Original Research Paper
New Insurance Technologies
Ghasem Zarei; Hossein Rahimi Kolour; Issa Masoumi Jenagard
Abstract
BACKGROUND AND OBJECTIVES: The integration of artificial intelligence (AI) into the insurance industry represents a major technological shift potentially capable of transforming traditional business models, operational processes, and customer engagement strategies. Despite its initial promise, AI adoption ...
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BACKGROUND AND OBJECTIVES: The integration of artificial intelligence (AI) into the insurance industry represents a major technological shift potentially capable of transforming traditional business models, operational processes, and customer engagement strategies. Despite its initial promise, AI adoption in insurance markets remains limited and uneven across regions and sub-sectors. Many insurers are still evaluating the feasibility and implications of AI technologies, while others have initiated pilot projects or partial automation systems. Scientific research on the strategic, organizational, and technological impacts of AI in insurance is still emerging, leaving a gap in understanding how AI can be effectively leveraged in this context. This study aims to address that gap by identifying the antecedents, core components, and consequences of AI utilization in the insurance industry. It also proposes a conceptual framework to guide future research and practical implementation efforts.METHODS: This research employed a qualitative methodology grounded in an interpretive paradigm and inductive reasoning. The study was designed to address a practical problem in the insurance sector while contributing to theoretical development through the creation of a new conceptual model. Data collection was conducted using purposive and snowball sampling techniques to recruit experts from both the insurance and the information technology domains. After achieving theoretical saturation, 40 semi-structured interviews were conducted with a diverse group of participants, including senior managers, insurance company specialists, and university faculty members. The interviews were transcribed and analyzed using thematic analysis, which was carried out in three stages: open coding, axial coding, and selective coding. MAXQDA 2020 software was used to facilitate the organization and synthesis of qualitative data, leading to the extraction of key themes and the development of the study’s conceptual framework.FINDINGS: The analysis resulted in the extraction of 566 initial codes, which were later refined and consolidated into 63 final codes. These codes were organized into three major categories: antecedents, components, and outcomes. Each category was further subdivided based on the Technology-Organization-Environment (TOE) framework. Antecedents included organizational factors such as perceived usefulness, competitive advantage, cost and time efficiency, self-efficacy, trust, fraud concerns, organizational size, and the growth of insurance claims. Technological antecedents encompassed system complexity and advancements in computational power, while environmental antecedents involved competitive pressure, market dynamics, and evolving customer expectations. The components of AI adoption were also classified into organizational (e.g., infrastructure readiness, top management support, stakeholder trust-building, employee training, organizational ethos, managerial skills, and budget allocation), technological (e.g., technological competencies, access to adoption guidelines, data quality and availability), and environmental (e.g., government support, financial assistance from banks) dimensions. The outcomes of AI adoption included both positive and negative consequences. Positive outcomes were particularly prominent and included service personalization, dynamic risk assessment, fraud detection, improved claims processing, enhanced customer service, and data-driven decision-making. These benefits contributed to greater operational agility, reduced administrative burden, and more accurate underwriting practices. Negative outcomes, although less emphasized, involved concerns related to data privacy, ethical implications of automated decision-making, potential job displacement due to automation, and the risk of over-reliance on AI systems without adequate human oversight. Overall, the findings underscore the complex interplay of internal and external factors that shape the trajectory of AI adoption in insurance. They highlight the need for a balanced approach integrating technological innovation with organizational preparedness and environmental alignment. The conceptual model developed in this study serves as a strategic tool for guiding insurers through the multifaceted process of AI implementation, ensuring that benefits are maximized while risks are proactively managed.CONCLUSION: This study developed a comprehensive conceptual model that captures the multifaceted nature of AI adoption in the insurance industry. By systematically identifying and categorizing the antecedents, components, and consequences, the model offers a valuable tool for researchers, practitioners, and policymakers seeking to understand and navigate the complexities of AI implementation. The findings emphasize the importance of aligning technological capabilities with organizational readiness and environmental support to ensure successful and sustainable AI integration. The study recommends that future research adopt quantitative approaches to validate and prioritize the proposed model across different insurance sub-sectors, such as health, auto, and life insurance. Such efforts will enable stakeholders to tailor AI strategies to specific contexts, optimize resource allocation, and mitigate potential risks. Ultimately, the research highlights the transformative potential of AI in enhancing operational efficiency, customer satisfaction, and strategic agility within the insurance sector, while also calling for thoughtful governance and ethical oversight to ensure responsible innovation.
Original Research Paper
New Insurance Technologies
Mona Parastesh
Abstract
BACKGROUND AND OBJECTIVES: One of the major challenges in the insurance industry is combating fraud during the claim submission process, which is particularly evident in digital claim systems where customers send images of damages and injuries through mobile applications. As the insurance sector continues ...
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BACKGROUND AND OBJECTIVES: One of the major challenges in the insurance industry is combating fraud during the claim submission process, which is particularly evident in digital claim systems where customers send images of damages and injuries through mobile applications. As the insurance sector continues its digital transformation, introducing modern methods across various operational stages such as underwriting, issuance, and claim processing, the necessity of developing innovative and secure fraud detection mechanisms has become more crucial than ever. With the rapid digitization and digitalization of insurance services, ensuring the authenticity of transmitted data and protecting sensitive information have emerged as key priorities. In digital claim reporting, where policyholders upload damage photographs via mobile applications, the authenticity of spatial and temporal metadata—specifically the location and time of the captured images—plays a vital role in reducing fraudulent submissions. To address this issue, this study proposes a novel security framework that utilizes steganography and cryptography for embedding encrypted metadata directly into the image file. In this method, the location and timestamp information extracted from the damage images are first encrypted using the AES-GCM algorithm and then securely embedded into the image through a Generative Adversarial Network (GAN)-based steganographic model. The hidden data can subsequently be extracted and decrypted at the insurer’s end for verification. This approach not only strengthens the authenticity verification of the submitted images but also enhances data confidentiality and resistance to tampering. By integrating this method into a company’s insurance application, insurers can build greater trust with policyholders, automate the verification process, and effectively reduce costs associated with fraudulent activities. The combination of deep learning–based steganography with robust encryption offers a promising path toward intelligent, secure, and fraud-resistant insurance claim systems.METHODS: The proposed system employs a GAN-based steganographic framework to embed spatial and temporal metadata within damage images. Initially, the Exif metadata (including the capture time and GPS coordinates) is extracted and encrypted using the AES-GCM (Advanced Encryption Standard – Galois/Counter Mode) algorithm. This encryption stage ensures confidentiality and integrity of sensitive data before it is hidden in the image. The encrypted data are then embedded using a deep neural network generator, which learns to conceal information within the least perceptible image regions while preserving high visual fidelity. For performance evaluation, the system was tested on a dataset of 100 automobile damage photographs having been collected from real insurance claim records. Three methods were compared: Baseline LSB (Least Significant Bit) method, GAN-based steganography without encryption, and GAN combined with AES-GCM encryption (proposed method). The evaluation considered several quantitative metrics: Image quality measured by Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM), Embedding capacity, Bit Error Rate (BER) under standard steganalysis attacks such as JPEG compression (quality 50), Gaussian noise (σ = 5), and image scaling (0.9), and Detection rate of metadata manipulation to assess system robustness against tampering.FINDINGS: The experimental results confirmed the effectiveness of the proposed approach. Images containing hidden data maintained a high visual quality with an average PSNR of 41 dB, demonstrating that the steganographic embedding had minimal perceptual impact. The GAN-based method outperformed the baseline LSB technique, achieving higher image quality (40.6 ± 0.8 dB vs. 36.7 ± 1.1 dB) and better structural similarity. Moreover, the average BER under compression and noise attacks was nearly half that of the baseline method (≈12–19% vs. ≈29–34%). Integrating AES-GCM encryption had no negative effect on visual quality but significantly improved end-to-end data security. Statistical analysis using a paired-sample t-test revealed that the performance differences were significant at a 95% confidence level (p < 0.001). The 95% confidence interval for PSNR values of the proposed model was calculated to be [40.7, 41.3], reflecting the system’s stability and consistency. In the metadata tampering experiments, all instances of manipulated metadata in the 100-image dataset were successfully detected, achieving 100% detection accuracy. The average mobile implementation time for the complete encryption and embedding sequence was approximately 2.0 seconds per image, confirming the feasibility of applying the system in real-time insurance applicationsCONCLUSION: The findings of this research demonstrate that employing deep learning-based steganography (GAN) in combination with AES-GCM encryption can effectively mitigate security challenges in online insurance claim processes. The proposed method provides a reliable mechanism to verify the authenticity of spatial and temporal data while maintaining high image quality and computational efficiency. This integrated framework enhances both data protection and fraud prevention, ensuring that insurance companies can verify the legitimacy of submitted claim images with greater confidence. Consequently, the proposed GAN–AES hybrid model achieves an optimal balance between image fidelity, robustness to steganographic attacks, and metadata integrity verification. The results suggest that this approach can serve as a practical and efficient layer of protection for digital insurance claim systems, contributing to enhancing trust, transparency, and security across the insurance ecosystem.
Original Research Paper
Marketing and Sales
Mohsen Nazari; Manouchehr Ansari; Mohammad Javad Ashari Pour
Abstract
BACKGROUND AND OBJECTIVES: Sustainable business model innovation is a widely studied concept in management, sustainability, and innovation literature. Although extensively researched, business models have not fully adapted themselves to the technological, sustainability, and post-pandemic era. A critical ...
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BACKGROUND AND OBJECTIVES: Sustainable business model innovation is a widely studied concept in management, sustainability, and innovation literature. Although extensively researched, business models have not fully adapted themselves to the technological, sustainability, and post-pandemic era. A critical future challenge for Iran is the financial instability of pension funds and social insurance organizations, with the crisis approaching a critical stage. Designing innovative sustainable business models for these organizations could offer an efficient solution. This study aims to identify factors influencing sustainable business model innovation, using a case study method focused on Iran’s Social Security Organization, and is the first such study of this organization. The research questions are: 1. What are the factors affecting sustainable business model innovation for the Social Security Organization, and how can they be classified? 2- What are the drivers and consequences affecting the implementation of sustainable business model innovation for the Social Security Organization, and how can they be classified? 3- What is the importance of each component of the sustainable business model innovation for the Social Security Organization across the three parts: antecedents, business model, and consequences?METHODS: A single case study was conducted on Iran’s Social Security Organization. Data were collected through documentation and archival records (62 documents), interviews (23 interviews), and participant observation until theoretical saturation was achieved. The level of support for each component and their rankings was determined using the Shannon entropy method. Cohen’s kappa coefficient was used to assess the reliability of the coding process. FINDINGS: The research findings were analyzed and categorized using MAXQDA software. A total of 63 components and 279 codes were identified, relating to the characteristics of sustainable business model innovation for the Social Security Organization, across three levels: antecedents, sustainable business model innovation, and consequences. For the first research question, the sustainable business model innovation for the Social Security Organization comprised 183 codes, classified into 38 components and six categories. For the second research question, the drivers consisted of 67 codes, classified into 18 components and two categories. The consequences comprised 29 codes, classified into 7 components and three categories. For the third research question, the importance of each component was determined using the Shannon entropy method. Among the antecedents, dynamic capabilities ranked first, followed by government and macroeconomic components in second and third places, respectively. Within the business model, the innovation component—focused on increasing premium collection (compulsory and non-compulsory premiums, statutory audits) and reducing liability costs (short-term, long-term, and treatment)—ranked first. The knowledge and actuarial components, human resources, and insurance services (based on actuarial calculations) ranked second to fourth, respectively. Treatment services (considering the Organization’s service showcase, mass production, procurement of quality treatment services for beneficiaries, and cost-reduction methods) and other governance elements ranked fourth and fifth, respectively. Among the consequences, competitive advantage and market components ranked first, followed by:) community development (education, health, economic growth, and livelihoods) and social security components in second and third places, respectively.CONCLUSION: Drawing on the sustainable business model framework (Bocken et al., 2018), this study introduces a novel model of antecedents, sustainable business model innovation, and consequences. The model includes antecedents (internal and external), the business model (divided into four subsections: value creation, value proposition, value exploitation, and value delivery), and consequences (economic, social, and environmental). This model can serve as a practical guide for managers of pension funds and social insurance organizations and policymakers in welfare and social security. The study also contributes to practical innovation and sustainable business model innovation in the service sector. To achieve sustainable business model innovation, the Social Security Organization should keep pace with new business trends (e.g., teleworking, freelancing, sharing economy) and simplify complex processes. Digitalizing services, including developing self-service applications and reducing in-person visits, is essential to improve beneficiary experiences. Operational transparency, through regular and online reports, strengthens public trust and social capital. Combating insurance fraud using artificial intelligence, data mining, and inter-agency collaboration conserves organizational resources. Marketing non-compulsory insurance expands coverage by strategically targeting new markets and modifying plans. An active role in discourse, lobbying, and legislation is crucial to maintaining the Organization’s independence and financial sustainability. Using artificial intelligence and digital capabilities to identify insured people and optimize inspections while increasing efficiency. Reducing bureaucracy, outsourcing non-core tasks, and reforming meritocratic appointments will enhance organizational innovation and agility.
Original Research Paper
Insurance rights
Zahra Asadi; Medrick Pirsaheb
Abstract
BACKGROUNDS AND OBJECTIVES: Employer’s liability insurance, which provides coverage for employers against legal liability for bodily injuries or deaths sustained by employees during the course of employment, is one of the most important fields of liability insurance in Iran’s insurance system. ...
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BACKGROUNDS AND OBJECTIVES: Employer’s liability insurance, which provides coverage for employers against legal liability for bodily injuries or deaths sustained by employees during the course of employment, is one of the most important fields of liability insurance in Iran’s insurance system. Given its significant role in compensating for work-related injuries and protecting employee rights, the development of clear and comprehensive regulations in this area has consistently been a priority for regulatory bodies. In line with this, the High Council of Insurance, in its meeting dated October 9, 2019 (17 Mehr 1398, Persian calendar), and in accordance with Article 17 of the Law on the Establishment of the Central Insurance of Iran and Insurance Operations, approved the “General Terms and Conditions of Employer’s Liability Insurance” under Regulation No. 98, consisting of 24 articles and 2 notes. This regulation was drafted with the aim of updating, clarifying, and standardizing the previous provisions, and it replaced the former Regulation No. 80, which had faced various criticisms and ambiguities in practice over the years.Although Regulation No. 98 represents an attempt to address the shortcomings and ambiguities of its predecessor, comparative analyses, expert opinions, and practical experiences in the insurance industry indicate that it still faces conceptual, operational, and legal challenges. These challenges include the lack of precise definitions for key terms, unclear delineation of responsibilities, and legal gaps in the compensation process, which can limit the regulation’s effectiveness in practice. Accordingly, the main objective of this study is to conduct a critical and analytical review of Regulation No. 98 and the insurance policies derived from it, with a focus on identifying the existing gaps, deficiencies, and practical challenges. The study also aims to propose reform strategies and policy recommendations to enhance the technical and legal performance of this branch of liability insurance. Through legal analysis, insurance theory, and empirical observations, this research seeks to contribute to the systematic improvement of current regulations and to support the advancement of employer’s liability insurance services in Iran.METHODS: This research adopts a descriptive-analytical approach, relying on library resources. First, the provisions of regulation 98 and additional coverages are reviewed. Then, through content analysis of these provisions, the main shortcomings and flaws are identified.FINDINGS: The employer’s civil liability insurance policy, in terms of its general conditions, is clearly subject to the provisions of Regulation No. 98 of the Supreme Insurance Council, which is recognized as the primary authority for regulating and defining related rules. This regulation, enacted with the aim of resolving ambiguities and amending the deficiencies of Regulation No. 80, despite efforts made to enhance the clarity and effectiveness of the provisions, still contains certain ambiguities and differing interpretations among stakeholders, including policyholders, insurers, and judicial authorities. These ambiguities mainly arise from some vague coverages or imprecise expressions, which have resulted in a lack of uniform and consistent interpretation regarding the rights and obligations of the parties to the insurance contract. This situation has, to some extent, led to legal and technical disputes between the parties and, in certain cases, dissatisfaction and uncertainty concerning the operation of the insurance policy. From this perspective, a more comprehensive and in-depth revision of Regulation No. 98 of the Supreme Insurance Council is increasingly necessary to eliminate ambiguities, facilitate more effective interactions, streamline legal processes, and enhance stakeholder satisfaction. In this revision, it is essential to utilize the expertise of legal, insurance, and industry specialists to not only clarify the provisions more precisely but also establish clear implementation frameworks and dispute resolution mechanisms to prevent recurrence of previous issuesCONCLUSION: Regulation No. 98 of the High Council of Insurance, as a key document governing employer’s liability insurance, requires fundamental revision and reform to more comprehensively and accurately address the evolving and complex needs of the insurance market. The conducted reviews indicate that certain coverages and provisions of the regulation, due to ambiguities in definitions and coverage scope, have led to varied and sometimes contradictory interpretations among policyholders and insurance companies. This situation not only reduces the satisfaction and trust of stakeholders but also has caused legal disputes in some cases. In response to these challenges, several supplementary coverages have been introduced to better cover risks and specific needs of policyholders, however, this measure alone is insufficient. Therefore, a comprehensive revision of the regulation with a critical and participatory approach, incorporating the views of experts, policyholders, and other stakeholders, appears essential. Such a revision can pave the way for improving insurance processes, increasing transparency, and enhancing the quality of services in the field of employer’s liability insurance.
Original Research Paper
Economics of finance / insurance
Atousa Goodarzi; Amirmohammad Karaminik
Abstract
BACKGROUND AND OBJECTIVES: Pension funds are one of the most critical pillars of a country’s social security system, tasked with ensuring financial protection for retirees and contributing to socio-economic stability. In Iran, the strategic role of pension funds has become increasingly vital due ...
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BACKGROUND AND OBJECTIVES: Pension funds are one of the most critical pillars of a country’s social security system, tasked with ensuring financial protection for retirees and contributing to socio-economic stability. In Iran, the strategic role of pension funds has become increasingly vital due to demographic transitions, rising life expectancy, economic volatility, and structural challenges in the national economy. Over the past decade, growing concerns have emerged regarding the financial sustainability of these funds, particularly in the face of fiscal pressures, dependency on government resources, and exposure to diverse risks. These risks—ranging from investment volatility to legislative uncertainty—have the potential to undermine both short-term liquidity and long-term solvency. The problem is compounded by insufficient risk management mechanisms, outdated investment strategies, and governance issues within the funds. Having Recognized the absence of a comprehensive, context-specific risk assessment model for the Iranian pension funds, this study was conducted to identify, classify, assess, and develop a model for controlling the key risks that influence their performance. The ultimate objective was to provide a structured framework that could support decision-makers in safeguarding the funds’ financial stability, improving resilience against future uncertainties, and aligning operational strategies with long-term sustainability goals.METHODS: This research employed a mixed-method approach, integrating qualitative and quantitative phases to ensure both depth and empirical validation. In the qualitative phase, the Grounded Theory methodology—following Strauss and Corbin’s systematic approach—was applied. Semi-structured, in-depth interviews were conducted with a purposive sample of experts, including senior executives of pension funds, insurance specialists, policymakers in the social security domain, and academic scholars in finance and risk management. The interviews focused on exploring participants’ perceptions of the critical risks affecting pension fund performance, the interrelations among these risks, and potential control mechanisms. Data coding was carried out in three stages: open coding, axial coding, and selective coding, resulting in the identification of key categories and sub-categories of risk. In the quantitative phase, the conceptual model derived from the qualitative findings was operationalized into a researcher-designed questionnaire. This instrument was structured to measure the perceived significance, probability, and controllability of each identified risk category. The questionnaire underwent content validity assessment by a panel of experts and reliability testing using Cronbach’s alpha coefficient. It was then distributed among a broader group of pension fund managers, policymakers, and industry specialists. The collected data were analyzed using Structural Equation Modeling (SEM) with appropriate fit indices to assess the model adequacy. This dual-phase methodology ensured that the final model was both theoretically grounded and empirically validated, increasing its practical applicability the for Iranian pension funds.FINDINGS: The results of the study revealed that risks influencing the performance and sustainability of the pension funds in Iran can be systematically classified into seven primary categories and thirty-three sub-categories. These main categories include financial and economic risks, which encompass investment performance volatility, inflationary pressures, currency fluctuations, and dependency on unstable revenue streams; managerial and investment risks, involving deficiencies in governance structures, poor asset allocation strategies, and insufficient expertise in risk-based decision-making; legal and political risks, related to regulatory instability, changes in government policies, and legislative interventions affecting investment and contribution frameworks; operational and organizational risks, such as inefficiencies in internal processes, inadequate human capital management, and weaknesses in organizational culture; technological and informational risks, referring to cybersecurity vulnerabilities, lack of integration in information systems, and insufficient adoption of data analytics in decision-making; social and demographic risks, driven by population aging, shifting workforce participation patterns, and changes in beneficiaries’ expectations; and international risks, linked to global market shocks, sanctions, and external economic dependencies. The analysis showed that financial and economic risks had the strongest direct impact on fund performance, followed by managerial and investment risks, highlighting the urgent need for strategic interventions in these domains. Furthermore, the SEM results confirmed that a proactive and integrated risk management framework significantly enhances the ability of the pension funds to maintain a positive asset-to-liability ratio, reduce reliance on government bailouts, and improve long-term sustainability.CONCLUSION: This research underscores that the effective management of identified risk factors is critical for ensuring the financial sustainability and operational resilience of the pension funds in Iran. The study concludes that the adoption of strategic, data-driven policies targeting both high-impact and high-probability risks can substantially mitigate systemic vulnerabilities. Among the most pressing needs are the reform of legal and regulatory frameworks to provide stability and predictability, the strengthening of governance and managerial competencies to align investment strategies with long-term liabilities, and the deployment of advanced technological solutions for enhanced data integration and risk monitoring. In addition, the study highlights the necessity of diversifying revenue sources and investment portfolios to reduce exposure to domestic economic volatility and external shocks. The proposed model not only offers a theoretical contribution to the literature on pension fund risk management but also provides practical tools for decision-makers to monitor, assess, and respond to emerging threats in a timely manner. By fostering a culture of continuous risk assessment and adaptive management, pension funds can better safeguard the retirement security of their beneficiaries and reduce the financial burden on the national economy. Ultimately, implementing the recommendations of this study can serve as a roadmap for transitioning from reactive crisis management to proactive, sustainable governance in the Iranian pension system.
Promotional-Science Article
Comparative studies in the field of insurance
Fatemeh Azadbakht; Sara Ahadi Kalayeh
Abstract
Background and Objectives:The aquaculture industry, particularly fish farming, plays a significant role in supplying protein for the world’s growing population and constitutes a key component of the global food economy by contributing to food security and employment. Nevertheless, this sector remains ...
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Background and Objectives:The aquaculture industry, particularly fish farming, plays a significant role in supplying protein for the world’s growing population and constitutes a key component of the global food economy by contributing to food security and employment. Nevertheless, this sector remains highly vulnerable to climatic fluctuations, viral and parasitic disease outbreaks, environmental pollution, and market volatility. Managing these risks requires effective financial instruments, among which insurance serves as a crucial mechanism. In Iran, the existing fish farming insurance structure does not fully meet the needs of the sector. Owing to its dependence on subsidized government resources and centralized administration, it lacks financial dynamism and sustainability. The objective of this study is to propose a reform-oriented model for improving the fish farming insurance framework in Iran, drawing on the experience of three leading countries in this domain, so as to strengthen the economic stability of farms and reduce vulnerability to inherent risks.Methodology:This research employs a descriptive–analytical and comparative approach. Data were collected through documentary review, including the examination of laws, guidelines, insurance regulations, and official reports from selected countries. The study population comprises the insurance and regulatory frameworks of Iran, China, India, and Japan.Findings: Comparative results indicate that in state centered models (such as Iran and China), loss coverage relies primarily on public funds and subsidies, and risk assessment tends to be administrative rather than competitive. In contrast, in market oriented models (such as India and Japan), the government mainly acts as a facilitator and regulator, while private insurers and specialized cooperatives serve as the principal implementers of insurance activities. Differences in supervisory and premium rating frameworks have led market driven systems to achieve greater financial stability and faster, more transparent compensation processes.Conclusion:Based on the findings, it is recommended that Iran transform its fish farming insurance system toward a hybrid, data driven model in which the Agricultural Insurance Fund acts as a reinsurer and technical regulator, while commercial insurance companies or takaful (mutual) funds operate as direct insurers. Establishing a dedicated takaful fund for edible fish insurance, together with reforming the subsidy mechanism and developing risk based regulatory oversight, can provide an indigenous and sustainable framework for managing climatic, biological, and economic risks in the aquaculture sector. Implementing this model would reduce the financial risk of insurers, enhance producers’ confidence, and promote long term economic stability in Iran’s aquaculture industry.Background and Objectives:The aquaculture industry, particularly fish farming, plays a significant role in supplying protein for the world’s growing population and constitutes a key component of the global food economy by contributing to food security and employment. Nevertheless, this sector remains highly vulnerable to climatic fluctuations, viral and parasitic disease outbreaks, environmental pollution, and market volatility. Managing these risks requires effective financial instruments, among which insurance serves as a crucial mechanism. In Iran, the existing fish farming insurance structure does not fully meet the needs of the sector. Owing to its dependence on subsidized government resources and centralized administration, it lacks financial dynamism and sustainability. The objective of this study is to propose a reform-oriented model for improving the fish farming insurance framework in Iran, drawing on the experience of three leading countries in this domain, so as to strengthen the economic stability of farms and reduce vulnerability to inherent risks.Methodology:This research employs a descriptive–analytical and comparative approach. Data were collected through documentary review, including the examination of laws, guidelines, insurance regulations, and official reports from selected countries. The study population comprises the insurance and regulatory frameworks of Iran, China, India, and Japan.Findings: Comparative results indicate that in state centered models (such as Iran and China), loss coverage relies primarily on public funds and subsidies, and risk assessment tends to be administrative rather than competitive. In contrast, in market oriented models (such as India and Japan), the government mainly acts as a facilitator and regulator, while private insurers and specialized cooperatives serve as the principal implementers of insurance activities. Differences in supervisory and premium rating frameworks have led market driven systems to achieve greater financial stability and faster, more transparent compensation processes.Conclusion:Based on the findings, it is recommended that Iran transform its fish farming insurance system toward a hybrid, data driven model in which the Agricultural Insurance Fund acts as a reinsurer and technical regulator, while commercial insurance companies or takaful (mutual) funds operate as direct insurers. Establishing a dedicated takaful fund for edible fish insurance, together with reforming the subsidy mechanism and developing risk based regulatory oversight, can provide an indigenous and sustainable framework for managing climatic, biological, and economic risks in the aquaculture sector. Implementing this model would reduce the financial risk of insurers, enhance producers’ confidence, and promote long term economic stability in Iran’s aquaculture industry.
