Document Type : Original Article

Authors

Department of Industrial Engineering and Management Systems, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.

Abstract

Automobile hull insurance has attracted much attention due to the high rate of vehicle applications in daily lives. Since purchasing these policies is optional in Iran and their premium rates are set competitively, a competition is formed among the insurance companies for attracting low risk drivers. However, most of the insurers still use comparative rates and pay no or less attention to the factors affecting risk in premium calculations. Considering the importance of fair ratemaking in attracting and maintaining good risks and encouraging bad risks to repent or leave the portfolio, and taking into account the shortcomings of the available databases, this paper focuses on determining and classifying the risk factors affecting premium calculation in automobile hull insurance from the viewpoint of the experts. In this regard, Fuzzy Delphi method is utilized, the factors are classified and the efficiency of the classification is checked by using Confirmatory Factor Analysis (CFA).

Keywords

Ahmadi, F., Nasiriani K., and Abazari, P., (2008). "Delphi technique: a tool in research", Iranian Journal of Medical Education, Vol. 8, No. 1, pp. 175-185 (in Persian).
Anbari, E., Nad-e-Ali, A., and Eslami Nosratabadi, H., (2010). "Comparing datamining algorithms for determining the risk of automobile insurance policyholders", The Fourth Conference on Datamining, Sharif University, Tehran (in Persian).
Aseervatham, V., Lex C., and Spindler, M., (2016). "How do unisex rating regulations affect gender differences in insurance premiums?", Geneva Pap. Risk Insurance Issues Pract., Vol. 41, pp. 128–160.
Baecke, P., and Bocca, L., (2017). "The value of vehicle telematics data in insurance risk selection processes", Decis. Support Syst., Vol. 98, pp. 69–79.
Barker, M., and Rayens, W., (2003). "Partial Least Squares for Discrimination", Journal of Chemometrics, Vol. 17, pp. 166-173.
Bian, Y., Yang, C., Zhao, J., and Liang, L., (2018). "Good drivers pay less: A study of usage-based vehicle insurance models", Transportation Research Part A, Vol. 107, pp. 20-34.
Byrne, B.M., (1994). Structural equation modeling with EQS and EQS/Windows: Basic concepts, applications and programming, Sage.
Central Insurance of Iran Research and Developmen Deputy, (2017). "Statistical yearbook of the insurance industry 1395 (2016)", Central Insurance of Iran, Tehran, Iran (in Persian).
Dehpanah, A., and Tprkestani, M., (2014). "Determining the potential claims of automobile hull insurance policyholders using a neural-network model- Case study: Asia Insurance Co.", The First Conference on Applied Economics and Management: A National Approach, Mazandaran University, Babolsar (in Persian).
Fornell, C., and Lacker, D., (1981). "Evaluation structural equation models with unobserved variables and measurement error", Journal of Marketing Research, Vol. 18, No. 1, pp. 39-50.
Haji-Heidari, N., Khalei, S., and Farahi, A., (2011). "Classifying the risk of automobile hull insurance policy holders using datamining algorithms- Case study: an insurance company", Iranian Journal of Insurance, Vol. 26, No. 4, pp. 107-129 (in Persian).
Hanafizadeh, P., and Rastkhiz-Paydar, N., (2011). "A model for risk classification of customer groups in automobile hull insurance using datamining", Iranian Journal of Insurance Research, Vol. 26, No. 2, pp. 55-81 (in Persian).
Hanafizadeh, P., and Rastkhiz-Paydar, N., (2013). "A comparison of two datamining techniques in clustering automobile hull insurance based on risk: case study: Mellat Insurance Co.", Industrial Management Studies, Vol. 11, No. 30, pp. 77-97 (in Persian).
High Council of Insurance, (2012). "Bylaw no. 81", Tehran (in Persian).
Imani Jajarmi, H. (2000). "An introduction to Delphi method and its application in decision-making”, Urban Management, Vol. 1, No. 1, pp. 35-39 (in Persian).
Insurance Research Center, (2014a). "Automobile hull insurance premium rates”, Advisory rates in commercial insurances (1393/2014), First ed., Tehran, Insurance Research Center (Affiliated to the Cental Insurance of Iran) (in Persian).
Insurance Research Center, (2014b). "Studying the risk factors and the factors affecting premium calculation in motor insurances in Iran and other countries", Working Paper no. 22 (in Persian).
Izadparast, S., Farahi, A., Fathnejad, F., and Teymourpour, B., (2012). "Using datamining techniques for determinign risk level of customers in automobile hull insurance”, Iranian Journal of Information Processing and Management, Vol. 27, No. 3, pp. 699-722 (in Persian).
Jukić, N., Sharma, A., Nestorov, S. and Jukić, B., (2015). "Augmenting data warehouses with Big Data”, Inf. Syst. Manage., Vol. 32, pp. 200-209.
Klir, G.J., and Yuan, B., (1995). Fuzzy sets and fuzzy logic, theory and applications, New Jersey: Prentice-Hall Inc.
Lahrmann, H., Agerholm, N., Tradisauskas, N., Berthelsen, K. and Harms, L. (2012). "Pay as You Speed, ISA with incentives for not speeding: results and interpretation of speed data", Accid. Anal. Prev., Vol. 48, pp. 17–28.
Linstone, H.A., and Turoff, M., (2002). "The Delphi Method", Techniques and applications, Vol. 53.
Liu, Y., and Rayens, W., (2007). "PLS and dimension reduction for classification”, Computational Statistics , Vol. 22, pp. 189–208.
Maitra, S. and Yan, J., (2008). "Principle Component Analysis and Partial Least Squares: Two Dimension Reduction Techniques for Regression", Casualty Actuarial Society, 2008 Discussion Paper Program, pp. 79-90.
Mehmood, T., Liland, K.H., Snipen, L. and Sæbø, S., (2012). "A review of variable selection methods in Partial Least Squares Regression”, Chemometrics and Intelligent Laboratory Systems, Vol. 118, pp. 62–69.
Murray, T., Pipino, L.L., and Gigch, J., (1985). "A pilot study of fuzzy set modification of Delphi", Human systems management, Vol. 5, pp. 76-80.
Nemati, S., (2014). "Investigating, identifying and prioritizing risks in automobile insurance", The First Conference on Risk and Insurance Management, Tehran (in Persian).
Nguyen, D.V., and Rocke, D.M., (2002). "Tumor classification by partial least squares using microarray gene expression data”, Bioinformaics, Vol. 18, No. 1, pp. 39-50.
Nguyen, D.V., and Rocke, D.M., (2004). "On partial least squares dimension reduction for microarray-based classi'cation: a simulation study”, Computational Statistics & Data Analysis , Vol. 46, pp. 407-425.
Okoli, C., and Pawlowski, S.D., (2004). "The Delphi method as a research tool: an example, design considerations and applications”, Information and Management, Vol. 42, pp. 15-29.
Paefgen, J., Staake, T., and Thiesse, F., (2013). "Evaluation and aggregation of pay-as-you-drive insurance rate factors: a classification analysis approach”, Decis. Support Syst., Vol. 56, p. 192–201.
Payandeh Najafabadi, A.T., (2015). "Analyzing the Bonus_Malus System of Iran (in Persian)”, Iranian Journal of Insurance Research, Vol. 29, No. 4, pp. 1-31.
Tselentis, D., Yannis, G., and Vlahogianni, E., (2016). "Innovative insurance schemes: pay as/how you drive”, Transportation Research Procedia, Vol. 14, pp. 362 – 371.
Tselentis, D., Yannis, G., and Vlahogianni, E., (2017). "Innovative motor insurance schemes: A review of current practices and emerging chellenges”, Accident Analysis and Prevention, Vol. 98, pp. 139-148.
Yeo, A.C., Smith, K.A., Willis, R.J., and Brooks, M., (2001). "Clustering Technique for Risk Classification and Prediction of Claim Costs in the Automobile Insurance Industry”, International Journal of Intelligent Systems in Accounting, Finance & Management, Vol. 10, pp. 39-50.
Yeo, A.C., Smith, K.A., Willis, R.J. and Brooks, M., (2003). "A comparison of soft computing and traditional approaches for risk classification and claim cost prediction in the automobile insurance industry”, Soft Computing in Measurement and Information Acquisition, pp. 249-261.
Zadeh, L.A., (1965). "Fuzzy sets”, Information and control , Vol. 8, No. 3, pp. 338-353.