Showing 8 results for Insurance
Dr Ghadir Mahdavi, Vahid Majed,
Volume 2, Issue 5 (10-2011)
Abstract
Life insurance as an investment and assurance tool provides a great source of investment financing in different economies. Despite life insurance development in advanced countries and in many developing economies, it could not get its appropriate share in Iranian family’s basket.
This paper investigates factors that affect life insurance demand in Iran. So, random sampling used to get required information in three provinces of Iran (Tehran, East Azerbayjan and Mazandaran).
Factors are divided into two main groups: Socioeconomics and psychological. Required data were gathered using questionnaire. Results show that life insurance demand has negative relationship with individual expected health condition, premium, expected inflation, degree of risk aversion and income. Bequest, economic optimism, age, employment of partner and reading has positive relation with life insurance demand. Based on the sample, result show that life insurance demand is not affected by advertisements but is affected by others recommendations.
Abolfazl Shahabadi, Mahsoomeh Ahmadi, Ali Moradi Ali Moradi,
Volume 9, Issue 31 (3-2018)
Abstract
The insurance industry as a means of transferring risk and paying damages, ensures the future and the confidence of individuals and as an investor's institution, It cumulation the saving resources and allocates it to the needs of investment and economic growth of the countries. Therefore, it is necessary to identify the factors influencing the development of this industry in countries with a low insurance penetration and action must be taken regarding reinforcement the increasing factors and Elimination its decreasing factors.In this regard, the present study has tried to determine the interaction between financial development and economic freedom indicators (total index, size of government, legal system and property rights, sound money, freedom to trade internationally and regulations) on the penetration insurance in Fifteen unsuccessful insurers will be insured over the period 2014-2000. For this purpose, the research model was estimated using panel data and generalized moment’s method. The results it shows the interaction of financial development and all index of economic freedom on insurance penetration the in selected countries have had a positive and meaningful. Also, the individual effect of financial development and total economic freedom index is positive and significant. However, their individual influence on the insurance penetration is less than their interaction. Finally, the effect of control variables including per capita income, human capital and urbanization rate on the insurance penetration in the selected countries have had a positive and meaningful and the effect of unemployment and inflation have had a negative and meaningful.
Mohammad Reza Monjazeb, Leyla Dehgani,
Volume 10, Issue 37 (10-2019)
Abstract
Life insurance is one of the most important economic instruments. Considering the important role of life insurance, this study investigates the life insurance capability in Iran. For this purpose, the Panel ARDL model has been used. Then, for the period 1990-2016, suitable models for the first group (Iran with the leading countries in the industry), the second group (Iran with the countries that were close to Iran in premiums) and the group Third (countries in two groups) were estimated. Based on models, the fitted value of life insurance premiums per capita in Iran is analyzed and compared as the potential or optimal level in each groups. The results showed that in each group, the actual life insurance premiums per capita in Iran are significantly lower than the optimal level. The capacity level of life insurance in Iran compared with first group is 46%, and compared with second group is about 42% and compared with third group is about 44%. The results indicate that Life insurance in our country has a high potential, and a large part of the insurance capacity in our country has not yet been fully acquired.
Abolfazl Shahabadi, Hossein Raghfar, Neda Solgi, Ali Moradi,
Volume 10, Issue 38 (12-2019)
Abstract
Insurance as a central risk-taking institution as well as one of the investment institutions increases economic participation, investment development and stimulating economic growth. Therefore, identification of the effective factors on the insurance penetration in developing countries seems necessary. In this regard, the present study attempted to investigate the impact of national competitiveness on insurance penetration coefficient in 20 developing countries during the period 2007-2017. The research model was estimated using panel data and generalized moment’s method in two case. In the first case, the sub-indicators of national competitiveness including basic requirements, efficiency enhancer’s factors and innovation and sophistication factors were used as key variables in the research, and in the second case, the overall competitiveness index is used as a key variable in the research model. The results showed that the effect of overall competitiveness index and its sub-indicators on insurance penetration was positive and significant. Also, the effect of control variables, including per capita income and urbanization rate on insurance penetration is positive and significant, and the effect of dependency ratio on insurance penetration is negative and significant.
Yasin Ghasemi, Abbas Khandan, Narges Akbarpour-Roshan,
Volume 13, Issue 47 (5-2022)
Abstract
The pension coverage of the Iranian Social Security Organization for self-employed workers is offered at three contribution rates of 12, 14 and 18 percent, but looking at the statistics shows that the demand for these types of insurances is low. This research investigates the characteristics of these insured groups by using data mining and applying two machine learning algorithms, decision tree and random forest, and predicts their behavior by providing a classification model. This will help the Social Security Organization to improve customer relationship management. For this purpose, the information of 1286174 insured persons of self-employed in 2020 was used, which includes the characteristics of age, gender, average monthly income, the years of service, and the type of self-employed pension scheme. The obtained results show that women mainly apply for the scheme with 12 percent contribution, while men tend to be covered by schemes with contribution rates of 14 and 18 percent due to the burden of supporting the family. Also, for men, the demand for schemes of 14 and 18 percent increases with the increase of age, income and years of service, but there are no such trends for women. According to the obtained results, years of service and then gender are decisive in choosing the type of pension scheme in such a way that according to the prediction of the model, people with less than 4.5 years of service are known as definite applicants for 12 percent self-employed pension scheme.
Dr Samira Motaghi, Dr Yegane Mosavi Jahromi, Mr Mohammad Amin Taheri Gorgani,
Volume 14, Issue 51 (5-2023)
Abstract
Purpose: The insurance penetration rate is one of the most important indicators used to evaluate the insurance industry of a country. This ratio is also a measure to compare the performance of the insurance industry between developed and developing countries. The aim of this research is to compare the insurance penetration rate and the factors affecting it in high and low income countries.
Methodology: The current research examines the effect of variables such as inflation rate, education, labor productivity, dependency ratio and income on the insurance penetration rate in the period 2011-2021 and using PMG and ARDL methods to derive short-term and long-term equations in 18 countries with income High and low income and the country of Iran pays.
Findings: The results obtained from the estimation of long-term PMG models in high-income countries indicate a positive effect of dependency ratio, income level and fertility level on the insurance penetration rate, as well as a negative effect of inflation rate and labor productivity on the dependent variable, also in selected countries with high income. All the variables, except for education and dependency ratio, which had a positive and significant effect on the insurance penetration rate, are statistically meaningless. On the other hand, the findings from the estimation of the long-term ARDL model in Kesho Iran show the negative impact of the inflation rate on the insurance penetration rate and the positive impact of the education level, income level and dependency ratio on the insurance penetration rate.
English Habib Habib Shirafken Lamso, English Amir Gholami, English Seyyed Mehdi Ahmadi,
Volume 14, Issue 52 (9-2023)
Abstract
This research aims to model the effective systematic risks of financial recovery in the insurance industry. This research is a type of applied research. The period of research is 11 years (1400-1390). For this purpose, the information on 14 systematic risks affecting the financial solvency of insurance companies was entered into dynamic, selective, and Bayesian averaging models. Based on the error rate, the Bayesian averaging model had the highest accuracy among the selected models. After estimating the model, 5 economic growth risks, inflation uncertainty, exchange rate, sanctions, and KOF index were selected; Also, based on the results of the TVPFAVAR model, it was assessed that the impact shock of the selected variables in the long-term period is stronger than the short-term period, which indicates that the elasticity of financial prosperity is greater than the changes in systematic risk variables compared to the short-term elasticity. Based on the results of economic growth and the KOF index, the positive effect and uncertainty variables of inflation, exchange rate, and sanctions hurt financial wealth in the general trend.
, Abbas Khandan,
Volume 14, Issue 52 (9-2023)
Abstract
Purpose: The aim of this study is to identify and classify insurance customers in order to identify the target population for increasing the profitability of insurance companies, achieving a balance in premium payments, and examining the health questionnaire as an indicator of policyholders' preferences. Moreover, designing a marketing strategy to optimize advertising efficiency.
Method: In this paper, five machine learning algorithms, namely Decision Tree, Random Forest, Support Vector Machine, Naive Bayes, and Logistic Regression, are used to classify customers into two categories: profit-generating and loss-generating. Data from a private insurance company is utilized, consisting of 2,897 observations collected from December 1400 to December 1401.
Findings: By utilizing machine learning methods and focusing on the target population, the chances of success can be increased. The presence of a small number of individuals who significantly reduce the profitability of insurance companies is evident. The pre-existing medical conditions of individuals have a considerable impact on their insurance usage and the damage caused to insurance companies.
Conclusion: Machine-learning methods can provide a comprehensive understanding of insurance customers and their needs. By identifying the target population, insurance companies can increase their profitability and satisfy their customers by addressing their specific demands
