Detecting Auto Insurance Fraud by Data Mining Techniques
| Full Text |  Pdf |
| Author | Rekha Bhowmik |
| ISSN | 2079-8407 |
| On Pages | 156-162 |
| Volume No. | 2 |
| Issue No. | 4 |
| Issue Date | April 01, 2011 |
| Publishing Date | April 01, 2011 |
| Keywords | Rule-based Algorithm, Bayesian Network, C4.5, Fraud Detection |
Abstract
The paper presents fraud detection method to predict and analyze fraud patterns from data. To generate classifiers, we apply the Naïve Bayesian Classification, and Decision Tree-Based algorithms. A brief description of the algorithm is provided along with its application in detecting fraud. The same data is used for both the techniques. We analyze and interpret the classifier predictions. The model prediction is supported by Bayesian Naïve Visualization, Decision Tree visualization, and Rule-Based Classification. We evaluate techniques to solve fraud detection in automobile insurance.
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