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The purpose of this study is to examine the effect of micro-level place on identity theft victimization. This study uses the 2016 Identity Theft Supplement (ITS) to investigate whether aspects of an individual’s residence affect their likelihood of becoming identity theft victims.

The authors conduct logistic regressions of whether a respondent was an identity theft victim in the past year using the following variables as key predictors: number of housing units in a residence, whether the respondent operates a business out of their residence and if residence access is restricted.

The results suggest that location influences the likelihood of identity theft to a modest degree though some aspects of location (possibly those related to rewards perceptions) may be more relevant than others. Meanwhile, though location may influence initial target selection, whether someone is victimized may be more dependent on factors such as personal behavior.

To the best of the authors’ knowledge, this manuscript represents one of the first investigations into the relationship between microlevel place and the incidence of identity theft. Furthermore, it provides evidence that one does exist which bears further inquiry.

One of the most important Information Security (IS) concerns nowadays is data theft or data leakage. To mitigate this type of risk, organisations use a solid infrastructure and deploy multiple layers of security protection technology and protocols such as firewalls, VPNs and IPsec VPN. However, these technologies do not guarantee data protection, and especially from insiders. Insider threat is a critical risk that can cause harm to the organisation through data theft. The main purpose of this study was to investigate and identify the threats related to data theft caused by insiders in organisations and explore the efforts made by them to control data leakage.

The study proposed a conceptual model to protect organisations’ data by preventing data theft by malicious insiders. The researchers conducted a comprehensive literature review to achieve the objectives of this study. The collection of the data for this study is based on earlier studies conducted by several researchers from January 2011 to December 2020. All the selected literature is from journal articles, conference articles and conference proceedings using various databases.

The study revealed three main findings: first, the main risks inherent in data theft are financial fraud, intellectual property theft, and sabotage of IT infrastructure. Second, there are still some organisations that are not considering data theft by insiders as being a severe risk that should be well controlled. Lastly, the main factors motivating the insiders to perform data leakage activities are financial gain, lack of fairness and justice in the workplace, the psychology or characteristics of the insiders, new technologies, lack of education and awareness and lack of management tools for understanding insider threats.

The study provides a holistic view of data theft by insiders, focusing on the problem from an organisational point of view. Organisations can therefore take into consideration our recommendations to reduce the risks of data leakage by their employees.

Familiar identity theft, which occurs when an individual known to a victim steals his/her identity, is a common problem in the USA. The purpose of this study was to understand familiar identity theft victims’ reporting behaviors using Black's (1976) theory of law as a conceptual framework.

Data were obtained from the 2012, 2014, 2016 and 2018 administrations of the National Crime Victimization Survey – Identity Theft Supplement. A series of cross-tabulations were conducted to examine the relationship between reporting behaviors and age, minority, gender, income, marital status and education. Fisher’s exact test was used to interpret the findings.

Key findings include older familiar identity theft victims who personally lost greater sums of money because of identity theft victimization were more likely to report to law enforcement than younger familiar identity theft victims who personally lost less money. Married familiar identity theft victims were less likely to report to law enforcement than those who were not married.

This study extends the work of Golladay (2017) to explore the reporting behaviors of a population of identity theft victims that have been largely overlooked in empirical literature.

This paper aims to propose a machine learning approach-based power theft detection using Garra Rufa Fish (GRF) optimization. Here, the analyzing of power theft is an important part to reduce the financial loss and protect the electricity from fraudulent users.

In this section, a new method is implemented to reduce the power theft in transmission lines and utility grids. The detection of power theft using smart meter with reliable manner can be achieved by the help of GRF algorithm.

The loss of power due to non-technical loss is small by using this proposed algorithm. It provides some benefits like increased predicting capacity, less complexity, high speed and high reliable output. The result is analyzed using MATLAB/Simulink platform. The result is compared with an existing method. According to the comparison result, the proposed method provides the good performance than existing method.

The proposed method gives good results of comparison than those of the other techniques and has an ability to overcome the associated problems.

The fraud landscape for FinTech industry has increased over the past few years, certainly during the time of COVID-19, FinTech market reported rapid growth in the fraud cases (World Bank, 2020). Taking the consideration, the paper has qualitatively understood the loopholes of the FinTech industry and designed a conceptual model declaring “Identity Theft” as the major and the common fraud type in this industry. The paper is divided in two phases. The first phase discusses about the evolution of FinTech industry, the second phase discusses “Identity Theft” as the common fraud type in FinTech Industry and suggests solutions to prevent “Identity Theft” frauds. This study aims to serve as a guide for subsequent investigations into the FinTech sector and add to the body of knowledge regarding fraud detection and prevention. This study would also help organisations and regulators raise their professional standards in relation to the global fraud scene.

This paper revisits the literature to understand the evolution of FinTech Industry and the types of FinTech solutions. The authors argue that traditional models must be modernised to keep up with the current trends in the rapidly increasing number and severity of fraud incidents and however introduces the conceptual model of the common fraud type in FinTech Industry. The research also develops evidences based on theoretical underpinnings to enhance the comprehension of the key fraud-causing elements.

The authors have identified the most common fraud type in the FinTech Industry which is “Identity Theft” and supports the study with profusion of literature. “Identity theft” and various types of fraud continue to outbreak customers and industries similar in 2021, leaving several to wonder what could be the scenario in 2022 and coming years ahead (IBS Inteligence, 2022). “Identify theft” has been identified as one the common fraud schemes to defraud individuals as per the Association of Certified Fraud Examiners. There is a need for many of the FinTech organisations to create preventive measures to combat such fraud scheme. The authors suggest some preventive techniques to prevent corporate frauds in the FinTech industry.

This study identifies the evolution of FinTech industry, major evidences of Identity Thefts and some preventive suggestions to combat identity theft frauds which requires practical approach in FinTech Industry. Further, this study is based out of qualitative data, the study can be modified with statistical data and can be measured with the quantitative results.

This study would also help organisations and regulators raise their professional standards in relation to the global fraud scene.

This study will serve as a guide for subsequent investigations into the FinTech sector and add to the body of knowledge regarding fraud detection and prevention.

This study presents evidence for the most prevalent fraud scheme in the FinTech sector and proposes that it serve as a theoretical standard for all ensuing comparison.

The incidents of hotel theft constitute a significant cause of concern for the hotel industry. Such incidents result in substantial financial implications, inventory management issues and complications in finding exact replacements. This study, therefore, investigates customer stealing practices in Indian hotel industry.

A structured email interview was conducted with twenty-five senior hotel managers. The data were analyzed by adopting a coding technique using inductive content analysis.

The results were discussed under seven headings-extent of such stealing incidents, financial consequences of such practices, strategies to prevent such instances and, finally, how to deal with customers when caught stealing.

This study highlighted themes related to the profile of customers involved in stealing practices, motives, consequences and strategies required to manage such customers. Future studies can focus on restaurants, airlines, airports and tourist attractions to identify strategies and best practices for preventing such practices.

The study's findings have tremendous potential for the hospitality industry. Dealing with customers’ stealing practices is a very sensitive issue. Furthermore, hotels bear lots of expenses if the policy for tackling the problem still needs to be implemented. Furthermore, if not handled professionally, a lack of effective guidelines can cause embarrassment for managers.

The study has the potential to raise awareness among the members of society to be more responsible toward hotel property.

This study extends to the limited literature on hotel guests' theft. The comprehensive analysis of the themes generated from an interview with the senior managers of the hotel industry provides a unique insight into the nature of the problem. The solutions offered in this study are an original contribution to the literature.

In Nigeria, insecurity has been breeding very rapidly given the Nigerian economic conditions in the recent past. Insecurity exposes enterprise development and survival to a serious threat. It has serious effects on lives and properties, obstructs business activities and discourages local and foreign investors, which in turn militate against Nigeria’s overall economic growth and development. This rising wave of insecurity has assumed an unsafe facet to enterprise development and its subsequent survival, hence, if unchecked, it can threaten the overall communal existence of the country as one entity. The purpose of this study is therefore, to examine the impact of insecurity on enterprise development in Nigeria.

This study used the most recent Nigeria Enterprise Survey data (2014) and applied multi-nomial logistic regression model to examine the impact of insecurity on enterprise development in Nigeria.

It was found among others that all the captured insecurity variables in this study have negative significant impact on enterprise development and as such significantly retards enterprise growth and development except for corruption and availability of strong, fair and impartial legal system (comparing partnership and limited partnership enterprise to the sole proprietorship), which were found to have positive impact on enterprise development in Nigeria.

This study therefore recommended among others that government at all levels – federal, state and local – should try harder to live up to its primary constitutional function of providing adequate security of lives and property to its citizenry.

There is no known study that has investigated the impact of insecurity on enterprise development in Nigeria. There is dearth of literature in the study area, hence this study enormously contributes to the growing literature on insecurity and enterprise development.

This research examines the relationship between the timeliness in announcing the discovery of a data breach and consumer trust in an e-commerce company, as well as later trust-rebuilding efforts taken by the company to compensate users impacted by the breach.

A survey experiment was used to examine the effect of both trust-reducing events (announced data breaches) and trust-enhancing events (provision of identity theft protection and credit monitoring) on consumer trust. The timeliness of the breach announcement by an e-commerce company was manipulated between two randomly assigned groups of subjects; one group viewed an announcement of the breach immediately upon its discovery, and the other viewed an announcement made two months after the breach was discovered. Consumer trust was measured before the breach, after the breach was announced, and finally, after the announcement of data protection.

The results suggest that companies that delay a data breach announcement are likely to suffer a larger drop in consumer trust than those that immediately disclose the data breach. The results also suggest that trust can be repaired by providing data protection. However, even after providing identity theft protection and credit monitoring, companies that fail to promptly disclose a breach have lower repaired trust than companies that promptly disclose.

This study contributes to the literature on e-commerce trust by examining how a company's forthrightness in reporting a data breach impacts user trust at the time of the disclosure of the data breach and after subsequent efforts to repair trust.

This study expands the empirical understanding of financial fraud victims and the consequences that emerge as a result of financial fraud victimization. In addition, this study aims to assess the impact of the unique role victims play in financial fraud and the impact self-identifying as a victim has on the negative consequences they experience.

Data from the Supplemental Fraud Survey to the National Crime Victimization Survey are used to assess the negative consequences of financial fraud victimization.

Results suggest that victims of financial fraud experience increased distress and financial complications following their victimization experience. In addition, self-reported victim status is found to significantly increase a respondent’s likelihood of reporting emotional distress and financial complications. Implications for research, theory and policy are discussed.

While empirical studies on the consequences of identity theft victimization have been increasing in recent years, financial fraud victimization remains understudied. Given the victim involvement in financial fraud, the consideration of financial fraud independent of identity theft fraud is vital.

The purpose is to understand how farmers in rural American communities perceive crime, safety and policing.

An online survey, adapted from a version used in Victoria, Australia (Harkness, 2017), was modified and administered through social media and farming organizations throughout three US states. The survey covers topics relating to crime and victimization, feelings of safety or fear in rural areas, policing practices and trust in police in their areas and any crime prevention practices that respondents use.

With nearly 1,200 respondents and four scales investigated, results indicate that those respondents with more favorable views of law enforcement and the criminal justice system had the highest fear of crime, those who had been prior victims of crime had a higher fear of crime than those who did not, those with higher community involvement had higher fear of crime, and those from Nebraska compared to Colorado had higher fear of crime.

A better understanding of the agricultural community’s perceptions of crime, safety and policing will aid law enforcement in community policing efforts and in farm crime investigation and prevention. Limitations of the study, including the distribution method will be discussed.

Farm- and agriculture-related crimes have serious financial and emotional consequences for producers and local economies. Stereotypes about rural areas being “safe with no crime” are still prevalent. Rural American farmers’ perceptions of crime, safety and police are largely absent from the literature and are important for improving farm crime prevention.