Original Research Paper
Marketing and Sales
Masoud Taheri Vesiesari; Zahra Jaferi; Zahra Bardal
Abstract
BACKGROUND AND OBJECTIVES: In today’s highly competitive environment, branding has become one of the most critical strategic factors for the success of companies across diverse industries. Although branding is often primarily associated with tangible products, its significance in the service industry ...
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BACKGROUND AND OBJECTIVES: In today’s highly competitive environment, branding has become one of the most critical strategic factors for the success of companies across diverse industries. Although branding is often primarily associated with tangible products, its significance in the service industry is equally vital. Especially in sectors driven by service delivery, such as insurance, effective branding goes far beyond surface-level marketing—the process involves multiple, often hidden, internal and external factors that can shape and enhance brand equity. The present study aims to identify the factors influencing branding and brand equity in the insurance industry, particularly from the perspective of employees as key organizational stakeholders. Employees’ viewpoints are of special importance in the context of branding, since they are not only the executors of organizational policies but also serve as the real ambassadors of brands in their interactions with clients. By delivering positive workplace experiences, demonstrating professional behaviors, and committing to corporate values, employees can have a significant and lasting effect on customer perception and the overall mental image of brands. They are the true link between the internal organizational culture and the external market environment.METHODS: This research adopts a mixed methodology, utilizing both qualitative and quantitative approaches in a complementary manner. By combining these methods, the study aims to harness the strengths of each to achieve a more comprehensive understanding of the issues at hand. In the qualitative phase, the researchers conducted a thorough review of the literature, examining established theories and previous research to build the conceptual and theoretical framework for the study. In the quantitative phase, the statistical population consisted of experts and professionals in the insurance industry. These participants were chosen through a judgmental purposive sampling method, meaning that individuals with necessary expertise, knowledge, and relevant experience were deliberately selected to enhance the reliability of the findings. The primary data collection tool in the quantitative section was the Fuzzy Delphi method. The Fuzzy Delphi method enables researchers to gather and refine professional opinions through a series of iterative rounds and is particularly effective for developing a consensus in complex contexts. In this approach, participants answer questions anonymously over multiple rounds, with opportunities to modify their previous responses after seeing the summarized findings from earlier rounds—resulting in more accurate and validated outcomes.FINDINGS: Through the application of the Fuzzy Delphi technique, the study identified 34 variables perceived by employees as influential on branding and brand equity. Out of these, 26 variables were confirmed in the first round, while 8 were rejected after further evaluation. Notably, responses to open-ended questions in the initial Delphi round led to the identification of 5 new variables, highlighting the dynamic nature of employee input and expertise. Ultimately, these variables were grouped into 9 main categories: employees’ experience of the employer brand, employees’ perceptions of the brand as seen by customers, employer brand and its competitors, employees’ brand knowledge, employees’ commitment to the brand, organizational citizenship behavior, word-of-mouth advertising, employee satisfaction, and employees’ intention to stay with the organization. This categorization demonstrates that shaping a strong brand image is a holistic process, not only reliant on leadership or marketing teams but also fundamentally shaped by everyday staff at all organizational levels. Factors such as personal satisfaction, supportive behaviors, effective interaction with both clients and competitors, and the transmission of a positive organizational message to the outside world are shown to be indispensable.CONCLUSION: The analysis and ranking of variables confirmed through various rounds of the Fuzzy Delphi method indicate that, from employees’ perspectives, the most influential factors contributing to branding and brand equity in the insurance industry are: a supportive and appropriate work environment, genuine passion and enthusiasm for the brand, and opportunities for professional and personal growth—ranked as the top three enablers of brand success Additional factors, including employees’ willingness to exert extra effort, their conversations with competitors about the organization, and their refusal to accept new job offers, while still important, were placed lower in the ranking (positions 18 to 20). Overall, the findings underscore that special attention to employees’ needs, aspirations, and attitudes, the strengthening of organizational values, and the creation of a dynamic and motivating environment for staff development and satisfaction are paramount to building a successful brand, particularly in service-oriented industries like insurance. These insights offer practical guidance to senior managers, policymakers, and HR specialists for designing and implementing effective and forward-thinking strategies in organizational branding.
Original Research Paper
Risk assessment in insurance
Mona Parastesh; Ziaeddin Beheshtifard; Abbas Raad
Abstract
BACKGROUND AND OBJECTIVES: The role of the insurance industry is changing nowadays. The reason is that companies are using new analytical methods to predict losses and risks, and these methods help them assess potential risks. In this era, traditional business models and old methods have always been ...
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BACKGROUND AND OBJECTIVES: The role of the insurance industry is changing nowadays. The reason is that companies are using new analytical methods to predict losses and risks, and these methods help them assess potential risks. In this era, traditional business models and old methods have always been under threat from technology. New insurance companies are using the power of innovative technologies to eliminate the traditional leaders of the insurance market. The protection provided to the insured against risks and the proposed solutions provided to deal with risks are obtained through services designed to identify potential risks, and these services can be used to warn of danger (in high-risk cases). As a result, these services will be the most important distinction of these companies and the key to their success in the future. Powerful artificial intelligence and analysis of large volumes of big data give insurers the power to move towards predicting losses and incidents. The more information insurance companies have about their policyholders, the better they can use these valuable data to predict policyholders’ behavior and create a historical profile for each individual, thereby reducing the volume of claims and associated risks. Insurance companies enjoying leverage innovative technologies have a significant opportunity for growth. However, those that continue to rely on basic questions such as age, gender, and occupation to determine premiums are unlikely to survive in the digital era and amidst the rise of insurtech. Insurers that fail to adopt predictive analytics and continue to use outdated traditional systems may experience longer delays in processing and paying claims compared to innovative companies. This gap will allow tech-driven insurers to attract more customers and cover a wider range of policyholders in the long term. Insurance data often contains nonlinear and complex relationships that simple models—such as linear regression or decision trees—cannot fully capture or model effectively. These companies are also faced with vast volumes of data. Traditional methods such as general linear models often fail to identify complex patterns in insurance data. Therefore, we seek to improve existing methods by applying modern techniques such as deep learning, since deep neural networks can more accurately identify complex patterns in insurance data, process large datasets efficiently, and uncover hidden insights. Deep learning, with the ability to identify nonlinear relationships and complex patterns, can overcome these limitations. In this paper, a method to improve the performance of deep learning using sequential deep regression techniques is presented. The proposed approach is a combination of deep learning and sequential models. Long Short-Term Memory (LSTM) neural networks are used to model time series data.METHODS: In this study, data spanning the past seven years from Alborz Insurance Company—specifically related to the issuance and loss records of fire insurance policies—has been systematically utilized to analyze and forecast potential losses in this domain. The methodology places a strong emphasis on comprehensive data pre-processing, including cleaning, normalization, and transformation to ensure the reliability and quality of the input data. In the feature engineering stage, various techniques were applied to extract the most informative and relevant attributes from the raw dataset. Out of a total of 40 initially selected features, the top 20 features were identified through statistical analysis and machine learning-based selection methods. These refined features were then used to train the deep learning models. The proposed method is a hybrid approach that combines deep learning with sequential modeling techniques. Specifically, Long Short-Term Memory (LSTM) neural networks were employed due to their ability to capture time-dependent patterns in sequential data, making them particularly suitable for modeling the temporal dynamics inherent in insurance data over multiple years. FINDINGS :The study involved the evaluation and comparison of multiple machine learning algorithms, including traditional models and advanced deep learning techniques. The results demonstrated that the proposed sequential deep regression approach significantly outperforms conventional models such as general linear models and decision trees. Notably, the LSTM-based model provided higher prediction accuracy and demonstrated superior performance in identifying complex, nonlinear patterns within the data. Key findings highlight the critical role of temporal features in enhancing prediction reliability and show that incorporating time series analysis is essential for improving the accuracy of damage occurrence forecasts in fire insurance. CONCLUSION: The results of this research underscore the effectiveness of combining deep learning techniques with sequential models for predicting fire insurance losses. Using the confidential and comprehensive issuance and claims dataset from Alborz Insurance Company over seven years, the proposed hybrid model was capable of delivering better performance in comparison to previous methods. The approach not only improved the precision of predictions but also offered a more robust and scalable solution for risk assessment. Overall, the use of LSTM-based deep learning models represents a significant advancement in the insurance industry’s ability to make data-driven decisions regarding premium setting, policy issuance, and risk mitigation strategies.
Original Research Paper
Corporate Governance in Insurance Companies
Yassaman Khalili; Maryam Sadeghi; Abdolkhalegh Khonaka; Abolfazl Momeni Yanesari
Abstract
BACKGROUND AND OBJECTIVES: Insurance companies serve as critical components of every financial system, acting as key players in risk management and providing essential financial security for individuals, businesses, and other legal entities. By offering products such as life insurance, property coverage, ...
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BACKGROUND AND OBJECTIVES: Insurance companies serve as critical components of every financial system, acting as key players in risk management and providing essential financial security for individuals, businesses, and other legal entities. By offering products such as life insurance, property coverage, and health plans, these companies help mitigate economic uncertainties and promote stability in markets. However, with growing scrutiny on corporate practices, the role of monitoring mechanisms like the audit committee and internal audit quality has become increasingly vital. The audit committee, functioning as an independent oversight body within corporate governance frameworks, is responsible for supervising financial reporting, internal controls, and compliance with regulations. Its effectiveness can significantly influence the quality of non-financial disclosures, such as social responsibility reports, which detail a company's environmental, social, and governance (ESG) impacts. Similarly, internal audit quality—encompassing the rigor, independence, and competence of internal audit functions—serves as a cornerstone of corporate governance by ensuring the accuracy, transparency, and completeness of reported information. In the context of social responsibility reporting, these mechanisms help verify that companies adhere to ethical standards, sustainability goals, and stakeholder expectations. Given the rising importance of social responsibility in the insurance industry—particularly in Iran, where regulatory pressures and public awareness are increasing—this study aims to investigate how the effectiveness of the audit committee and the quality of internal audit performance may influence social responsibility reporting. By focusing on the Iranian insurance companies, the research addresses a gap in understanding how robust governance structures can enhance accountability and trust in an industry that deals with public funds and societal well-being.METHODS: This study adopts a correlational research design, which involves examining the relationships between variables without manipulating them, making it suitable for exploring associations in real-world settings. Hypothesis testing was conducted using multivariate regression analysis, a statistical technique that allows for assessing the simultaneous impact of multiple independent variables (such as audit committee effectiveness and internal audit quality) on a dependent variable (social responsibility reporting). The research is classified as applied in terms of purpose, meaning it seeks to generate practical insights that can inform real-world decision-making, rather than purely theoretical contributions. The approach is framed within inductive reasoning, where specific observations from the data are used to draw broader generalizations. The statistical population consists of all insurance companies operating in Iran, including a diverse range of firms from state-owned to private entities. To ensure relevance and timeliness, the sample period spans from 1398 to 1402 (corresponding to the Persian calendar years, or approximately 2019 to 2023 in the Gregorian calendar). Data collection likely involved reviewing annual reports, corporate governance disclosures, and other publicly available sources, with variables operationalized through established metrics (e.g., audit committee independence, expertise, and audit committee size for effectiveness and internal audit quality indicators such as internal audit size, age, and competence for internal audit performance). This methodological rigor helps establish reliable cause-and-effect relationships while controlling for confounding factors.FINDINGS: The empirical results from the hypothesis testing reveal a significant and positive relationship between both audit committee effectiveness and internal audit performance quality, and the enhancement of social responsibility reporting. Specifically, higher levels of audit committee effectiveness—characterized by factors such as member independence, financial expertise, and audit committee size —were found to correlate with improved reporting quality, leading to greater transparency, accuracy, and reliability in disclosures. For instance, an effective audit committee may enforce stricter review processes that ensure social responsibility reports accurately reflect a company's efforts in areas like community engagement, environmental sustainability, and ethical practices. Similarly, superior internal audit quality, which includes thorough risk assessments, unbiased evaluations, and timely reporting, directly contributes to the integrity of these reports by identifying and rectifying discrepancies or omissions. Overall, the findings underscore the importance of a strong corporate governance infrastructure in fostering social accountability. By bolstering stakeholder trust—such as that of investors, regulators, and the public—these mechanisms not only comply with legal requirements but also promote long-term sustainability in the insurance sector. The positive effects observed in this study highlight how investments in governance can yield tangible benefits, particularly in an industry like insurance, where public perception and ethical conduct are crucial for maintaining credibility.CONCLUSION: This research provides valuable empirical evidence that enriches the existing literature on social responsibility reporting and corporate governance, with a specific focus on the insurance industry in Iran. By demonstrating the positive impacts of audit committee effectiveness and internal audit quality, the study offers actionable insights for stakeholders. For policymakers and regulatory bodies, such as the Central Bank of Iran or the Securities and Exchange Organization of Iran, these findings can guide the development of enhanced governance standards and reporting mandates. Managers of insurance companies can use this information to prioritize governance improvements, potentially leading to better risk management and reputational gains. Furthermore, the results emphasize the need for ongoing monitoring and potential reforms in corporate practices to align with global sustainability trends. While the study contributes significantly to understanding these dynamics in an Iranian context, it also opens avenues for future research, such as comparative analyses with other industries or countries, to explore additional factors influencing social responsibility reporting. Ultimately, by promoting transparency and accountability, this work supports broader goals of ethical business practices and sustainable development in the financial sector.
Original Research Paper
Corporate Governance in Insurance Companies
Mona Parsaei; Leili Niakan; Parasto Mostafaei; Tooba Haghighat
Abstract
BACKGROUND AND OBJECTIVES: The purpose of drafting regulations and disclosure requirements, both for supervisory bodies and for the public, is to reduce information asymmetry, enhance transparency, and improve comparability to boost market efficiency and regulation. The International Association of Insurance ...
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BACKGROUND AND OBJECTIVES: The purpose of drafting regulations and disclosure requirements, both for supervisory bodies and for the public, is to reduce information asymmetry, enhance transparency, and improve comparability to boost market efficiency and regulation. The International Association of Insurance Supervisors (IAIS) is the global standard-setting body for the insurance industry, comprising supervisory and regulatory authorities from over 200 jurisdictions across 140 countries, representing approximately 97% of the world’s insurance premiums. One of its main objectives is to develop and promote supervisory standards and guidelines for the insurance sector, covering various aspects such as solvency assessment, risk management, and corporate governance. In addition, the European Union Directive EC/138/2009, known as Solvency II, provides a comprehensive regulatory framework for insurance companies operating within EU member states.The insurance regulatory body in each country enacts laws and regulations regarding information disclosure to protect the rights of stakeholders. Given the necessity of determining the level of reporting and disclosure regulations for insurance companies, the present study aims to develop reporting and disclosure components in Iran. The “Regulation No. 88 on Reporting and Disclosure of Insurance Institutions,” enacted by the High Council of Insurance, currently serves as the legal basis for mandatory information disclosure by all insurance companies in Iran. Under this regulation, insurance companies are obliged to report information regarding their business plan, corporate governance, risk management, and solvency position, as well as their financial status and performance, to the regulatory authority — the Central Insurance of the Islamic Republic of Iran. In addition, they must publicly disclose this information on their official websites.METHODS: This applied research was conducted in three stages. In the first stage, the challenges of Regulation No. 88, ratified by the High Council of Insurance and titled “Reporting and Disclosure of Information by Insurance Institutions”, were identified through interviews and content analysis. The snowball sampling method was employed, and data collection continued until theoretical saturation was reached. In the second stage, by reviewing reporting and disclosure regulations in Iran’s insurance industry, international regulatory frameworks, the European Union, and selected countries, relevant reporting and disclosure components were extracted through document and content analysis. Finally, in the third stage, the proposed components were refined and validated using expert opinions gathered via a questionnaire, applying the Fuzzy Delphi method to reach a consensus. To quantify the responses, a five-point Likert scale with fuzzy triangular numbers was applied. Based on the structure and logic of the questionnaire, two types of five-point Likert scales with different verbal anchors were used: one ranging from “strongly agree” to “strongly disagree,” and the other from “very important” to “not important at all.”FINDINGS: The results are analyzed in three sections: "Fundamental Concepts," "Key Principles in Determining Reporting and Disclosure Requirements," and "Review and Evaluation Process by the Supervisory Authority." The findings in the first section indicate that reported information should have qualitative characteristics and be understandable to users. In the second section, the results show that a precise framework should be developed and implemented. Additionally, a supervisory plan should be designed to determine the frequency and scope of monitoring the reporting process. In the third section, the findings emphasize the corporate governance framework and the importance of analyzing board meeting minutes, auditors' reports, and ownership structure evaluations. Furthermore, risk management reporting should include a risk appetite statement, a risk management strategy, and a business plan addressing significant risks over three years, along with the internal capital adequacy assessment process. For public disclosure, the study identified key indicators such as company specifications, corporate governance framework, technical reserves, financial instruments, and other investments, underwriting, investment, and liquidity risks, asset-liability management, capital adequacy (solvency), financial performance, and corporate sustainability.CONCLUSION: This study provides a descriptive overview of the current regulations on reporting and disclosure in the insurance industry in Iran and globally. It also offers guidance for developing a reporting and disclosure model tailored to the Iranian insurance industry.To improve supervisory processes and enhance transparency and the quality of information for reporting and disclosure purposes, it is recommended that a comprehensive database for public reporting and disclosure be designed. Information should be categorized into tiers, and a precise reporting and disclosure timeline should be announced accordingly. Additionally, the components of reporting and public disclosure should be revised, and a practical guideline for the regulatory framework should be developed. This guideline should clearly define the elements of reporting and disclosure to promote greater transparency and improve comparability across insurance institutions.
Original Research Paper
Economics of finance / insurance
Zaniyar Ghorbani; Parvin Alimoradi Afshar; Ali Fegheh Majidi; Zanko Ghorbani
Abstract
BACKGROUND AND OBJECTIVES: The insurance industry constitutes a fundamental pillar in the economic infrastructure of any nation, fulfilling a critical function in the systematic management of diverse risks encountered by individuals, households, and businesses. By providing comprehensive insurance coverage, ...
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BACKGROUND AND OBJECTIVES: The insurance industry constitutes a fundamental pillar in the economic infrastructure of any nation, fulfilling a critical function in the systematic management of diverse risks encountered by individuals, households, and businesses. By providing comprehensive insurance coverage, this sector safeguards stakeholders against potential financial losses arising from unforeseen events, thereby actively contributing to economic stabilization and long-term sustainability. In economies characterized by elevated uncertainty and volatile conditions – such as those experiencing frequent macroeconomic shocks or political instability – the propensity for individuals and firms to utilize insurance services demonstrably increases. This heightened demand stems from insurance's efficacy in mitigating both financial exposure (potential asset devaluation or income loss) and operational risks (business continuity threats). Consequently, insurance transcends its role as a mere financial instrument and emerges as a pivotal mechanism for national economic stabilization and a vital buffer against sudden adverse shocks.Within this context, rigorous analysis of the influence exerted by key economic determinants – particularly macroeconomic uncertainty – on the insurance penetration rate (measured as the ratio of total insurance premiums to Gross Domestic Product, GDP) assumes paramount importance. A nuanced understanding of this relationship is indispensable for adopting effective economic policies and industry strategies. The primary objective of this research is therefore to conduct a rigorous empirical investigation into the specific impact of shocks originating from macroeconomic uncertainty on the insurance penetration rate within the distinctive and challenging economic landscape of Iran. Iran's economy, marked by international sanctions, significant political risks, volatile oil revenues, and recurrent macroeconomic disturbances, presents a compelling case study for examining how profound uncertainty shapes risk mitigation behaviors through formal insurance channels.METHODS: This research employs a comprehensive and recent macroeconomic uncertainty index as the primary measurement of uncertainty. This index is constructed based on seven major economic variables: interest rates, inflation, exchange rates, oil prices, stock market indices, unemployment rates, and gross domestic product (GDP). The data spans the period from 1990 (Persian year 1369) to 2021 (Persian year 1400), covering both the uncertainty index and insurance penetration rates. To analyze the relationship between these variables, a Structural Vector Autoregression (SVAR) model is used. The SVAR model is capable of identifying and analyzing the impact of stochastic shocks to each variable and evaluating both short-term and long-term effects on insurance penetration. This methodological approach allows for a nuanced understanding of how macroeconomic uncertainty influences insurance demand over time. Precise identification assumptions, based on economic logic and the specific context of Iran (e.g., the exogeneity of oil price shocks), are incorporated within the SVAR model. These assumptions are vital for distinguishing between endogenous responses (how variables react to each other within the system) and genuine exogenous shocks, thereby ensuring the credibility and interpretability of the causal inferences drawn regarding the impact of uncertainty. This robust methodological approach provides a solid foundation for understanding the transmission mechanisms—how macroeconomic shocks propagate through the Iranian economy—and ultimately influence the demand decisions for insurance coverage by households and firms.FINDINGS: The results demonstrate a positive and significant relationship between macroeconomic uncertainty and insurance penetration. Specifically, an increase in economic uncertainty correlates with heightened demand for insurance products. This indicates that as uncertainty and volatility in the economy rise, individuals and firms are more inclined to purchase insurance as a risk mitigation instrument. The long-term analysis reveals that shocks to the uncertainty index lead to a sustained increase in insurance penetration. Moreover, variance decomposition results reveal that, in the tenth period (2011-2021), approximately 73.30% of the fluctuations in insurance penetration are explained by macroeconomic uncertainty shocks. The findings also highlight that economic sanctions and political risks negatively and significantly impact insurance penetration, reducing its levels. Conversely, factors such as Foreign Direct Investment (FDI), oil price uncertainty, and human capital development show a positive and significant influence on increasing insurance demand.CONCLUSION: Based on the study’s findings, it can be concluded that in conditions of high economic uncertainty, individuals and economic practitioners tend to rely more on insurance products. As a critical tool in risk management, insurance helps protect assets during unforeseen events, economic crises, and price fluctuations. Therefore, the policymakers should recognize these dynamics and develop strategic policies aimed at supporting and expanding the insurance sector. Effective policy measures can mitigate the adverse effects of economic uncertainty, reinforce economic stability, and promote broader insurance market development. Understanding these relationships enables policymakers to create targeted interventions that enhance financial resilience and foster sustainable economic growth, especially in uncertain environments such as Iran.
Original Research Paper
Risk assessment in insurance
Zeynolabedin Aghilifar; Sayed Yahya Abtahi; Gholamreza Askarzadeh; Hamid Khajeh Mahmoodabadi
Abstract
BACKGROUND AND OBJECTIVES: Examining the long-term relationships and cointegration among different branches of insurance is crucial for understanding risk management and financial stability in the insurance industry. These relationships emerge due to factors such as the nature of similar risks, dependence ...
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BACKGROUND AND OBJECTIVES: Examining the long-term relationships and cointegration among different branches of insurance is crucial for understanding risk management and financial stability in the insurance industry. These relationships emerge due to factors such as the nature of similar risks, dependence on economic variables (e.g., interest rates, inflation, or economic growth), and shared capital management in the long term. Therefore, cointegration analysis is a powerful tool for identifying long-term relationships among different insurance branches. This method helps insurance companies to adopt better risk management strategies, allocate their capital optimally, and provide better services to customers. Since the insurance market is influenced by economic, social, and environmental factors, this analysis is of great importance for improving strategic decision-making. This study investigates the dependency structure among various insurance branches using nonlinear cointegration analysis.METHODS: In this study, the dependency structure among different insurance branches is analyzed using Johansen's linear cointegration method and Hansen and Seo's nonlinear cointegration approach, as well as the existence of equilibrium processes in their long-term relationships. For this purpose, a dataset comprising monthly claim amounts (excluding recoveries) from liability insurance, third-party insurance, and automobile body insurance is used. These branches were selected due to their non-zero and similar order of integration. The dataset spans the period from January 2011 to December 2023.FINDINGS: The results indicate the existence of at least one linear cointegration vector among the risks of different insurance branches. However, examining the presence of nonlinear relationships among the three branches within the framework of threshold vector error correction models (TVECM) reveals that adjustments toward long-term equilibrium occur when the gap between liability and automobile body insurance claims is within or beyond estimated threshold values. Moreover, when the loss gap exceeds the threshold, the adjustment towards long-term equilibrium occurs at a faster rate. Additionally, the error correction effect is significantly stronger for liability insurance compared to the other two branches. Automobile body insurance exhibits a higher error correction rate than third-party insurance, while third-party insurance demonstrates the weakest error correction effect. The estimation of the three equations related to the long-term relationships of insurance branches shows that the error correction component in the equations related to liability insurance and body insurance is significant in both the high and low regimes. However, the error correction component in the equations related to third-party insurance is not significant in either regime. On the other hand, the error correction coefficient in the equations for liability insurance and body insurance is much higher in the high regimes than in the low regimes. In other words, when the gap between the losses in liability and body insurance is estimated to be less than or greater than the threshold values, an adjustment towards the long-term equilibrium occurs, but the adjustment process towards the long-term equilibrium occurs more rapidly in cases where the loss gap is greater than the threshold. Also, there is a much stronger error correction effect for the liability insurance branch than for the other two branches. Then, body insurance has higher error correction than third-party insurance. Finally, third-party insurance has much lower error correction than the others.CONCLUSION: Liability insurance is exposed to high systematic risk, and macroeconomic conditions—such as high inflation rates and economic constraints due to sanctions—have led to a decline in vehicle quality and an increase in claims for third-party and automobile body insurance. Consequently, the systematic risk in the liability insurance sector has also increased, as it exhibits a high adjustment speed in its relationships with third-party and automobile body insurance. A similar pattern is observed for automobile body insurance, where an increase in third-party insurance claims can raise the systematic risk of automobile body insurance, ultimately eliminating the risk gap between these two branches in the long term. Therefore, risk and capital management in insurance companies shall account for such dependencies among insurance branches. Ignoring the adjustments in inter-branch risk relationships could expose insurance firms to significant financial losses. It is suggested that since third-party insurance has less error correction than other branches, insurance companies and policymakers in the country's insurance sector pay special attention to risk management in this sector because increasing risk in this sector, given the high adjustment speed of other insurance branches compared to third-party, can also increase the risk of other sectors and create systematic risk in the entire insurance industry. On the other hand, to optimally manage the risk of liability and body insurance, insurance companies need to pay attention to the critical loss thresholds in this type of insurance and estimate these thresholds according to the long-term relationships among losses in different insurance branches in each company.
