TY  - JOUR
TT  - Fuzzy Risk Classification in Life Insurance
AU  - Apaydın, Ayşen
AU  - Başer, Furkan
AU  - Güneri Tosunoğlu, Nuray
PY  - 2009
DA  - June
JF  - Selcuk University Journal of  Science Faculty
JO  - sufefd
PB  - Selcuk University
WT  - DergiPark
SN  - 2458-9411
SP  - 123
EP  - 136
VL  - 2
IS  - 34
KW  - Sigorta
KW  - Hayat sigortası
KW  - Risk sınıflandırma
KW  - Bulanık mantık
KW  - Bulanık çıkarım sistemleri
N2  - Risk classification, which can be defined as categorizing insured risks according to their probability of generating claims and according to the size of those claims, is one of the most important topics in actuarial science. Traditionally, life insurance policyholders are classified by using classical mortality tables and generally according to limited number of risk characteristics, many other risk factors are ignored. Conventional clustering algorithms are organized in contemplation of the fact that objects are either in the set or not. However, the boundaries of each class are not always sharply defined. In these circumstances, fuzzy set methodology provides a convenient way for constructing a model that represents system more accurately since it allows integrating multiple fuzzy or non-fuzzy factors in the evaluation and classification of risks. In this paper, we investigate an alternative method of classifying risks in life insurance, based on the concept of fuzzy inference systems. We differentiate policyholders on the basis of their cardiovascular risk characteristics and estimate risk loading ratio to obtain gross premiums paid by the insured. Four categories of group are considered: preferred risk, normal risk, substandard risk and unacceptable risk.
CR  - Ostaszewski, K. M., An Investigation into Possible Applications of Fuzzy Set Methods in Actuarial Science, The Society of Actuaries, Schaumburg (1993).
CR  - DeWit, G.W., Underwriting and uncertainty, Insurance Mathematics and Economics, 1, 277–285 (1982).
CR  - Lemaire, J., Fuzzy Insurance, Astin Bulletin, 20, 33-56 (1990).
CR  - Young, V.R., The application of fuzzy sets to group health underwriting, Trans. Soc. Actuaries, 45, 551–590 (1993).
CR  - Derrig, R. A., Ostaszewski, K. M., Fuzzy Sets Methodologies in Actuarial Science, Practical Applications of Fuzzy Technologies, Zimmerman, H. J. (ed.), Kluwer Academic Publishers, Boston (1999).
CR  - Huebner, S. S., Black, K., Life Insurance, Prentice-Hall, New Jersey (1976).
CR  - Baykal, N., Beyan T., Bulanık Mantık Uzman Sistemler ve Denetleyiciler, Bıçaklar Kitabevi, Ankara (2004).
CR  - Bojadziev, G., Bojadziev, M., Fuzzy Logic for Business, Finance and Management, World Scientific, London (2007).
CR  - Şen, Z., Bulanık Mantık ve Modelleme İlkeleri, Bilge Kültür Sanat, İstanbul (2001).
CR  - 0] Özdemir, A., Hayat Sigortası: Teori ve Türkiye’de Uygulama, A. Ü. Siyasal Bilgiler Fakültesi Yayınları, Ankara (1980).
CR  - 1] Horgby, P.-J., Risk Classification by Fuzzy Inference, The Geneva Papers on Risk and Insurance, 23, 63-82 (1998).
CR  - 2] Onat, A., Risk factors and cardiovascular disease in Turkey, Atherosclerosis, 156, 1-10 (2001).
CR  - 3] Dikmenoğlu, N., Kardiyovasküler hastalıklarda sigara ve kolesterol kadar önemli bir risk faktörü: kan akışkanlığı, Hacettepe Tıp Dergisi, 37, 93–97 (2006).
CR  - 4] Samur, G., Yıldız, E., Obezite ve Kardiyovasküler Hastalıklar / Hipertansiyon, Klasmat Matbaacılık, Ankara (2008).
UR  - https://dergipark.org.tr/en/pub/sufefd/issue//246778
L1  - https://dergipark.org.tr/en/download/article-file/214599
ER  -