> IBM Software > Using Data Mining to Detect Insurance Fraud
 

Using Data Mining to Detect Insurance Fraud

White Paper Published By: IBM Software
IBM Software
Published:  Nov 02, 2010
Type:  White Paper
Length:  7 pages

Insurers lose millions each year through fraudulent claims. Learn how leading insurance companies are using data mining techniques to target claims with the greatest likelihood of adjustment, improving audit accuracy, and saving time and resources. Read this paper to learn how to combine powerful analytical techniques with your existing fraud detection and prevention efforts; build models based on previously audited claims and use them to identify potentially fraudulent future claims; ensure adjusters focus on claims most likely to be fraudulent; and deploy results to the people who can use the information to eradicate fraud and recoup money.



Tags : 
ibm cognos predictive analysis, data mining, insurance fraud detection, analytical technique, prevention

We use technologies such as cookies to understand how you use our site and to provide a better user experience. This includes personalizing content, using analytics and improving site operations. We may share your information about your use of our site with third parties in accordance with our Privacy Policy. You can change your cookie settings as described here at any time, but parts of our site may not function correctly without them. By continuing to use our site, you agree that we can save cookies on your device, unless you have disabled cookies.
I Accept