Neural Networks Approach for Determining Total Claim Amounts in Insurance
Yazarlar (3)
Karadeniz Teknik Üniversitesi, Türkiye
Ankara Üniversitesi, Türkiye
Prof. Dr. Kamile ŞANLI KULA
Kırşehir Ahi Evran Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | INSURANCE MATHEMATICS & ECONOMICS | ||
| Dergi ISSN | 0167-6687 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 10-2009 |
| Cilt / Sayı / Sayfa | 45 / 2 / 236–241 | DOI | 10.1016/j.insmatheco.2009.06.004 |
| Özet |
| 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. (C) 2009 Elsevier B.V. All rights reserved. |
| Anahtar Kelimeler |
| Neural networks | Least squares method | Total claim amount | Claim amount payments | Fuzzy if-then rules |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| WoS | 9 |