IRANIAN JOURNAL OF INSURANCE RESEARCH (SANAAT-E-BIMEH)
Year:2020 | Volume:34 | Issue:4|Papers Count:11

Objective: This paper examines the effect of risk culture on the performance of risk management in insurance companies providing complementary health insurance, in terms of neoclassical economics and enterprise risk management. Methodology: The Analytic hierarchy process (AHP) was used in this study. Findings: The principles of risk management as well as four cultures-based theory of multiple rationality were presented and the principles of neoclassical economics and enterprise risk management were analyzed for insurance companies offering complementary health insurance. The principles of "enterprise risk management" with weight of 62. 1% has gained the highest rank compared to "neoclassical economics" with weight of 37. 9% in relation to overall goal. Also, "risk appetite" and "separate measurement and management of risk" criteria in selection of enterprise risk management gained the highest weight compared to other criteria. Conclusion: The principles of risk culture is best compatible with the principles of enterprise risk management, but this does not mean that the principles of enterprise risk management and the neoclassical economy cannot be used simultaneously in a company. Generally, the insurance companies choose a combination of these principles. In other words, insurance companies select a combination of four approaches based on the theory of multiple rationality. Also, considering that the attitude of Central Insurance Organization of Islamic Republic of Iran to the risk strategy has the impact on the risk culture of insurance companies, it is recommended that Central Insurance Organization adopts an optimal attitude according to the conditions and necessities of the insurance industry.

Objective: Natural disasters have destructive effects on the countries’ physical and human capitals. Hence, it is necessary to use risk management techniques. The purpose of this study is to analysis the impact of earthquake insurance on reducing the earthquake destructive effects on economic growth through financing the destruction and forcing the insureds to reduce risk. Therefore, the effects of possible earthquakes in the Ray fault or Tehran north fault on Iran economic growth for 40 years is simulated. The year 2012 was assumed as the beginning and the possible earthquake occurrence was predicted in the eighth year (2020). Then, the effects of using insurance techniques for risk management on reducing the damaging effects of earthquakes on economic growth have been analyzed. Method: The effects of probable earthquake in Tehran on Iran economic growth is simulated by system dynamics method. This method provides the possibility of comprehensive analysis of the insurance earthquake effect on the reduction of the destructive earthquake impacts on national capital, and identifies the earthquake impact channels on economic growth by dynamically examining causal relationships, and Iran economic growth changes by earthquake predicts in the long run. Finding: The findings show that in the event of an earthquake in the Rey fault, the physical capitals of 2400100 billion rails, 647800 humans and 203480 billion gross domestic product will decrease by 2051. Therefore, earthquake risk management is necessary to reduce these effects. If there is no earthquake insurance, only part of the damages will be compensated by the government and international organizations. Thus, the government's development budget will be spent on post-earthquake reconstruction and it will hit the country's economy. However, if there is earthquake insurance fund, most of the losses will offset by the funds received from the insureds and foreign reinsurers will required to pay damages. Another advantage of using earthquake insurance is to create conditions to reduce the damages scope by the insureds. Results suggest that insurer required to comply with the insured with the country's seismic regulations by applying incentive and risk-based pricing policies. Therefore, buildings collapse risk and amount of earthquake damage will be reduced. Conclusion: The speed of reconstruction and compensation will increase in case of application of insurance technique in earthquake risk management. Therefore, a general earthquake insurance fund should be created. Observing the risk dispersion principle is important for the insurers. The fund covers part of its funds with foreign reinsurance. Part of potential losses incurred in Iran will be compensated through foreign insurers, capital will be rebuilt and the country's economic growth will be improved. The results recommend that the fund considers buildings collapse risk and the country's seismic regulations compliance to determine the amount of premium. Thus, the devastating effects of the earthquake on physical assets will be decreased by 525, 600 billion Rials and economic growth will be improved by 62100 billion Rials by creating a public earthquake insurance fund and obliging the insured to observe the Iran seismic regulations.

Objective: Risk classification of insurance customers, based on the observable characteristics, can significantly help insurers mitigate losses, classify their customers and prevent adverse selection. This paper aims to study losses occurred in motor Third Party Liability (TPL) insurance and predict customers’ risk of loss. Methodology: With the help of four supervised algorithms namely; decision tree, SVM, naï ve Bayes and neural network hidden pattern of data is discovered to classify customers of TPL insurance. Furthermore, the imbalanced dataset was the main challenge for implementing machine learning and data mining techniques which will be discussed throughout the article. Findings: The dataset contains more than 400, 000 observations for five years from an Iranian insurance company. It also has five variables of which four are independent: car type, car group, plate type, car age; and one binary dependent variable: financial loss. Comparing the model performances, decision tree is the most efficient (F1=0. 72± 1). Conclusions: The model provides prioritization of independent features as follows: car type, plate type, car age, car group. Findings also suggest that to obtain more accurate prediction on claims and high-risk customers, more features concerning drivers’ traits are required.

May 2 Abstract Objective: Since surviving on obligations to insurers and maximizing the benefits of the company is one of the most important goals of insurance companies, and on the one hand, the regulatory agencies of each country are trying to enact specific laws and regulations and managers by adopting precautionary measures and modern technical and financial strategies. The purpose of this study was to present an intelligent model for predicting financial empowerment in insurance companies as a decision support system. Methodology: In order to present a model of predicting the financial health of insurance companies by examining the background of 17 variables as predictor variables for predicting the class of financial wealth, extracted from reliable sources of central insurance site of the Islamic Republic of Iran during 2013-2017. In this study, first, the results of applying different prediction models based on artificial intelligence including: decision tree, neural network, nibbles were compared. Then, the ranking of predictive algorithms was evaluated. Findings: The results of this study showed that the decision tree with 99% accuracy has the best performance in predicting financial ability, considering that the decision tree is a nonlinear cognition and mapping models and patterns of turbulence between goal and decision variables. Conclusion: The accuracy of the decision tree model in predicting financial robustness is high and the model extracted using decision tree has high accuracy and capability in estimation.

Objective: Understanding the dimensions of strategic market orientation is crucial in industries where competition is high and customers have different and diverse needs and wants. Acquiring market information and responding accordingly is the philosophy of market orientation. The main purpose of this study is to conceptualize strategic market orientation and its relationship with performance in the Iranian insurance industry. Methodology: The study population of this descriptive survey is 16681 managers of public and private insurance agencies in the provinces of Tehran, Khorasan-e-Razavi, Isfahan, Fars, Azerbaijan-e-sharghi and Khuzestan. Three hundred agencies using the stratified random sampling method participated in this survey and completed the questionnaires. The validity of the questionnaire was confirmed through content and construct validity tests and its reliability was confirmed through Cronbach's alpha coefficient. Collected data was analyzed through structural equation modeling using AMOS18 to test hypotheses of research. Findings: Strategic market orientation has positive impact on financial and non-financial performance of insurance companies. The mediating role of non-financial performance between strategic market orientation and financial performance was also confirmed. Conclusion: Gathering and analyzing customer and competitor information and then designing a market-oriented strategy tailored to meet environmental opportunities and threats and providing process, system, and behavioral infrastructure to implement this strategy improve financial and non-financial indicators in the Iranian insurance industry.

Objective: Financial development resulted from the advances in the insurance, banking and capital markets sectors is one of the most important requirements for a country’ s sustained economic growth. An efficient system is needed for pooling micro-funds in the banking and insurance sectors and converting them into financial resources for firms’ financing and investment. In developed countries, life insurance is one of the most important mechanisms for attracting stagnant liquidity in the market and leading them into capital market along with sustaining the benefits for policyholders. However, in developing countries, the role of this financial institution is very limited. The objective of this study is to identify and investigate the macroeconomic factors affecting financial development with an emphasis on life insurance development. Methodology: This study examined the impact of life insurance on financial development in a comparative study between developed countries and Iran during the period of 1985-2016 using the Generalized method of moments approach. Findings: The results show that the development of life insurance in developed countries, unlike Iran, has a significant impact on financial development. This indicates the underdevelopment of the life insurance sector in Iran's insurance industry. Also, the effect of government expenditure on financial development in Iran, in contrast to the developed countries, is positive and significant. On the other hand, the impact of the inflation rate on financial development in Iran has been significant in contrast to the developed countries. Among the variables studied for developed countries, trade volume, government spending, GDP per capita and life insurance development had the greatest impact on financial development. In Iran, government spending, inflation, and life insurance have had the greatest impact on financial development. Conclusions: The impact of life insurance on financial development is more than nonlife insurance. Besides, unlike the developed countries, life insurance in Iran due to its low share in the insurance companies’ portfolio, has a significant negative effect on financial development in the banking sector. The first hypothesis of the research "life insurance development has a significant impact on the financial development in the developed countries" is confirmed. Nevertheless, the second hypothesis of the research, "life insurance Development has a significant impact on Iran’ s financial development", is partially supported.

Objective: Developing a model for catastrophe swap pricing based on the stochastic models and numerical model solving. Methodology: Vrance and Pielke (2009) database was used in this descriptive and retrospective study. Ito has been followed to determine the swap price changes, and the Black– Scholes modeling method was used to reach the catastrophe swap model. A partial integral differential equation was extracted and transformed to ordinary differential equations using Semi-discretization. The Finite difference method and the Euler method were used to solve the catastrophe swap pricing model. The parameters have been estimated and implemented numerically using Bjork's (2009) statistical inference method and finally, the model was implemented using MATLAB software. Findingys: A new two-factor damage model was introduced. In other words, instead of c in the Anger model, ce to the power Lambda is used and Lambda is considered to be stochastic at any given moment. Therefore, from a view of mathematical probability, intensity value is not constant and fallows a Geometric Brownian Motion process, which is correlated with the damage. A new model for catastrophe swap pricing has also been introduced, which has two integral and differential parts. Conclusions: The price of a catastrophe swap securities is inversely correlated with the growth of the damage and the increase in the severity of the damage. Besides, the price trend for damage less than the threshold, has a regular trend and these changes are proportional to the changes in the damage and intensity.

Objective: The blue ocean strategy, as a competitive source, can identify the potential of the companies and win them in the competition. Therefore, this study evaluates the relationship between using the blue ocean strategy and gaining competitive advantage. Methodology: The research is a descriptive study using a questionnaire survey. About 157 of managers, consultants and employees of the Novin insurance company were selected using simple random sampling method and participated in this study. Data was analyzed using structure equation modeling and the path analysis to examine the research hypotheses using SPSS and PLS softwares. Findings: The results indicate that all research hypotheses were confirmed and the removal strategy of the blue ocean has first rank and the greatest impact on the competitive advantage of the Novin insurance company, and the reducing strategy for the ocean blue has Fourth rank and the lowest impact on the competitive advantage of the Novin insurance company. Conclusions: Insurance Companies can Achieve Competitive Advantage using the blue ocean strategy.

Objective: this study aimed to develop a model for factors affecting customers' switching intention and their behavioral intentions in the insurance industry using with structural equations and fuzzy inference system. Methodology: This study was descriptive-analytical. The statistical population consisted of customers of insurance companies in Alborz province (18 companies). About 386 customers (by stratified random sampling method) participated in this study using the Cochran sample size formula. Standard questionnaires (with verified validity and reliability) were used for data collection. The structural equation modeling and fuzzy inference system were used for data analysis. Findings: The results in structural equation modeling showed that the set of contextual factors in the theoretical model of this research can explain 91. 8% and 77. 2% of changes in customers’ behavioral intentions and customers' switching intention (R-Square = 0. 918-0. 772). In addition, the results from the fuzzy inference system showed that the effects of customer’ s satisfaction and perceived risks on each other were in opposite direction. Conclusion: in perceived risks with upward average amount (from a numerical value of 0. 5 to 1), changes of customer satisfaction scores served from a numerical amount of 0. 1 to 1, with a decreasing form on customers' switching intention. Also, switching costs had less impact on achieving the positive behavioral intentions of customers than the brand image. Thus, it can be seen that by realizing the high switching costs, i. e., scores higher than 0. 8, it is only enough that the brand image is higher than 0. 2, so it can be expected that the positive behavioral intentions to be realized in a very acceptable level in the customers.

Objective: The purpose of this paper is to introduce the process of risk assessment of insurance companies in a risk-based supervision system and the way to monitor it. Methodogogy: We used the KNF (2018) risk assessment framework for insurance and reinsurance companies. This comprehensive framework uses all available information held by the supervisory authority about the (re)insurance company, including information obtained as a result of actions related to the licensing, off-site analyses and control actions during on-site inspections carried out in the (re)insurance company as well as inquiries/questionnaires sent to the (re)insurance companys. Findings: The supervisory assessment focuses on significant risks and areas of operation of (re)insurance companies. Implementing this new approach requires complying the International Association of Insurance Supervisors’ (IAIS) principles, preparing risk management and actuarial reports, rating and ranking insurance companies, analyzing complaint data and separating life and non-life insurance accounts. Conclusions: An action plan is necessary to achieve effective supervision and risk-based supervision in the insurance industry:-The compliance of the insurance regulations with the IAIS core principles-The separation of life and non life insurance accounts-Developing actuarial standards of practice-Obliging insurance companies to prepare their Own Risk & Solvency Assessments (ORSA) empowerment to comply with the requirements of the Corporate Governance (Risk Management) Regulations in accordance with IAIS principles-Use of international and general standards and supervisory and regulatory standards of enterprise risk management-preparation the report of internal controls by insurance companies.