پژوهشنامه بیمه
سال سی و یکم شماره 3 (پاییز 1395)

Organizational vision and mission statements and goals are major indices for the orientation of an organization. In this study, using modern text mining techniques combined with K-means clustering techniques, the vision, mission and goals of 39 international insurance companies (top 500 companies of the world list) and 18 Iranian insurance companies have been analyzed. The results indicate that the international companies and Iranian companies can be classified into four clusters, including financial security, value, service, product-service, quality for the former groupand professionalism, peace of mind, profitability (financial) and services providing for the latter group. Finally, the international companies are aligned with the domestic companies in some issues. However, in many issues the type of perspective to these documents and their wording is different.

The conventional theory of adverse selection in markets with asymmetric information expects that the anti-choice phenomenon occurs. Hence, bad products beat good products out of the market. Consequently, a reduction in market efficiency may lead to market failure. Insurance market is among the markets in which this phenomenon can happen. However, in the 90s a number of researchers reported occurrence of advantageous selection in the insurance market. These researchers have shown that if by focusing on risk aversion of individuals and their willingness to do precautionary effort, a negative correlation exists between risk aversion and risk taking, and also between coverage and claim and a positive correlation is observed between precautionary effort and coverage, then we can conclude that there is an advantageous selection in that field of insurance; so claims of omission of good customer from the market with asymmetric information will be rejected. This paper examines the advantageous selection in the Iranian automobile collision insurance market and concludes that there exists considerable advantageous selection behavior in this market and precautionary efforts affects market performance and prevent market failure.

Sale agents are fundamental factors for the insurance industry’s ongoing operation. They act as a bridge between the organization and customers. Communication is the necessary ability of each seller; but some factors lead to a level of communication apprehension. In the current research, the objective is to identify factors affecting communication apprehension. The research method is participant selection mixed method which has been done in two phases: qualitative and quantitative. The research statistical population is an insurance company’s agents, operating under the control of a district in Ahvaz city. Based on Morgan table, 86 individuals were selected randomly and the questionnaire distributed among them. The purpose of this phase is to determine agents with higher communication apprehension based on Mccroskey questionnaire. Based on the results of the 1st phase, the agents had a low grade in communication apprehension, so agents with higher grade in communication apprehension were selected for in-depth individual interview. In the 2nd phase, answers were investigated by using thematic analysis and three factors were revealed. The factors identified as affecting communication apprehension are individual factors: agent characteristics, motivation, knowledge, experience; environmental factors: third person, costumer; and institutional laws relating to insurance, training, issues of agents and staff of company. Finally, recommendations for solving the aforementioned factors were presented.

Various kinds of recoverable damages and the method by which the mentioned damages could be recovered are among the issues that have been addressed by the conventions on nuclear liability. The provision of financial guarantees, as one of the principles of nuclear civil liability, is regarded as the most important loss compensation method. The worldwide acceptance of insurance has led to the approval of relevant rules in the conventions. Insurance only covers damages which have been enumerated in the related conventions. Bodily and financial damages under the preceding conventions and new titles of nuclear damages such as lucrum interceptum and pure economic losses under the contemporary conventions have been stated as recoverable. It appears that pure economic losses are recoverable through the generalities of tort rules such as La’Zarar, according to the Iranian law. Nuclear installations operators have limited liability under conventions or domestic laws; however, Iran’s law has no specific provisions regarding the civil liability arising from nuclear accidents and is not a signatory to any of the conventions as well; thus, general principles of liability could be invoked, that of course based on which the liability is unlimited; therefore, formulation of a particular law or membership in the pertinent conventions is essential in order for exploiting insurance facilities.

Unemployment Insurance (UI) fraud is an important topic in social insurances which is regarded by law as a penal offense. The best way for fraud evaluation is to prevent and control it at early steps, using previous unfolded fraud documents. In this paper, first of all, the fraud control diagram is depicted, then according to the existence of an appropriate database of social security of UI claimants, two modern data mining techniques have been used for data analysis. The Neural Networks and Decision Tree algorithms create models which have been used for evaluating UI benefits fraud. These obtained models will provide an appropriate opportunity for social insurance authorities to have better conceptual understanding and effective combat against all kinds of insurance fraud, clearly just on time. According to several empirical studies, two obtained models have been applied on real data of 15983 records including new and current UI claimants. The accuracy and efficiency of each model have precisely examined. Indicated results show that the Neural Networks model take the first place by 88% of accuracy and the second place is for Decision Tree model by 84% of accuracy. The most important predictors which build each model for fraud pattern recognition, consist of the insured’s previous occupation, paid premium record and age in Neural Networks and branch’s geographic location, gender and the numbers of sponsorships in Decision Tree.

Uncertainty and volatility are among important topics in capital markets. Since volatility may lead to increased uncertainty and ultimately bankruptcy and exit from the capital market; choosing the optimal investment portfolio reduces anxiety about investment in the future. This study is set to determine the optimal combination of an Insurance Companie's investment portfolio in Tehran Stock Exchange during 2009-2013. To select the optimal combination of investment portfolio, we have used the single index sharp model which is the most efficient model for optimal portfolio, selection. This study is an analytical- descriptive research using Persian and English books and articles to develop theoretical principles and basic concepts.
Financial statements of Dana Insurance Company have been used for model estimation. We used SPSS19 software in order to estimate the model and data analysis. The results show that 19 out of 33 companies in the Dana Insurance Company investment portfolio, have the largest share. In order to determine the optimal frequency between current and optimal portfolio a sample t-test is used. Accordingly, 19 hypotheses were examined. The results indicate that a significant difference exists between current and optimal investment combination of aforementioned insurance company. Finally, the share of each of the 19 companies in new portfolio combination is determined.