In parallel to the increase in the number of credit card transactions, the financial losses due to fraud have also increased. Thus, the popularity of credit card fraud detection has been increased both for academicians and banks. Many supervised learning methods were introduced in credit card fraud literature some of which bears quite complex algorithms. As compared to complex algorithms which ...

Credit card usage has been increased tremendously because of the popularity of E-commerce. As the usage of credit card grows the occurrence of fraudulent transactions also increases, thus comes the stipulation of fraud detection. Detection of fraudulent transaction using credit card plays a vital role in financial institutions. In the proposed work, fraud detection is done with data mining appr...

Identity fraud is the great matter of concern in the field of the e-commerce. Identity Fraud is more than a security issue it is a financial burden as in transaction and application domain the culprit can make serious problems for the victims as they can be affected with unethical activity by using victims’ private information for the economic gain. Application fraud is one of the prominent exa...

Extensive research has been done on the analytical and empirical examination of financial data in annual reports to detect fraud; however, there is scant research on the analysis of text in annual reports to detect fraud. The basic premise of this research is that there are clues hidden in the text that can be detected to determine the likelihood of fraud. In this research, we examine both the ...

In this paper we describe the results achieved using the JAM distributed data mining system for the real world problem of fraud detection in financial information systems. For this domain we provide clear evidence that state-of-the-art commercial fraud detection systems can be substantially improved in stopping losses due to fraud by combining multiple models of fraudulent transaction shared am...

One of the management measures to reduce tax liabilities is non-payment of taxes through tax fraud. Because personality factors may play a role in explaining tax ethics, examining personality traits and aspects of tax fraud can help to better understand the factors that influence tax decisions. The main purpose of this study is to provide a model for detecting tax fraud based on the personality...

P2P lending directly connects borrowers and lenders without a financial institution as the intermediary. This new form of crowdfunding brings lenders more investment opportunities, but also poses unprecedented risks of default and fraud. This research-in-progress paper focuses on a specific type of fraud, loan request fraud, which may be unique to lenders on Chinese P2P lending sites due to the...

OBJECTIVE To examine whether financial fraud is associated with poor health sleeping problems and poor quality of life. METHODS Pilot study (n=188) conducted in 2015-2016 in Madrid and León (Spain) by recruiting subjects affected by two types of fraud (preferred shares and foreign currency mortgages) using venue-based sampling. Information on the monetary value of each case of fraud; the date...

The aim of this research is to examine the impact fraud diamonds on identification fraudulent financial statements. Fraud diamonds, a framework used detect statements, considers various factors such as pressure (measured by ROA), opportunity Ineffective monitoring (IND)), rationalization auditor turnover (AUDCHANGE)), and capability change directors (DIRCHANGE)). sample comprised 9 companies se...

Anomaly detection is an important data analysis task. It is used to identify interesting and emerging patterns, trends and anomalies from data. Anomaly detection is an important tool to detect abnormalities in many different domains including financial fraud detection, computer network intrusion, human behavioural analysis, gene expression analysis and many more. Recently, in the financial sect...