Fraud investigation and fraud control are entirely different processes. Similarly the auditing of a life insurance company and the issuing of life insurance policies and business quality control are not the same. Business quality control and fraud control have much in common. In this article, these similarities are explored and a case is made that companies issuing life insurance policies shoul...

Executive Summary Insurance fraud is the second biggest white-collar crime in the U.S. after tax evasion, according to the National Insurance Crime Bureau. As insurers deal with an uncertain economic climate and intense competition, they must also grapple with the increasing incidence and sophistication of fraud, not to mention the resulting losses. The traditional methods of identifying fraud ...

In today's time because of less-cost and more-resolution digital cameras, there is ample amount of digital images across globe. Digital images have a crucial presence in specific domains like in insurance process, forensic lab work, monitoring systems, services of intelligence, medical imaging and journalism. The most needed requirement is the images we see should be authentic. With the availab...

We present an unsupervised learning method for classifying consumer insurance claims according to their suspiciousness of fraud versus nonfraud. The predictor variables contained within a claim file that are used in this analysis can be binary, ordinal categorical, or continuous variates. They are constructed such that the ordinal position of the response to the predictor variable bears a monot...

Fraud detection is one of the ways to cope with damages associated with fraudulent activities that have become common due to the rapid development of the Internet and electronic business. There is a need to propose methods to detect fraud accurately and fast. To achieve to accuracy, fraud detection methods need to consider both kind of features, features based on user level and features based o...

The article proposes an expert system for detection, and subsequent investigation, of groups of collaborating automobile insurance fraudsters. The system is described and examined in great detail, several technical difficulties in detecting fraud are also considered, for it to be applicable in practice. Opposed to many other approaches, the system uses networks for representation of data. Netwo...

Data mining is a combination of database and artificial intelligence technologies. It is a process of identifying and extracting patterns from data, particularly from very large and/or complex sets of data. The major focus of machine learning research is to automatically learn to recognize complex patterns and make intelligent decisions based on data. Data mining and Machine Learning is a relat...

Fraud detection has been an important topic of research in the data mining community for the past two decades. Supervised, semi-supervised, and unsupervised approaches to fraud detection have been proposed for the telecommunications, credit, insurance and health-care industries. We describe a novel hybrid system for detecting fraud in the highly growing lotteries and online games of chance sect...