پژوهشنامه بیمه
سال بیست و ششم شماره 3 (پاییز 1390)

Insurers determine consumer’s risk class and life insurance rate by studying factors affecting mortality rates. But, the above-mentioned factors are observed only at Policy issue time and the impact of later changes are not considered.In this paper, a discrete-time multi-state model that surveys the changes of factors in a two year period after the conclusion of contract, is used. In order to study the influence of insured’s health status on the cancellation of life insurance contract, we considered the insured’s health status after conclusion of contract, as a risk factor in the model. Results show that there is a significant difference between mortality rates of insurdes of an insurance company, considering the impact of cancellation and without this consideration. The above-mentioned difference leads to different premium rates for each status.

In this reserch, we show that the delayed Sparre Andersen insurance risk model can be analyzed as a Markov chain and we will use it for calculate the ruin probability for insurance companies. Then we describe how matrix analytic methods can be used to establish a computational procedure for calculating the probability distributions associated with fundamental ruin related quantities of interest such as the time of ruin the surplus immediately before ruin and deficit at ruin. Our aim in this research is more computational in flavour. At the beginning, we will show how the delayed Sparre Andersen model can be set up as a doubly infinite Markov chain. After this definitions we wil use this model for our calculations and at the end we calculate ruin probability for one of the Iranian insurance companies by using this model.

Traditional insurance principles for insurability require that there should be sufficient demand to yield appropriate levels of income revenue for insurers to supply the coverage. We study the provision of earthquake insurance and investigate the number of factors influencing demand for earthquake insurance in metropolitan Tehran, Iran.We investigate whether individuals’ expected utility when insured is more than their expected utility when not insured. We also investigate empirically, the effect of individuals’ risk aversion on demand for earthquake insurance.The main results of this study are summarized as follows: First, the expected utility in the state of insurance is more than the expected utility in the state of no insurance. Second, the results show that individuals’ risk aversion is significantly related to demand for residential earthquake insurance.

Considering the importance of social interaction and innovation, in this paper we have examined the effect of social interaction on innovation in insurance companies. Statistical population of this study was private insurance companies in Tehran and 115 of this company's executives was selected. A standard questionnaire was used to collect data. Its validity was supported by experts and its reliability was investigated by Cronbach's alpha coefficient. Structural Equation Analysis was used to test the hypothesis. Considering the total results of the hypothesis test and standard regression can be argued that the administrative innovation in Iranian insurance companies has been forgotten, due to weakness in the knowledge acquisition phase, low level of social interaction between employees, lack of introducing service-providing methods and innovative service-providing processes as well as non-fundamental and necessary changes in organizational structures.

Fraud is one of the most important problems that impose huge losses to insurance companies. There are many ways to do fraud detection; one of them is analyzing the historical data of detected frauds. Nowadays, using data mining methods to find the patterns of data is in common. Using these methods could be useful to identify spurious claims. Here, in addition to surveying the common methods of fraud detection in Auto insurance, three special methods, namely, Logistic Regression, Naive Bayes and Decision Tree, are applied to real data including 72 Auto insurance claims and their efficiencies are evaluated. As a result, Naive Bayes method has been chosen as the best identifier of real or fraud claims with 90.28% accuracy. Decision Tree and Logistic Regression, respectively stand in the next places, with 88.9% and 86.1% of accuracy.

One of the tools that can play a major role in the booming the stock market is the insurance investment companies which are of much importance due to financing the main part of flows of financial resources. According to Fama, an efficient market is one that the new incoming information affects the stock prices quickly. One way to examine the efficiency in weak form is to test for random walk hypothesis. In this paper, the efficiency of the insurance Industry investment company was examined with the Richardson & Smith variance ratio test, Belaire-Franch & Contreras variance ratio test, and Kim Bootstrap variance ratio test. The results indicated the insurance Industry investment company is inefficient in weak form for the period May 1999 to November 2010. Therefore, we can conclude that the efficiency of the insurance Industry investment company does not hold.

This study aimed to investigate the relationship between transformational leadership and organizational innovation in an insurance company. The research method was descriptive-correlative and the statistical population consisted of all experts of Insurance Company,(520 persons), that 126 persons were selected randomly using Saraei formula. In order to collect data two questionnaire were used.1- transformational leadership questionnaire (a=./92), 2- Organizational Innovation questionnaire (a=./89), Pearson correlation and stepwise regression were used to analyze of data. finding showed that there are a positive relationship between transformational leadership and organizational innovation and its component Idealized Influence, Inspirational Motivation, Intellectual Stimulation, Individualized Consideration, Inspirational Communication, Vision and regression results show that transformational leadership’s components Idealized Influence, Intellectual Stimulation, Inspirational Communication can predict organizational innovation orientation in an Insurance Company.