Evaluating and classifying the insurers risk in the insurance industry using data envelopment analysis
Subject Areas : Statistics
Seyyedeh Nasim Shobeiri
1
(
Department of Accounting, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
)
Mohsen Rostamy- Malkhalifeh
2
(
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
)
Hashem Nikoomaram
3
(
Department of Accounting, Faculty of Management and Economics, Science and Research
Branch, Islamic Azad University, Tehran, Iran
)
Mohammadreza Miri Lavasani
4
(
Department of HSE Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
)
Keywords: طبقهبندی ریسک بیمهگذاران, تحلیل پوششی دادهها, بیمه خودرو, صنعت بیمه,
Abstract :
One of the most important factors for the economic development of countries is the insurance industry.A closer look at the economies of Developed Countries shows that the insurance industry has a significant contribution in the economic development of these countries. The insurance industry needs to accept the risk in order to carry out any insurance activity. In the other word, the insurance companies create tranquillity in the society by accepting the risk. On the other hand, the insurance companies need to access to the powerful risk analysis tools in order to manage the potential risks. Data envelopment analysis (DEA) is one of the most important techniques to identify the risk resources. Hence, data envelopment analysis is widely used in the insurance industry. This study uses the dataset of the car insurance policies of Saman Insurance Company during the years 2018-2019. First, we identify the effective indicators and examine the properties of these indicators to classify them into input and output groups. Finally, we use data envelopment analysis to propose a model for predictionthe risk of insurers (in terms of existence of damage risk or absence of damage risk). This model can be used in the future policies of the insurance company. For example, the insurance companies can use the results of data envelopment analysis to adjust the premiums received from different insurers and increase the satisfaction for insurers and their profitability by creating a rating system based on the insurers 'risk.
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