The healthy development of the Internet largely depends on the online advertisement which provides the financial support to the Internet. Click fraud, however, poses serious threat to the Internet ecosystem. It not only brings harm to the advertisers, but also damages the mutual trust between advertiser and ad agency. Click fraud prediction is a typical big data application in that we normally ...

In this paper, a fuzzy rule-based classifier (FRBC) system was developed and used in two Evolutionary Algorithm Models to detect patterns of financial statement fraud and assess the effectiveness of a subset of SAS No. 99 red flag variables. Each FRBC was evolved by using Generic Algorithm(GA) and MARLEDA – a modern estimation of distribution algorithm (EDA) – and trained with a data collection...

F are increasingly relying on software to detect fraud in domains such as security, financial services, tax, and auditing. A fundamental problem in using detection software for fraud detection is achieving the optimal balance between the detection and false-positive rates. Many firms use decision theory to address the configuration problem. Decision theory is based on the presumption that the f...

Financial exploitation, and particularly thefts and scams, are increasing at an alarming rate. In this study we (a) determined the national prevalence of older adults who report having been a victim of fraud, (b) created a population-based model for the prediction of fraud, and (c) examined how fraud is experienced by the most psychologically vulnerable older adults. The older adults studied we...

Minority class detection is the problem of detecting the occurrence of rare key events differing from the majority of a data set. This paper considers the problem of unsupervised minority class detection for multidimensional data that are highly nongaussian, mixed (continuous and/or discrete), noisy, and nonlinearly related, such as occurs, for example, in fraud detection in typical financial d...

Fraud is an unauthorized activity taking place in electronic payments systems, but these are treated as illegal activities. Fraud detection methods are continuously developed to defend criminals in adapting to their strategies. Fraud can be identified quickly and easily through fraud detection techniques. In this paper, clustering approach is used for credit card fraud detection. Data is genera...

The majority of the United States health care fraud has been focused on the major public program, Medicare. The yearly financial loss from Medicare fraud has been estimated at about $54 billion. The purpose of this research study was to explore the current state of Medicare fraud in the United States, identify current policies and laws that foster Medicare fraud, and determine the financial imp...

The auditor's ability to detect fraud is the determine illegal acts that result in material misstatement financial statements which were done intentionally. In order for perform detection increase, an experienced auditor, professional skepticism and competence needed. purpose of this study empirically prove effect experience, skepticism, on auditors fraud. This research was conducted at a Publi...

Fraud is an unauthorized activity taking place in electronic payments systems, but these are treated as illegal activities. Fraud detection methods are continuously developed to defend criminals in adapting to their strategies. Fraud can be identified quickly and easily through fraud detection techniques. In this paper, clustering approach is used for credit card fraud detection. Data is genera...

Financial managers, auditors, and fraud examiners are eager to find an automated, timely approach to discovering which publicly traded companies may be harboring financial frauds. Investors, corporate treasurers, and portfolio managers all want a dependable, automatic process to help them sift through voluminous financial data to find the few firms among hundreds that give investors bad informa...