internet provides a threat actor access to a lot of potential victims and the use of various threat vectors to gain access to personal information by means of social engineering. It is therefore not surprising that cyber fraud has become a serious threat which continues to escalate globally. In 2021, around $100 million was lost in Canada due to online fraud. The United Kingdom (UK) Finance indicated that cyber fraud costs consumers more than £1.2 billion in 2022. The South African (SA) Fraud Prevention Services noted a 356% surge in identity fraud between April 2022 and April 2023. The cybersecurity threat landscape is ever-evolving with the UK Finance warning that the number of cyber frauds could surge out of control as threat actors begin to incorporate the use of Artificial intelligence (AI) to make their operations far more sophisticated and not as easily detected. In 2023 the United States (US) also warned that the irresponsible use of AI could exacerbate societal harms such as fraud. Cyber fraud, also referred to as a “white collar” or commercial crime, is an umbrella term to describe the commission of different types of cyber fraud by means of the use of various threat vectors. The threat vector used to commit the different type of fraud is continuously evolving, such as the use of sophisticated phishing to quishing and deep fakes which are aimed at deceiving the recipient in sharing information. The information obtained from a data breach may be used to commit cyber fraud. Irrespective of the threat vector used to commit fraud, all types of fraud present with the same elements, namely a threat actor who unlawfully and intentionally deceives a victim to benefit and cause harm. The discussion focuses on cyber fraud in general and not a specific type of cyber fraud. The purpose of the discussion is to provide an overview of the challenges cyber fraud present to the South African cybersecurity legal landscape.

Fraud and corruption as an object of internal audit in corporate governance

Introduction. Fraud and corruption in the modern world is a pressing issue that significantly affects the functioning of the corporate sector and economic development in general. These phenomena generate serious losses for businesses, violate investor and consumer confidence, and undermine the effectiveness of the corporate governance system. Nevertheless, despite their importance, fraud and corruption remain complicated phenomena to detect and control. Therefore, internal audit is proving to be a key tool in combating these negative developments in corporate governance. It aims to identify, analyze and minimize risks related to fraud and corruption, as well as to improve the control and management system in accordance with best practices. The purpose of the paper is to analyze fraud and corruption as phenomena that affect corporate governance in order to identify their causes, forms, scope and consequences. Results. The paper examines the problem of fraud and corruption in organizations based on the complex interaction of economic, sociocultural and organizational factors. Different types of fraud and corruption such as financial manipulation, exploitation of conflict of interest, and misuse of resources are explored, as well as methods for identifying and analyzing potential fraud and corruption in organizations. Emphasized the importance of integrating these techniques into the internal control and audit system to ensure effective detection and prevention of fraud and corruption in organizations. The author presents the optimal principles that contribute to the effective role of internal audit in preventing fraud and corruption in organizations. Conclusions. Fraud and corruption, as an object of internal audit in corporate governance, are key aspects that require attention and systematic measures to detect, prevent and effectively control them. Detecting and eliminating fraud and corruption in organizations has a significant impact on business, including financial stability, reputation and efficiency. Solving these problems requires joint efforts on the part of all stakeholders, as well as the implementation of strategies and mechanisms aimed at counteracting and preventing the occurrence of such phenomena in the future.

Data Classification of Dark Web using SVM and S3VM

Abstract: There are many issues regarding the dark web structural Type. It also increases the number of cybercrimes like illegal trade, forums, Terrorist activity. By understanding online criminal’s actions are challenging because the data is available in a very great extent amount. In a recent day the Online crimes are increasing all over the world. The data related to different types of frauds and scams, such as phishing schemes, identity theft etc. The data and discussion related to the act of hacking (hacktivist) activities, this often involve political or social causes. In some parts of dark web might be used for anonymous communication and the losing of sensitive information to explore wrong doing by governments or corporations. But in some countries the dark web might be used as a means to access information and content that is hardly restricted. The primary focus of this research is to develop a hybrid classification model that combines the strengths of deep learning and natural language processing algorithms. The model leverages a curated dataset of Dark Web content, meticulously labeled by content category, ranging from illegal commerce to cyber threats. By extracting relevant features from the textual and visual components of the data, the model demonstrates superior accuracy in distinguishing between different content categories

FAKTOR-FAKTOR YANG MEMPENGARUHI KEMAMPUAN AUDITOR DALAM MENDETEKSI KECURANGAN

The ability of an auditor to detect fraud is no longer a kept secret. One of the auditor's abilities, and hence one auditor's qualities, is to detect fraud and explain abnormalities throughout the audit. This ability is supported by the auditor's understanding of the different types of fraud, their characteristics, and how to detect them. However, due to a variety of factors, many auditors fail to detect fraud. As a result, this study was conducted to empirically prove the influence of Red Flags, Time Pressure, Professional Skepticism, Competence, Independence, and Professionalism. The population in this study is the entire target population of BPK Representatives of Lampung Province auditors. Saturation sampling to obtain a sample of 48 questionnaires from all those distributed, with 35 respondents responding. The analytical method used was descriptive analysis using the IBM SPSS Statistics 26 application. The findings of this study show that Red Flags, Professional Skepticism, Competence, Independence, and Professionalism all have a positive and sig influence. On the other hand, the results of the Time Pressure variable have no positive and insignificant effect on the auditor's ability to detect fraud.

Insider employee-led cyber fraud (IECF) in Indian banks: from identification to sustainable mitigation planning

ABSTRACT This paper explores the different insider employee-led cyber frauds (IECF) based on the recent large-scale fraud events of prominent Indian banking institutions. Examining the different types of fraud and appropriate control measures will protect the banking industry from fraudsters. In this study, we identify and classify Cyber Fraud (CF), map the severity of the fraud on a scale of priority, test the mitigation effectiveness, and propose optimal mitigation measures. The identification and classification of CF losses were based on a literature review and focus group discussions with risk and vigilance officers and cyber cell experts. The CF was analyzed using secondary data. We predicted and prioritized CF based on machine learning-derived Random Forest (RF). An efficient fraud mitigation model was developed based on an offender-victim-centric approach. Mitigation is advised both before and after fraud occurs. Through the findings of this research, banks and fraud investigators can prevent CF by detecting it quickly and controlling it on time. This study proposes a structured, sustainable CF mitigation plan that protects banks, employees, regulators, customers, and the economy, thus saving time, resources, and money. Further, these mitigation measures will improve the reputation of the Indian banking industry and ensure its survival.

Machine learning-based approach for designing and implementing a collaborative fraud detection model through CDR and traffic analysis

Fraud in telecommunications networks is a constantly growing phenomenon that causes enormous financial losses for both the individual user and the telecommunications operators. We can denote many researchers who have proposed various approaches to provide a solution to this problem, but still need to be improve to ensure the efficiency. Detecting fraud is difficult and, it's no surprise that many frauds schemes have serious limitations. Different types of fraud may require different systems, each with different procedures, parameter adjustments, database interfaces, and case management tools and capabilities. This article uses the K-Means algorithm to handle fraud detection based on Call Detail Record (CDR) and traffic analysis in a telecommunication industry. Our algorithm consists to compare traffic and CDR generated in the network and check if there is abnormal behavior and if yes, our model is used to confirm if users suspecting of fraud are really fraudster or not. To build our model we used real word CDR data collected in November 2021. Our model associates the Differential Privacy model to encrypt users' personal information, and the k-means algorithm to group users into different clusters. Those clusters represent non fraud users having similar characteristics based on criteria used to build the model. Users having abnormal behavior that can be assimilated to fraudsters are those who are far from the different clusters center. Thanks to a representation in a plan, we better visualize user’s behavior. We validated our model by evaluating our segmentation method. The interpretation of the results shows sufficiently that our approach allows to obtain better results. Our approach can be used by all telecommunications operator to reduce the impact of fraud on internet services.

Nuclear magnetic resonance spectroscopy in extra virgin olive oil authentication.

Extra virgin olive oil (EVOO) is a high-quality product that has become one of the stars in the food fraud context in recent years. EVOO can encounter different types of fraud, from adulteration with cheaper oils to mislabeling, and for this reason, the assessment of its authenticity and traceability can be challenging. There are several officially recognized analytical methods for its authentication, but they are not able to unambiguously trace the geographical and botanical origin of EVOOs. The application of nuclear magnetic resonance (NMR) spectroscopy to EVOO is reviewed here as a reliable and rapid tool to verify different aspects of its adulteration, such as undeclared blends with cheaper oils and cultivar and geographical origin mislabeling. This technique makes it possible to use both targeted and untargeted approaches and to determine the olive oil metabolomic profile and the quantification of its constituents.

Credit Card Fraud Detection project

Abstract: For some time, there has been a strong interest in the ethics of banking (Molyneaux, 2007; George, 1992), as well as the moral complexity of fraudulent behavior (Clarke, 1994). Fraud means obtaining services/goods and/or money by unethical means, and is a growing problem all over the world nowadays. Fraud deals with cases involving criminal purposes that, mostly, are difficult to identify. Credit cards are one of the most famous targets of fraud but not the only one; fraud can occur with any type of credit products, such as personal loans, home loans, and retail. Furthermore, the face of fraud has changed dramatically during the last few decades as technologies have changed and developed. A critical task to help businesses and financial institutions including banks is to take steps to prevent fraud and to deal with it efficiently and effectively, when it does happen (Anderson, 2007). Anderson (2007) has identified and explained the different types of fraud, which are as many and varied as the financial institution’s products and technologies, such as Transaction products: credit and debit cards and checks, Relationship to accounts first, second and third parties, Business processes: application and transaction, Manner and timing short versus long term, Identify misrepresentation: embellishment, theft and fabrication, Handling of transaction: lost or stolen, not received, skimming and at hand, Utilization counterfeit, not present, altered or unaltered, Technologies ATM and Internet. Solutions for integrating sequential information in the feature set exist in the literature. The predominant one consists in creating a set of features which are descriptive statistics obtained by aggregating the sequences of transactions of the cardholders (sum of amount, count of transactions, location from where the payment is being made etc..). We used this method as a benchmark feature engineering method for credit card fraud detection. However, this feature engineering strategy raised several research questions. First of all, we assumed that these descriptive statistics cannot fully describe the sequential properties of fraud and genuine patterns and that modelling the sequences of transactions could be beneficial for fraud detection. Moreover, the creation of these aggregated features is guided by expert knowledge whereas sequence modelling could be automated thanks to the class labels available for past transactions. Finally, the aggregated features are point estimates that may be complemented by a multi-perspective univariate description of the transaction context. We proposed a multi-perspective HMM-based automated feature engineering strategy in order to incorporate a broad spectrum of sequential information in the transactions feature sets. In fact, we model the genuine and fraudulent behaviors of the merchants and the card-holders according to two univariate features: the country from where the payment is being made and the amount of each of the transactions being made. Moreover, the HMMbased features are created in a supervised way and therefore lower the need of expert knowledge for the creation of the fraud detection system. In the end, our multiple perspectives HMM-based approach offers automated feature engineering to model temporal correlations so as to complement and possibly supplement the use of transaction aggregation strategies in order to improve the effectiveness of the classification task. Experiments conducted on a large real world credit card transaction dataset (46 million transactions from belgium card-holders between March and May 2015) have shown that the proposed HMMbased feature engineering allows for an increase in the detection of fraudulent transactions when combined with the state-ofthe-art expert-based feature engineering strategy for credit card fraud detection. To conclude, this work leads to a better understanding of what can be considered contextual knowledge for a credit card fraud detection task and how to include it in the classification task in order to get an increase in fraud detection. The method proposed can be extended to any supervised task with sequential datasets. The main aims are, firstly, to identify the different types of credit card fraud, and, secondly, to review alternative techniques that have been used in fraud detection. Indeed, transaction products, including credit cards, are the most vulnerable to fraud. On the other hand, other products such as personal loans and retail are also at risk, and have serious ethical conflicts. Keywords: Behavior and Location Analysis (BLA); Fraud Detection System (FDS); Automated Teller Machine (ATM); Credit Card Fraud Detection; DB: Database.

Fabricating insurance subject matter and defrauding insurance money: a civil wrong or a criminal offence?

ABSTRACT Insurance fraud is a serious problem and is dealt with mainly by the mechanisms of civil liability and criminal punishment in China. This article critically examines these mechanisms and their application to different types of fraud, identifies the existing and potential problems with them, and also propose solutions to the problems with reference to the English common law fraudulent claims rule and the Fraud Act 2006 (UK). Chinese Criminal Law provides a unique type of insurance fraud, namely, ‘fabricate insurance subject matter and defraud insurance money’, but no definition of this type of fraud is provided in the Law, this causes judicial difficulty in the trial of the fraud cases. This type of fraud is committed at two stages: ‘fabricate insurance subject matter’ at the stage of conclusion of the contract and ‘defraud insurance money’ at the stage of making claims. It argues that the phrase of ‘fabricate insurance subject matter’ should be construed in a narrow sense that it only refers to the fraud where a non-existent insurance subject matter is fabricated into an existent one; while fabrication of the features or characters of the insurance subject matter should not be taken as the fraud of ‘fabricate insurance subject matter’. This article examines the circumstances under which this type of fraud may be dealt with by civil law or criminal law and puts forward guidelines for the determination of this type of fraud and for the correct application of civil remedies or criminal sanction for the fraud.

МОЖЛИВОСТІ ВИКОРИСТАННЯ ТЕХНОЛОГІЙ БЛОКЧЕЙНУ ДЛЯ ЗАХИСТУ ВІД ШАХРАЙСТВА

The article examines the nature and main types of fraud based on the classification of the Association of Certified Fraud Experts (ACFE), which proposes the division of fraud into three groups: corruption, fraud in financial reporting and misappropriation of assets. The purpose of the article is to conduct a comparative analysis of economic losses from fraud and provide suggestions for reducing them through the use of blockchain technology. The research methodology is based on the use of Report to the Nation data and the results of other surveys presented on the ACFE website for a comparative analysis of types of economic fraud by volume, period, territorial affiliation and counteraction. Based on a report for the nation prepared by ACFE, it was found that the company's largest monthly losses are caused by fraud with financial statements, which lasts an average of 18 months. The frequency of cases of different types of fraud depending on the industry was analyzed and it was found that the most common companies in each industry are corrupt. The 8 most risky departments with different types of fraud were identified, and it was found that corruption is also the most common in each department. The most common schemes of professional fraud by region were studied, which showed that the most common schemes of professional fraud in all countries are corruption, with the highest level in South Asia. It has been established that tip, internal audit and management review are used to detect company fraud in all regions. A study of the most common means of control against fraud showed that the most effective of them are the External Audit of Financial Statements and the Code of Conduct. It has been established that in most countries of the region the Code of Conduct and the External Audit of Financial Statements are used as anti-fraud tools. It should be noted that a large number of companies use proactive monitoring / analysis of data, of which blockchain technology is an integral part. The main stages of creation and use of blockchain technologies for the financial operations of the company are offered, which will allow more effective control over the fight against fraud.

Identity Management Reform and Fraud Prevention in the Nigerian Banking Industry

This paper assesses the effect ofidentity management reform, namely the Bank verification number (BVN) policy on fraud prevention in the Nigerian banking industry. Using secondary data obtained from annual reports of Nigerian Deposit Insurance Corporation (NDIC) from 2011 to 2018, the study employed descriptive method to analyze trend in fraud variables before and after introduction of the policy and independent t-test to test the hypotheses in the study. Findings revealed that there was an initial decrease in number of staff involved and total amount involved in fraud in the two years following BVN introduction, but which showed increases thereafter.A similar trend was revealed in various fraud types with internet banking fraud showing significant increases in frequency of cases. The results from the t-tests revealed that theBVN policy had no significant impact on fraud prevention within the period under study. It was recommended that the banking public be educated on the different types of fraud and how to protect their personal details from getting into wrong hands. There is also the need to beef up security by improving on protocols required to carry out bank transactions particularly in the area of internet banking. It was also suggested that all bank account numbers be linked to the National Identity Number (NIN) immediately in line with proposals made by the Federal Government on identity management.

Bank’s battle against insider frauds ignitors and mitigators: an emerging nation experience

Purpose Banks are exposed to many challenges to name a few i.e. growing market competition, political environment, market forces of demand and supply, technological changes, frauds and poor management. The banking sector devasted experiences of fraud have impacted all facets of the Banking, Financial Services and Insurance. In continuation, this study aims to revolve around themes of different types of frauds, especially insider frauds that have gained mainstream attention in recent major value fraud events with prominent Indian banks. This study will identify the types and drivers of insider frauds. Design/methodology/approach The methodology opted for the study is through confidential primary survey and focused group discussion with risk officers of banks who are associated with Indian banks for more than three years, further to understand the relation between type of Insider frauds and originating drivers were paired based on the principal component analysis. Findings Finally, the paper concludes with the conceptual mitigation framework for different types of insider fraud and driver pairs within the scope of this paper. This paper thought will support policymakers of the Indian banking system to create a more robust environment within the banking system via timely detection of frauds so that up to an extent it can be squared before it appears. Originality/value The study is innovative in the area of banks’ internal fraud management, where original data collected through a primary survey contributes to the conclusion of fraud management for various Indian banks.

Confidentiality and scam in the internet

The purpose of the work is to consider the theoretical and practical aspects of fraud in the Internet sphere and on this basis to identify ways to ensure the confidentiality and cybersecurity of private users and commercial organizations. The methodological basis of the work is the use of general and special methods of scientific knowledge. Methods of combining analysis and synthesis, induction and deduction have been used to identify different types of fraud in the Internet. Generalization methods, logical and empirical, were used in determining the directions of development of the national cyber defense system and ensuring confidentiality. The main results of the work: The most common methods of fraud with the use of bank payment cards are identified, among which: a fake poll on social networks with a prize draw; a phone call to obtain classified information; SIM card replacement for access to online banking; online payments on unsecured sites; phishing; copying card data when handed over; unsecured WI-Fi networks; computers in public places; skimming for card data theft; unauthorized micropayments; ATM fraud; use of malicious programs (viruses), fake sites in order to compromise the details of electronic payment instruments and/or logins/passwords for access to Internet/mobile banking systems; dissemination (sale, dissemination) of information on compromised data; terminal network fraud; fraud in remote service systems; social engineering. Basic security rules are defined to prevent fraud. The experience of European countries in the field of cybersecurity is analyzed. The directions of adaptation of the current legislation on cybersecurity to the EU standards are outlined and the directions of development of the national system of cybersecurity are defined. The practical significance of the results is to deepen the understanding of the nature and mechanism of various types of fraud in the Internet. The recommendations proposed in the paper can form a methodological and theoretical basis for the development of economic policy of the state to ensure the confidentiality and cybersecurity of private users and commercial organizations. Conclusions. The state should establish an effective oversight body in the field of personal data protection, but security measures and online restrictions should comply with international standards. The use of encryption should not be prohibited at the legislative level, as such restrictions reduce the ability of citizens to protect themselves from illegal intrusions into privacy. In addition, the state policy in the Internet should be aimed at promoting the development and operation of secure Internet technologies and the formation of mechanisms to protect against services and protocols that threaten the technical functioning of the Internet from viruses, phishing and more.

Initial coin offerings, information disclosure, and fraud

We study the extent of fraud in initial coin offerings (ICOs), and whether information disclosure prior to the issuance predicts fraud. We document different types of fraud, and that fraudulent ICOs are on average much larger than the sample average. Issuers who disclose their code on GitHub are more likely to be targeted by phishing and hacker activities, which suggests that there are risks related to disclosing the code. Generally, we find it extremely difficult to predict fraud with the information available at the time of issuance. This calls for the need to install a third party that certifies the quality of the issuers, such as specialized platforms, or the engagement of institutional investors and venture capital funds that can perform a due diligence and thus verify the quality of the project.

Explainable anomaly detection for procurement fraud identification—lessons from practical deployments

AbstractThis article reports the results of our work to construct a system for the detection of fraudulent behavior in procurement transactions. To solve the problem, we model different types of fraud via separate statistical indicators. We propose a formalized framework to describe the severity of fraud in a unified way regardless of underlying fraud mechanics. Subsequently, we leverage this concept to build indicator ensembles that collect evidence from multiple indicators and deliver an interpretable per transaction score to the procurement audit officer. As a case study, we overview 48 such fraud indicators constructed for our client and describe two examples in detail showing how our formal definitions can be transformed into a practical implementation. The presented results include experiments with all indicators on data covering four years of procurement activity with approximately 216,000 transactions coming from a large government organization in Singapore. The final evaluation of our system shows 67.1% precision in detecting suspicious transactions. The article describes how outcome of our work helped to effectively cope with the problem of anomaly detection explainability and the lessons learned from integrating this solution to operational practices of a procurement department.

Online Fraud Victimization in China: A Case Study of Baidu Tieba

ABSTRACT When it comes to online populations and markets, China has some of the largest in the world. As a result, Chinese cybercriminals have more opportunities to target and access victims. While extant research in Western countries has examined online fraud victimization and offenses in virtual communities, a relatively small body of research on these phenomena has been conducted in non-Western societies. This study attempts to address this gap by analyzing online fraud victimization in Chinese online communities. Routine activity theory is applied to understand the patterns and dynamics of victimization. Data were collected from Baidu Tieba (a Chinese version of Craigslist), a prominent Chinese online platform for reporting victimization. This study highlights the range of services, types, and methods along which victimization occurs. The results, which reflect China’s rapid pace of technological development, show that different types of fraud are perpetrated online and that victimization methods are associated with particular types of media. This study also identifies implications for China and other countries where similar crimes and instances in cyberspace occur.

To Whom Do Victims of Mass-Market Consumer Fraud Complain?

Utilizing data from surveys of mass-market consumer fraud sponsored by the Federal Trade Commission in 2005, 2011, and 2017, this paper explores whether victims of such mass-market consumer frauds complain to anyone beyond their families and friends about being victimized, and if they do complain, to whom they complain. It also explores whether victims with different demographic characteristics are more or less likely to complain. In about 45 percent of instances, victims complained to someone beyond their family and friends. This might have been the seller or manufacturer of the fraudulent product of service; a provider of payment services such as a credit card company, a bank or another payment service; a Better Business Bureau; or a government agency. This figure is stable across the three surveys included in this analysis. While there is little, if any, variation in complaint rates across the three surveys, there is considerable variation in the likelihood that victims of different types of frauds complained. Those who were billed for an item that they had never agreed to purchase were the most likely to report having complained – with 61 percent of those victims indicating that they had complained to at least one party. Fifty-eight percent of those who paid for a product or service that they never received reported having complained. For victims who experienced other types of frauds, no more than 40 percent complained. Of those who purchased fraudulent credit card insurance or a fraudulent computer repair, less than 20 percent complained. Not surprisingly, complaints were most frequently directed at someone directly involved in the transaction – a seller or a manufacturer. Thirty percent of victims reported having complained either to a seller or to a manufacturer. About 12 percent complained to a credit card company, a bank, or some other payment service provider. Less than 3 percent of victims complained to a government entity. Somewhat more than half of these – 1.5 percent of victims – complained to a local authority – the local police or a local consumer agency. Less than 1 percent complained to a state Attorney General or other state authority or to a federal agency. Just over 2 percent of victims reported having complained to a Better Business Bureau. Together, 4.8 percent of victims complained to a BBB or to a government agency. To whom a complaint is directed varies somewhat with the type of problem being considered. While a seller or manufacturer is the most frequent recipient of complaints for most of the types of fraud considered here, the percentage of victims who complained to a seller or manufacturer ranged from 43 percent among victims who paid for an item that they never received to 6 percent for victims of fraudulent computer repair offerings. The percentage of complainants who complained to a governmental entity or the BBB likewise varied with the type of fraud – with around 20 percent of victims of a debt-relief fraud complaining to one of these entities, while less than 1 percent of those who purchased a fraudulent weight-loss product did so. Rates of complaining differ somewhat depending on the demographic characteristics of the consumer who was reporting on the experience. Consumers who were more educated were more likely to complain about their experiences. Looking at race and ethnicity, Latinos were less likely to complain than were those in other racial and ethnic groups, though overall the differences across racial and ethnic groups are not statistically significant. There was no statistically significant relationship between the age of a victim and likelihood of the victim complaining.