Neural networks approach for determining total claim amounts in insurance |
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| Authors: | Turkan Erbay Dalkilic Fatih Tank Kamile Sanli Kula |
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| Institution: | aKaradeniz Technical University, Faculty of Arts and Sciences, Department of Statistics and Computer Sciences, 61080, Trabzon, Turkey;bKirikkale University, Faculty of Arts and Sciences, Department of Statistics, 71100 Yahsihan-Kirikkale, Turkey;cAhi Evran University, Faculty of Arts and Sciences, Department of Mathematics, 40200 Kirsehir, Turkey |
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| Abstract: | In this study, we present an approach based on neural networks, as an alternative to the ordinary least squares method, to describe the relation between the dependent and independent variables. It has been suggested to construct a model to describe the relation between dependent and independent variables as an alternative to the ordinary least squares method. A new model, which contains the month and number of payments, is proposed based on real data to determine total claim amounts in insurance as an alternative to the model suggested by Rousseeuw et al. (1984) Rousseeuw, P., Daniels, B., Leroy, A., 1984. Applying robust regression to insurance. Insurance: Math. Econom. 3, 67–72] in view of an insurer. |
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| Keywords: | Neural networks Least squares method Total claim amount Claim amount payments Fuzzy if-then rules |
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