Abstract
The insurance industries consist of more than thousand companies in worldwide. And collect more than one trillions of dollars premiums in each year. When a person or entity make false insurance claims in order to obtain compensation or benefits to which they are not entitled is known as an insurance fraud. The total cost of an insurance fraud is estimated to be more than forty billions of dollars. So detection of an insurance fraud is a challenging problem for the insurance industry. The traditional approach for fraud detection is based on developing heuristics around fraud indicator. The auto\vehicle insurance fraud is the most prominent type of insurance fraud, which can be done by fake accident claim. In this paper, focusing on detecting the auto\vehicle fraud by using, machine learning technique. Also, the performance will be compared by calculation of confusion matrix. This can help to calculate accuracy, precision, and recall.
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