Document Type : Original Research Paper

Authors

1 PhD Candidate, Department of Economics, Faculty of Management and Economics, Islamic Azad University, Science and Research Branch, Tehran, Iran.University, Tehran, Iran.

2 Assistant Professor, Department of Management, Faculty of Management and Economics, Islamic Azad University, Science and Research Branch, Tehran, Iran.

3 Assistant Professor, Department of Economics, Faculty of Economics and Accounting, Islamic Azad University, Central Tehran Branch, Tehran, Iran.

4 Assistant Professor, Department of Economics, Faculty of Management and Economics, Islamic Azad University, Science and Research Branch, Tehran, Iran.

Abstract

BACKGROUND and OBJECTIVES: The capacity to retain underwriting risk and the continuous provision of strategic mechanisms to augment this capacity are essential to the operational stability, long-term survival, and financial resilience of insurance institutions. A primary and globally recognized strategy to achieve this structural resilience is executing robust risk transfer policies through ceded (outward) reinsurance operations. In addition to an insurer’s intrinsic capital base and shareholders’ equity, ceded reinsurance serves as the predominant and most accessible instrument for creating additional underwriting capacity, elevating solvency margins, and hedging against catastrophic, cumulative, or unexpectedly heavy losses. However, the financial costs associated with purchasing these reinsurance protections—alongside the strategic necessity of ceding a significant portion of potential policy benefits and premium income to reinsurers to secure their participation in potential losses—constitute a major operational expenditure for direct insurers. This issue is critically important given the specific characteristics, macroeconomic fluctuations, and unique dynamics of the Iranian insurance market, which often operates under constrained external capacities and requires high internal optimization. Consequently, maximizing the productivity of these consumptive expenses to secure optimal returns, minimizing unnecessary premium leakage, and formulating an efficient ceded reinsurance strategy have become vital for the competitive success of insurers. Therefore, this study aims to determine the ceded reinsurance efficiency frontier of the Iranian insurers in a rigorous comparative framework over a specified period, directly addressing existing ambiguities regarding the mathematical and practical optimization of outward reinsurance operations.
METHODS: This research adopts a rigorous quantitative approach utilizing advanced Data Envelopment Analysis (DEA) techniques based on critical financial ratios directly linked to cede reinsurance operations. The mathematical model systematically evaluates the operational and technical efficiency of 22 direct Iranian insurers, acting as autonomous Decision-Making Units (DMUs), over four consecutive financial years (spanning 1400 to 1403 (Persian Year)). The DEA framework utilized incorporates both constant and variable returns to scale assumptions to provide a nuanced understanding of scale efficiencies within the sector. By identifying the fully efficient units that maximize their output-to-input ratios, the optimal ceded reinsurance efficiency frontier is precisely delineated for each respective financial year. Furthermore, the highly volatile macroeconomic and market conditions during this specific four-year timeframe necessitated a granular, longitudinal comparative analysis to discover the underlying reasons for shifts within the efficiency frontier over time. Consequently, the operational outcomes and productivity trajectories of each year were comprehensively evaluated and analyzed utilizing the Malmquist Productivity Index (MPI). By meticulously tracking temporal changes in overall efficiency and isolating the contributing factors—specifically distinguishing between technical efficiency changes (the catch-up effect) and technological changes (the frontier shift)—the MPI plays a pivotal role in developing targeted, data-driven strategies to continuously enhance the operational performance of inefficient DMUs.
FINDINGS: Following the precise determination of the mathematical efficiency frontier based on the performance of the fully efficient units of each evaluated year, targeted strategic pathways and corrective optimization solutions for efficiency enhancement were designed and prescribed using the calculated λ (lambda) values. These solutions are presented to establish empirically validated and highly specific benchmarking frameworks for insurance institutions diagnosed with sub-optimal or inefficient outward reinsurance operations. The reference weights, denoted as λ, precisely indicate which peer companies should be emulated to reach the optimal frontier. Additionally, the longitudinal analysis facilitated by the MPI across the evaluated financial periods demonstrated a highly dynamic and frequently shifting efficiency frontier. This observable dynamism is directly attributed to the evolving systemic conditions of the national insurance market, including inflation rates, regulatory adjustments, and variations in domestic retention capacities during the 1400 to 1403 period (Persian Year). The decomposition of the Malmquist index revealed that while some insurers improved their internal processes, the overall industry frontier experienced periods of regression and progression due to external shocks. These dynamic results, synthesized with the customized benchmarking strategies, culminate in the formulation of comprehensive macro-level action plans that can be practically utilized by executives.
CONCLUSION: The outcomes of this study successfully identify and elucidate the optimal ceded reinsurance efficiency frontier for (Persian Year) Iranian insurers, while explicitly outlining the strategic interventions required by direct insurers to structurally improve the functional efficiency of these critical risk-transfer operations. In this regard, localized, highly actionable performance improvement strategies have been explicitly extracted based on the λ reference weights derived from the optimally performing benchmark units. Furthermore, the study calculates and presents auxiliary slack variables which precisely quantify the mathematical deficit or surplus within the input and output financial ratios. This slack analysis highlights exact, quantified areas for operational adjustment, such as reducing unnecessary ceded premiums or renegotiating for better commission rates. Finally, the comprehensive analysis of the MPI, carefully contextualized against the specific economic characteristics and systemic challenges of each financial period, provides a robust, evidence-based, and highly functional analytical foundation. This foundation is designed to directly guide the strategic decision-making processes of corporate insurers and enhance the supervisory frameworks of national regulatory bodies, ensuring long-term market stability.

Keywords

Main Subjects

Babaei, S., Rostami Mal-Khalifeh, M., & Heidari, M. (2023). The evolution and determinants of accepted in Tehran stock exchange insurance companies’ Profitability: A DEA-based perspective. Iranian Journal of Insurance Research, 13(1), 61-70. https://doi.org/10.22056/ijir.2024.01.05 [In Persian].
Barros, C. P., Nektarios, M., & Assaf, A. (2010). Efficiency in the Greek insurance industry. European Journal of Operational Research, 205(2), 431-436. https://ideas.repec.org/a/eee/ejores/v205y2010i2p431-436.html
Benvidi, M., Emdadi, F., & Rostami Mal-khalifeh, M. (2024). Effectiveness of Insurance Companies from the perspective of reinsurance cession policy [Conference Paper]. 31st National and 12th International Conference on Insurance and Development (ICID 2024): Public Satisfaction and Trust in Insurance Industry. https://civilica.com/doc/2148782 [In Persian].
Berger, A. N., & Mester, L. J. (1997). Inside the black box: What explains differences in the efficiencies of financial institutions? Journal of Banking & Finance, 21(7), 895-947. https://www.sciencedirect.com/science/article/pii/S0378426697000101
Biener, C., & Eling, M. (2016). Insurability in microinsurance markets: An analysis of problems and potential solutions. In C. Courbage (Ed.), The Geneva Papers: 40 Years at the Cutting Edge of Research in Insurance Economics (pp. 196-234). Palgrave Macmillan. https://doi.org/10.1007/978-1-137-57479-4_8
Bodmer, U., & Vaughan, D. R. (2009). Approaches to preventing crises in family controlled small enterprises. Journal of Neuroscience, Psychology, and Economics, 2(1), 41-58. https://doi.org/10.1037/a0015767
Borch, K. (1967). The Theory of Risk. Journal of the Royal Statistical Society. Series B (Methodological), 29(3), 432-467. https://www.jstor.org/stable/2984385
Caves, D. W., Christensen, L. R., & Diewert, W. E. (1982). The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica, 50(6), 1393–1414. https://doi.org/10.2307/1913388
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2(6), 429-444. https://doi.org/10.1016/0377-2217(78)90138-8
Chen, R., Wong, K. A., & Lee, H. C. (1999). Underwriting cycles in Asia. Journal of Risk and Insurance, 66(1), 29-47. https://doi.org/10.2307/253876
Coelli, T., Rao, D. S. P., O’Donnell, C. J., Battese, G. E. (2005). An Introduction to Efficiency and Productivity Analysis. Springer Nature Inc. https://doi.org/10.1007/b136381
Cook, W. D., Tone, K., & Zhu, J. (2014). Data envelopment analysis: Prior to choosing a model. Omega, 44, 1-4. https://doi.org/10.1016/j.omega.2013.09.004
Cook, W. D., Hababou, M., & Tuenter, H. J. H. (2000). Multicomponent Efficiency Measurement and Shared Inputs in Data Envelopment Analysis: An Application to Sales and Service Performance in Bank Branches, Journal of Productivity Analysis, 14, 209-224. https://doi.org/10.1023/A:1026598803764
Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-solver Software. Springer Nature Inc. https://doi.org/10.1007/978-0-387-45283-8
Cooper, W.W., Seiford, L.M., & Zhu, J. (2011). Handbook on Data Envelopment Analysis. Springer Nature Inc. https://doi.org/10.1007/978-1-4419-6151-8
Cummins, J. D., & Xie, X. (2008). Mergers and acquisitions in the US property-liability insurance industry: Productivity and efficiency effects. Journal of Banking & Finance, 32(1), 30-55. https://doi.org/10.1016/j.jbankfin.2007.09.003
Cummins, J. D., Feng, Z., Weiss, M. A. (2012). Reinsurance counterparty relationships and firm performance in the U.S. Property-Liability Insurance Industry. SSRN Electronic Journal Temple University- Risk Management & Insurance & Actuarial Science. Retrieved June 19, 2025, from http://dx.doi.org/10.2139/ssrn.1997444
Cummins, J. D., Rubio-Misas, M., & Zi, H. (2004). The effect of organizational structure on efficiency: Evidence from the Spanish insurance industry. Journal of Banking & Finance, 28(12), 3113-3150. https://doi.org/10.1016/j.jbankfin.2004.05.004
Cummins, J. D., Weiss, M. A. (2000). The Global Market for Reinsurance: Consolidation, Capacity, and Efficiency. Brookings-Wharton Papers on Financial Services. https://scholar.google.com/scholar?q=The+global+market+for+reinsurance+%3A+consolidation%2C+capacity%2C+and+efficiency+Cummins+Weiss
Cummins, J. D., & Weiss, M. A. (2009). Convergence of Insurance and Financial Markets: Hybrid and Securitized Risk-Transfer Solutions. Journal of Risk and Insurance Association, 76(3), 493–545. https://doi.org/10.1111/j.1539-6975.2009.01311.x
Cummins, J. D., & Weiss, M. A. (2013). Analyzing firm performance in the insurance industry using frontier efficiency and productivity methods. In G. Dionne (Ed.), Handbook of Insurance (pp. 795-861). Springer Nature Inc. New York, NY. https://doi.org/10.1007/978-1-4614-0155-1_28
Despic, O., Despic, M., & Paradi, J. C. (2007). DEA-R: Ratio-based comparative efficiency model, its mathematical relation to DEA and its use in applications. Journal of Productivity Analysis, 28(1/2), 33 – 44. http://www.jstor.org/stable/41770324
Dimitrova, D. S., & Kaishev, V. K. (2010). Optimal joint survival reinsurance: An efficient frontier approach. Insurance: Mathematics and Economics, 47(1), 27–35. https://doi.org/10.1016/j.insmatheco.2010.03.006
Eling, M.,  &Luhnen, M. (2010). Efficiency in the international insurance industry: A cross-country comparison. Journal of Banking & Finance, 34(7), 1497-1509. https://doi.org/10.1016/j.jbankfin.2009.08.026
Eling, M., & Schmeiser, H. (2010). Insurance and the credit crisis: Impact and ten consequences for risk management and supervision. The Geneva Papers on Risk and Insurance- Issues and Practice, 35, 9–34. https://doi.org/10.1057/gpp.2009.39
Emrouznejad, A., Yang, G. L. (2018). A survey and analysis of the first 40 years of DEA literature: 1978–2016. Socio-Economic Planning Sciences, 61, 4–8. https://doi.org/10.1016/j.seps.2017.01.008
Ennew, C., Wright, M., Wong, P. (1998). Marketing of financial services: The Service Industries
Fare, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. American Economic Review, 84(1), 66–83. https://www.jstor.org/stable/2117971
Farrell, M. J. (1957). The measurement of productivity efficiency. Journal of the Royal Statistical Society Series A: General, 120(3), 253 –290. https://doi.org/10.2307/2343100
Gharekhani, M., & Zinsaz, A. (2013). A Study on the role of reinsurance contracts on the financial solvency of insurance companies [Conference Paper]. 20th National Conference on Insurance and Development. https://sid.ir/paper/879562/fa [In Persian].
 Kao, C., & Hwang, S. N., Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan, (2008). European Journal of Operational Research, 185(1), 418-429. https://link.springer.com/article/10.1007/s10479-017-2399-1?utm_source=researchgate.net&utm_medium=article
Hashemi, V.,  &Ghalichi, Z. (2015). Evaluating the Efficiency of the country’s insurance industry companies based on reinsurance indicators using the Data Envelopment Analysis (DEA) method [Conference Paper]. 3rd International Conference on Accounting and Management with a New Research Sciences Approach. https://civilica.com/doc/492730 [In Persian].
International Association Insurance Supervisors. (2018). IAIS Annual Report 2018. IAIS. https://www.iais.org/uploads/2022/01/191115-IAIS-2018-Annual-Report-Double-Page.pdf
IFRS Foundation. (2017). Annual Report 2017: IFRS Foundation Financial Reporting for the World Economy. IFRS Foundation. https://www.ifrs.org/content/dam/ifrs/about-us/funding/2017/annual-report-2017.pdf
Jeng, V., & Lai, G. C. (2005). Ownership structure, agency costs, specialization, and efficiency: Analysis of keiretsu and independent insurers in the Japanese nonlife insurance industry. Journal of Risk and Insurance, 72(1), 105–158. https://doi.org/10.1111/j.0022-4367.2005.00118.x
Jeng, V., Lai, G. C., & McNamara, M. J. (2007). Efficiency and demutualization: Evidence from the us life insurance industry in the 1980s and 1990s. Journal of Risk and Insurance, 74(3), 683–711. https://doi.org/10.1111/j.1539-6975.2007.00230.x
Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3(4), 305-360. https://doi.org/10.1016/0304-405X(76)90026-X
Jiang, W., Ren, J., Yang, C., & Hong, H. (2018). On optimal reinsurance treaties in cooperative game under heterogeneous beliefs. Insurance Mathematics and Economics, 85, 173-184. https://doi.org/10.1016/j.insmatheco.2018.12.004
Kaffash, S., Azizi, R., Huang, Y., & Zhu, J. (2019). A survey of data envelopment analysis applications in the insurance industry 1993–2018, European Journal of Operational Research, 284(3), 801-813. https://www.sciencedirect.com/science/article/abs/pii/S0377221719305983
Kahane, Y. (1978). Generation of investable funds and the portfolio behavior of non-life insurers. The Journal of Risk and Insurance, 45(1), 65-77. https://doi.org/10.2307/251808
Moran, M., & Salisbury, D. (2014). Sanctions and the insurance industry: Challenges, risks and opportunities. Business and Politics, Cambridge University Press, 16(3), 429-451. https://ideas.repec.org/a/cup/buspol/v16y2014i03p429-451_00.html
Mozaffari, M. R., Kamyab, P., Jablonsky, J., & Gerami, J. (2014). Cost and revenue efficiency in DEA-R models. Computers & Industrial Engineering, 78, 188 –194. https://doi.org/10.1016/j.cie.2014.10.001
Namdar, M. R., Gharekhani, M. (2018). Analysis the effect of detariffication on the performance of Iranian insurance using mathematical and statistical modeling. The Journal of Productivity Management, 12(2), 153-176. https://sanad.iau.ir/Journal/jpm/Article/976213 [In Persian].
Naseri Khezerloo, S., Seddigh Noohi, M., & Abdoli, A. (2023). Evaluating the impacts of reducing the compulsory reinsurance share on the performance of insurance companies and the outlook of the reinsurance market [Conference Paper]. 30th National Conference on Insurance and Development. https://civilica.com/doc/2115334 [In Persian].
Nekouei Dastjerdi, L. A. (2025). Applied Reinsurance. Research Institute of Insurance, affiliated with the Central Insurance of the Islamic Republic of Iran. https://www.irc.ac.ir/_douranportal/documents/book/1404-03-13-2.pdf [In Persian].
Pasiouras, F., & Gaganis, C. (2013). Regulations and soundness of insurance firms: International evidence. Journal of Business Research, 66(5), 632-642. https://doi.org/10.1016/j.jbusres.2012.09.023
Plantin, G. (2006). Does reinsurance need reinsurers? Journal of Risk and Insurance, 73(1), 153-168. https://doi.org/10.1111/j.1539-6975.2006.00169.x
Rubio-Misas, M. (2022). Analysis of insurers' performance using frontier efficiency and productivity methods, The great contributions by David Cummins and Mary Weiss. Risk Management and Insurance Review, 25, 445–489. https://doi.org/10.1111/rmir.12227
Shiu, Y. (2004). Determinants of United Kingdom general insurance company performance. British Actuarial Journal, 10(5), 1079-1110. https://doi.org/10.1017/S1357321700002968
Thanassoulis E. (2001). Introduction to the Theory and Application of Data Envelopment Analysis: A Foundation Text with Integrated Software. Springer Inc. https://doi.org/10.1007/978-1-4615-1407-7
Torkavannejad, M., Daneshian, B., Tohidi, G., Maghbouli, M., & Modarres Khiyabani, F. (2023). Efficiency analysis in multi-period system using DEA-R models. International Journal of Applied Operational Research, 11(2), 59-75. http://ijorlu.lahijan.iau.ir/article-1-643-en.html
Weiss, M. A., & Chung, J. (2004). U.S. Reinsurance Prices, Financial Quality, and Global Capacity. Journal of Risk and Insurance, 71(3), 437-467. https://doi.org/10.1111/j.0022-4367.2004.00098.x
Yan, T., Park, K., & Wong, H. Y. (2022). Irreversible reinsurance: A singular control approach. Insurance: Mathematics and Economics 107, 326-348. https://doi.org/10.1016/j.insmatheco.2022.09.004
Zhu, S., & Shi, J. (2022). Optimal reinsurance and investment strategies under mean-variance criteria: Partial and full information. Journal of Systems Science and Complexity, 35, 1458-1479. https://doi.org/10.1007/s11424-022-0236-3

Letters to Editor


IJIR Journal welcomes letters to the editor for the post-publication discussions and corrections which allows debate post publication on its site, through the Letters to Editor. Letters pertaining to manuscript published in IJIR should be sent to the editorial office of IJIR within three months of either online publication or before printed publication, except for critiques of original research. Following points are to be considering before sending the letters (comments) to the editor.

[1] Letters that include statements of statistics, facts, research, or theories should include appropriate references, although more than three are discouraged.

[2] Letters that are personal attacks on an author rather than thoughtful criticism of the author’s ideas will not be considered for publication.

[3] Letters can be no more than 300 words in length.

[4] Letter writers should include a statement at the beginning of the letter stating that it is being submitted either for publication or not.

[5] Anonymous letters will not be considered.

[6] Letter writers must include their city and state of residence or work.

[7] Letters will be edited for clarity and length.
CAPTCHA Image