Original Research Paper
Loss adjuster in insurance
I. Raeesi Vanani; M. Taghavifard; B. Sohrabi; M. Amirhosseini
Original Research Paper
Insurance pricing
A. Khandan; L. Niakan; Z. Fakharinezhad
Abstract
BACKGROUND AND OBJECTIVES: Life insurance has a very low adoption rate in Iran, mainly due to policy surrender. This research aims to analyze the individual characteristics and insurance contract features that influence the surrendering of term life insurance policies.METHODS: The study utilizes a pilot ...
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BACKGROUND AND OBJECTIVES: Life insurance has a very low adoption rate in Iran, mainly due to policy surrender. This research aims to analyze the individual characteristics and insurance contract features that influence the surrendering of term life insurance policies.METHODS: The study utilizes a pilot database of 35,171 policy-holders and pensioners registered by an Iranian insurance company in 2021. Data mining, deep learning, and neural network algorithms are used for analysis due to their high accuracy in prediction:FINDINGS: The model demonstrates desirable performance based on evaluation metrics with a 74 percent accuracy in predicting both types of surrendered and non-surrendered insurance policies. The model performs better in predicting non-surrendered insurance policies more attention is given to interpreting those results. Despite imbalanced data, the model still performs well. In the dataset, surrendered policies make up only 3 percent of the total, leading to bias towards predicting the majority class. Nonetheless, the model accurately predicts and categorizes most surrendered policies, covering 59 percent of the total 244 cases.CONCLUSION: The results indicate that certain demographic characteristics, such as age, female gender, health surcharge, and accident risk rate, as well as specific contract characteristics, including policy term, time since start date, longer premium payment methods, higher annual increase in capital and premium, fewer covered risks, and lower benefits, are negatively correlated with policy surrender. Furthermore, the results suggest that if the insured person is the policy surrender themselves, the probability of surrender is minimized. On the other hand, if the insured person is someone else, especially distant relatives, the probability of surrender increases.
Original Research Paper
Loss adjuster in insurance
A. Shakouri; M. Izadi; B.E. Khaledi
Abstract
BACKGROUND and OBJECTIVE: V, a loss reserve is a prediction of the amount an insurer will need to pay for future claims. Researchers have been exploring methods to incorporate dependencies among multiple loss triangles to improve the accuracy of outstanding claim prediction. This study aims to predict ...
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BACKGROUND and OBJECTIVE: V, a loss reserve is a prediction of the amount an insurer will need to pay for future claims. Researchers have been exploring methods to incorporate dependencies among multiple loss triangles to improve the accuracy of outstanding claim prediction. This study aims to predict outstanding claims in dependent run-off triangles by considering the dependence among the outstanding claims paid in each run-off triangle.METHODS: The study considers the dependence among corresponding outstanding claims in run-off triangles related to different lines of insurance. It also takes into account the calendar year of payment of claims, in addition to factors such as the year of claim occurrence and the number of years of delay in payment. Two methods are used to model the inter-triangular and intra-triangular dependencies. The first method involves modeling the dependence among triangles by using a multivariate distribution for outstanding claims in the corresponding cells of run-off triangles. The calendar dependence within each run-off triangle is incorporated by adding a calendar year effect factor to the mean of the outstanding claims distribution. The second method uses a multivariate distribution for the outstanding claims of the calendar years corresponding to run-off triangles, capturing both types of dependence. Bayesian approach and Hamiltonian Monte-Carlo sampling methods are employed to estimate model parameters.FINDINGS: The study utilizes data from an Iranian insurance company on outstanding claims in car body insurance and third-party car insurance from 2012 to 2015. The two methods of calendar dependence modeling are compared using a scale mixture multivariate distribution with normal marginal distributions and copula dependence. The mean absolute percentage error is used to measure the accuracy of the prediction. The results show that using a multivariate distribution for calendar dependence modeling leads to a more accurate prediction compared to adding the calendar year effect factor to the mean model.CONCLUSION: Based on the findings, it is concluded that modeling the calendar dependence among outstanding claims in run-off triangles using a multivariate distribution improves the accuracy of reserves prediction compared to using the calendar year effect factor. This approach can enhance the prediction of outstanding claims and contribute to the insurer's profitability and solvency.
Original Research Paper
financial markets
H. Shirafkan Lamso; A. Gholami; S.M.M. Ahmadi
Abstract
BACKGROUND AND OBJECTIVES: This research aims to develop a new approach to modeling systematic and unsystematic risks as well as geopolitical risks, in financial solvency within the insurance industry in Iran. The objective is to improve the accuracy of prediction models used in the industry..METHODS: ...
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BACKGROUND AND OBJECTIVES: This research aims to develop a new approach to modeling systematic and unsystematic risks as well as geopolitical risks, in financial solvency within the insurance industry in Iran. The objective is to improve the accuracy of prediction models used in the industry..METHODS: The research follows developmental-practical approach and unilizes a descriptive-survey method. Data from 2011 to 2021, covering an 11-year period, were collected and analyzed. A total of 33 risk indicators affecting the financial solvency of insurance companies were examined using BMA, TVP-DMA, TVP-DMS, and BVAR models.FINDINGS: The BMA model demonstrated the highest accuracy based on error rate. Through the analysis, 11 main variables were identified as significant factors influencing financial solvency including economic growth, inflation uncertainty, exchange rate, sanctions, KOF index, return on working capital, cash adequacy ratio, total debt-to-equity ratio, loss factor, Herfindahl-Hirschman index, and geopolitical risk. The results The results highlight the complex nature of financial solvency prediction in the insurance industry, emphasizing the need for a comprehensive and systematic approach.CONCLUSION: This study emphasizes the limitations of relying on a single conceptual model in financial solvency modeling and decision-making. The multiplicity of factors influencing financial solvency requires a systemic perspective in managing insurance companies. Additionally, it is important to consider a wide range of variables rather than relying on a specific model or set of variables to ensure a comprehensive understanding of financial solvency in the industry.
Original Research Paper
Insurance Social Studies
M. Shakouri; T. Shiri; R. Mohseni
Abstract
BACKGROUND AND OBJECTIVES: Welfare policies are an essential aspect of government management in societies. This study aims to analyze the discourse of welfare policy in the Labor Law and the Unemployment Insurance Scheme during the Covid-19 pandemic.METHODS: The research method used in this study is ...
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BACKGROUND AND OBJECTIVES: Welfare policies are an essential aspect of government management in societies. This study aims to analyze the discourse of welfare policy in the Labor Law and the Unemployment Insurance Scheme during the Covid-19 pandemic.METHODS: The research method used in this study is discourse analysis, based on the approach developed by Laclau and Mouffe. The texts of the Labor Law and the Unemployment Insurance Scheme during the Covid-19 pandemic were analyzed.FINDINGS: Iran has implemented welfare policies and programs since the 1979 Revolution. However, the discourse surrounding welfare policy in the field of unemployment insurance has varied among different governments. The mechanisms of welfare policy in terms of unemployment relief and job creation have changed over time. The discourse governing the Labor Law emphasizes "full employment social policy," while the discourse surrounding the Unemployment Insurance Scheme during Covid-19 focuses on "applying a comprehensive support policy”.CONCLUSION: The discourse approaches to unemployment and related supports in Iran, as reflected in the Labor Law and the Unemployment Insurance Scheme, center around "deserved justice" for accessing short-term social security services. This means that only individuals covered by specific laws are entitled to insurance support, excluding those who do not meet certain criteria. This approach contradicts Article 29 of the Constitution, which emphasizes that social security is a universal right that should be provided for all members of society using public resources. This highlights the need for a more inclusive and comprehensive approach based on distributive justice.
Original Research Paper
New Insurance Technologies
M. Yahyazadehfar; A. Najafpour; M. Shirkhodaie; J. Soltanzadeh
Abstract
Background and Objective: The development of new financial markets, such as insurtech, has become a focus for researchers and policymakers. This study aims to identify the challenges faced by insurance companies in Iran in adopting insurtech.METHODS: The research method was qualitative and data ...
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Background and Objective: The development of new financial markets, such as insurtech, has become a focus for researchers and policymakers. This study aims to identify the challenges faced by insurance companies in Iran in adopting insurtech.METHODS: The research method was qualitative and data was collected through theoretical study, literature review, and interviews with experts. Qualitative content analysis was conducted using MAXQDA software. The credibility of the analysis was assessed using data-oriented reliability. The study population included managers of insurtech businesses in Iran.Findings: Through interviews, consensus was reached on various challenges. After coding, 52 initial indicators were identified, leading to the identification of 21 subcomponents and 12 main components. The credibility of the coding was confirmed using the Kappa test. The identified dimensions and factors included culture, integration, training, conflict of interests, financial issues, management structure, infrastructure, regulations, neglect of innovation and new products, lack of investment, taxes, and contracts. The experts predicted the strongest consensus among conflict of interests, management structure, regulations, infrastructure, culture, and training.Conclusion: The challenges and barriers to adopting insurtech in Iran can be categorized into macro and micro levels. At the macro level, there are obstacles related to laws, regulations, monopolies, and infrastructure that require government attention. At the micro level, obstacles include organizational interests, culture, structure, infrastructure, and training that should be addressed by organizational managers. Without proper implementation of these factors, insurtech activities cannot thrive in Iran. The proposed framework can assist managers and policymakers in addressing these challenges.
