As a capital market investment, stocks have risks that must be managed. Therefore, investors should consider the returns and risks of investment products. This study aims to estimate the risk of insurance companies' loss when investing. The method used to estimate the level of risk is Value at Risk (VaR) based on Extreme Value Theory (EVT). The data used is secondary data in the form of daily stock closing prices from two insurance companies, AXA General Insurance and BRI Insurance, from January 2016 to January 2022. The data were used to estimate the risk value according to the EVT principle. As a result, Insurance AXA General Insurance, with 5.91% liquidity, has the lowest VaR value with a 99% confidence level, while BRI Insurance has 5.04%. We concluded from these results that AXA General Insurance has a lower investment risk. It means that each company has a different risk value. Therefore, investors should know these risk factors when choosing a company.

Life insurance is designed to reduce the risk of financial loss due to unforeseen consequences related to the insured's death. In life insurance, the insurer provides death benefits as a claim when the insured suffers death. The claim is the compensation for a risk loss. Individual claim in one-period insurance is called aggregation claim, while aggregation claim is a collective risk. Collective risk is usually measured using a variance. However, the variance risk measure cannot often accommodate any event risk because there is a risk of claims beyond the amount of variance. Using the proposed method CVaR and confidence level are taken from α = 0.25% until 4%. This study found that the proposed method CVaR scored more fairly than Collective Risk. In conclusion, this study indicated that the collective risk model is just included using mean and variance without any confidence level. Therefore, only one result for the Collective Risk model, which automatically shows the model using mean, variance and standard deviation, could not accommodate all risk events.

The Saudi Arabian insurance sector has two distinctive features. First, major revenue for this sector comes from the mandatory medical and motor insurance. Second, this sector is dominated by a few companies which generally provide the same products in the sector. Therefore, a company may focus on providing better service quality in order to attain future growth and stability. High-quality service is essential to gain a competitive advantage in the insurance sector. In this context, the present study identifies a gap in assessing the quality of service in the insurance sector of Saudi Arabia, using the SERVPERF scale in particular. Structural Equation Modeling is used to assess the quality of service. The results indicate that SERVPERF is not adequate to measure service quality in the context of Saudi Arabia. In the process, this study opens a debate on, whether a universally acknowledged SERVPERF scale is suitable to apply in an environment where service is of mandatory nature.

This paper presents an exploratory factor analysis on knowledge management and organizational innovation items influencing on organizational strategy. The study designs a questionnaire in Likert scale and distributes it among 210 employees in an insurance firm named Dana located in Iran. Cronbach alpha has been well above 0.90, which confirms the validity of the overall survey. Using principle component analysis, the study extracts six critical success factors influencing on knowledge management including knowledge management processes, organizational culture, organizational structure, human resources, information technology, top management support and three factors of innovation including product innovation, process innovation, and organizational performance.

This paper attempts to find important factors influencing on insurance issued by export guarantee funds. The study uses factor analysis to detect important factors based on a questionnaire in Likert scale. The study has determined four factors including risk management, customer oriented, quality management and trade management. The first factor is associated with risk management and it includes four sub-factors. The factors include being responsive, reliability, service quality and customer detection and reliability plays the most important factor. The second factor is associated with being customer oriented where the factor includes four components including cost recognition, access, marketing knowledge and the level of management training. The third factor is associated with quality management, which includes four variables including responsiveness, reliability, quality of services and customer recognition. Finally, the last factor is associated with trade management, which includes three variables including trade risk, insurance premium and currency.

Agricultural business is a very high-risk job and an increase demand for agricultural products from one side and steady increase in production cost and weather changes, on the other side, have motivated many to use insurance for agricultural products. Insurance plays an important role in influencing crop production and insured satisfaction or farmers. The purpose of this research is to find critical components in agricultural insurance. Based on an exploration of the literature review and interviews, the proposed study of this paper extracts 24 variables and using factor analysis, we select the most important factors, which are grouped in seven categories. The implementation of our factor analysis has revealed uncertainty, moderator, market equilibrium, risky environment, empowering factor, education, training, structural hazards and natural ecosystems as the most important factors influencing agricultural industry.

Measuring the relative performance of insurance firms plays an important role in this industry. In this paper, we present a two-stage data envelopment analysis to measure the performance of insurance firms, which were active over the period of 2006-2010. The proposed study of this paper performs DEA method in two stages where the first stage considers five inputs and three outputs while the second stage considers the outputs of the first stage as the inputs of the second stage and uses three different outputs for this stage. The results of our survey have indicated that while there were 4 efficient insurance firms most other insurances were noticeably inefficient. This means market was monopolized mostly by a limited number of insurance firms and competition was not fare enough to let other firms participate in economy, more efficiently.

Ranking insurance firms plays an important role on choosing the most appropriate company for receiving appropriate services especially long term insurances such as life insurances. The proposed model of this paper uses two well-known methods of CAMELS and RBC to rank 18 active private and governmental insurance firms in Iran over the period of 2009-2011. The results of Spearman test imply that there is no meaningful difference between these two methods for year 2010 and year 2011 and according to Freedman test, there is not meaningful difference between these two methods in any three years of 2009, 2010 and 2011. In summary, we can conclude that the results of both methods could be used in practice.