@article{2020,title={Fraud Detection in Insurance Claims with Machine Learning},abstractNode={Fraud has been rising recent years all over the world. Especially, increase of the internet usage and use of credit cards more increase to fraud cases as well. Much work has been done and measures have been taken in the banking sector to detect and prevent credit and credit card frauds. Similarly, counterfeit claims are also common in the insurance sector. It is seen that the insurance sector is a little more difficult to predict fake claims than the bank sector and the studies in this area are less. As computers' transaction volumes and speeds progress, human beings have started to use newer technologies in every area of their business. Nowadays, we are talking about the writing, learning and implementation of the algorithm by the program itself. Machine learning is an application of artificial intelligence and it achieves results by developing what it has learned. Machine learning has also started to be used in finance and insurance sector like it is used in many industry. Insured customer informations and claim informations are collected in the big data pool and reach serious dimensions over time. If this data is used and analyzed with correct machine learning algorithms, counterfeit claims can be estimated to a large extent. In this study, using the machine learning algorithms on the claim data set obtained from an insurance company, the predictive scores of the fraud cases of the claims will be compared. By running 7 different machine learning algorithms on the same data set with the same test and training rates, the accuracy rates and performances will be compared and the results will be shown.},author={Yaşar GEREN},year={2020},journal={Turkish Studies-Information Technologies and Applied Sciences}}