One of the most severe threats to revenue and quality of service in telecom providers is fraud. The advent of new technologies has provided fraudsters new techniques to commit fraud. SIM box fraud is one of such fraud that has emerged with the use of VOIP technologies. In this work, a total of nine features found to be useful in identifying SIM box fraud subscriber are derived from the attribut...

The ubiquitous cases of abnormal transactions with intent to defraud is a global phenomenon. An architecture that enhances fraud detection using a radial basis function network was designed using a supervised data mining technique― radial basis function (RBF) network, interpolation approximation method. Several base models were thus created, and in turn used in aggregation to select the optimum...

SIM box fraud is classified as one of the dominant types of fraud instead of subscription and superimposed types of fraud. This fraud activity has been increasing dramatically each year due to the new modern technologies and the global superhighways of communication, resulting the decreasing of the revenue and quality of service in telecommunication providers especially in Africa and Asia. This...

We estimate what percentage of firms engage in fraud and the economic cost of fraud. Our estimates are based on detected frauds, and frauds that we infer are started but are not caught. To identify the ‘iceberg’ of undetected fraud we take advantage of an exogenous shock to the incentives for fraud detection: Arthur Andersen’s demise, which forces companies to change auditors. By assuming that ...

The rapid transition to card payments has sparked a search for effective countermeasures to those who exploit card payment security vulnerabilities to commit payment fraud. A review of these vulnerabilities finds that they are tied together by an information-intensive payment approval system. Especially damaging are large data breaches, which are often the result of criminals gathering informat...

The paper presents fraud detection method to predict and analyze fraud patterns from data. To generate classifiers, we apply the Naïve Bayesian Classification, and Decision Tree-Based algorithms. A brief description of the algorithm is provided along with its application in detecting fraud. The same data is used for both the techniques. We analyze and interpret the classifier predictions. The m...

The quintessential crime of the information age is identity theft, the malicious use of personal identifying data. In this paper we model “identity” and its use in credit transactions. Various types of identity theft occur in equilibrium, including “new account fraud,” “existing account fraud,” and “friendly fraud.” The equilibrium incidence of identity theft represents a tradeoff between a des...

This study examines the market valuation of accounting earnings during the period before it is publicly revealed that the earnings are fraudulent. Using both cross-sectional and time-series valuation models, we first find that the market accords less weight to earnings when the accounting numbers are fraudulent. We also show that the market better anticipates the presence of fraud when there is...

A detailed review of all 2,047 biomedical and life-science research articles indexed by PubMed as retracted on May 3, 2012 revealed that only 21.3% of retractions were attributable to error. In contrast, 67.4% of retractions were attributable to misconduct, including fraud or suspected fraud (43.4%), duplicate publication (14.2%), and plagiarism (9.8%). Incomplete, uninformative or misleading r...

The paper proposes a linguistics-based text mining approach to demonstrate the process of extracting financial concepts from the Security Exchange Commission (SEC) litigation releases (LR). The proposed approach presents the extracted information as a knowledge base to be used in market monitoring surveillance systems. Also, it facilitates users’ acquisition, maintenance and access to financial...