نتایج جستجو برای: detecting fraud
تعداد نتایج: 110013 فیلتر نتایج به سال:
Inappropriate payments by insurance organizations or third party payers occur because of errors, abuse and fraud. The scale of this problem is large enough to make it a priority issue for health systems. Traditional methods of detecting health care fraud and abuse are time-consuming and inefficient. Combining automated methods and statistical knowledge lead to the emergence of a new interdiscip...
An accredited biennial 2012 study by the Association of Certified Fraud Examiners claims that on average 5% of a company’s revenue is lost because of unchecked fraud every year. The reason for such heavy losses are that it takes around 18 months for a fraud to be caught and audits catch only 3% of the actual fraud. This begs the need for better tools and processes to be able to quickly and chea...
Online auction, shopping, electronic billing etc. all such types of application involves problems of fraudulent transactions. Online fraud occurrence and its detection is one of the challenging fields for web development and online phantom transaction. As no-secure specification of online frauds is in research database, so the techniques to evaluate and stop them are also in study. We are provi...
Internet users are often victimized by malicious attackers. Some attackers infect and use innocent users’ machines to launch large-scale attacks without the users’ knowledge. One of such attacks is the click-fraud attack. Click-fraud happens in Pay-Per-Click (PPC) ad networks where the ad network charges advertisers for every click on their ads. Click-fraud has been proved to be a serious probl...
Data mining techniques are providing great aid in financial accounting fraud detection, since dealing with the large data volumes and complexities of financial data are big challenges for forensic accounting. The implementation of data mining techniques for fraud detection follows the traditional information flow of data mining, which begins with feature selection followed by representation, da...
An important area of data mining is anomaly detection, particularly for fraud. However, little work has been done in terms of detecting anomalies in data that is represented as a graph. In this paper we present graph-based approaches to uncovering anomalies in domains where the anomalies consist of unexpected entity/relationship alterations that closely resemble non-anomalous behavior. We have ...
The volume of banking transaction has increased considerably in the recent years with advancement in financial transactions payment methods. Consequently, the number of fraud cases has also increased, causing billion of dollar losses each year worldwide, although from Literature, there has been substantial work in the domain of fraud detection by both the industry and academia’s. Despite the su...
Title of dissertation: Securities Fraud: An Economic Analysis Yue Wang, Doctor of Philosophy, 2005 Dissertation directed by: Professor Lemma Senbet, Professor Nagpurnanand Prabhala Department of Finance This thesis develops an economic analysis of securities fraud. The thesis consists of a theory essay and an empirical essay. In the theory essay, I analyze a firm’s propensity to commit securiti...
There are millions of apps are available in market for the application of mobile users. However, all the mobile users first prefer high ranked apps when downloading it. But we cannot guarantee the reliability for the downloaded application since there is increasing number of ranking frauds. Ranking fraud in the mobile App market refers to fraudulent or deceptive activities which have a purpose ...
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