Paper Title
Ascertaining Illegitimate Medical Insurance Claims

Abstract- Discerning the Fraud is tedious and it plays a key role in the most of the business sectors such ascredit companies, banks, insurance companies, telecom and aerospace companies. The problem arises when the data is not handled and analyzed properly in order to get the legitimate business transactions.Inability to catch fraud can become an extremely costly, painful and damaging problem to a business and thus the need for efficient Fraud Detection solutions resides high on the "to do" list of every company. Inspite of dealing with millions of insured customers and dozens of thousands of providers of medical services, healthcare insurance companies have to routinely address the task of verifying the authenticity and legitimacy of all processed transactions. In fact, fraudulent transactions might be originating from all involved parties. The fraud patterns get more sophisticated and the volume of transactions grows, it becomes increasingly more difficult to discern fraud from licit transactions. Analysts have to utilize advanced data analysis tools capable of processing large volumes of data and detecting unusual events deviating from the normal operation patterns. Fraud schemes are rapidly changing and analysts need to be able to discern new fraud patterns without an explicit prior knowledge of these patterns. This paper introduces an open source and effective solution for analyzing the health care data using Revolution Analytics which is often called as R. By using the R and other components we provide robust frame work and efficient fraud detection system Keywords- Analytics, Detection, Framework, Fraud