Document Type : Original Research Paper

Authors

• Mohsen Gharahkhani ¹
• Marjan Gharahkhani ²
• Feryal Farakesh ³

¹ Ph.D., Department of Accounting, Faculty of Finance and Accounting, Iranian eUniversity, Tehran, Iran.

² PhD Student, Department of Industrial Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran.

³ Master's degree, Department of Management, Faculty of Management, Science and Technology, Amirkabir University of Technology, Tehran, Iran.

Abstract

BACKGROUND AND OBJECTIVES: The financial solvency and sustainability of insurance companies is widely recognized as a fundamental cornerstone of financial system stability, given the central role insurers play in risk transfer, loss absorption, and long-term capital allocation. Solvent insurance institutions contribute to economic resilience by protecting policyholders, limiting contagion effects, and reinforcing trust in financial markets. International experience, particularly during episodes of financial disstress and insurance market disruptions, has shown that weaknesses in insurers’ financial soundness can propagate systemic risk, amplify macroeconomic shocks, and undermine the effectiveness of regulatory frameworks. As a result, supervisory authorities increasingly emphasize the development of early-warning mechanisms and analytical tools capable of monitoring and forecasting insurers’ financial conditions in a timely and reliable manner. In this context, identifying the determinants of insurers’ financial solvency and constructing empirically robust predictive models have become key research priorities. While several internationally recognized frameworks—such as Risk-Based Capital Systems, Solvency II, and Financial Soundness Indicators—have been developed and applied across advanced insurance markets, their empirical adaptation to emerging and developing insurance systems remains limited. In Iran, despite the expansion of the insurance industry, increased private sector participation, and greater product complexity, empirical studies that integrate global solvency frameworks with firm-level domestic data are still relatively scarce. Accordingly, the primary objective of this study is to identify the key financial factors influencing the solvency of Iranian insurance companies and to develop an analytical model for predicting their financial condition based on internationally accepted financial soundness frameworks.
METHODS: This study adopts a quantitative approach grounded in established international solvency assessment methodologies. A comprehensive set of indicators was constructed using the CARAMELS framework and Financial Soundness Indicators (FSIs), capturing critical dimensions of insurers’ financial health, including capital adequacy, asset quality, reinsurance structure, actuarial soundness, management efficiency, profitability, liquidity, and sensitivity to risk. Financial data were extracted from the audited financial statements of Iranian insurance companies over the study period and subjected to rigorous preprocessing procedures, including data validation, standardization, normality assessment, and the mitigation of multicollinearity among explanatory variables. Given the binary nature of the dependent variable indicating improvement or deterioration in financial solvency, a logistic regression model was employed to estimate the probability of maintaining adequate solvency. Model parameters were estimated using maximum likelihood techniques, and model adequacy was evaluated through standard goodness-of-fit measures and classification performance indicators. To assess the robustness and stability of the estimated relationships, a sensitivity analysis was conducted by examining changes in coefficient estimates and predictive outcomes under alternative specifications. This methodological design allows both explanatory insight into solvency drivers and practical predictive capability for supervisory use.
FINDINGS: The empirical results indicate that the estimated model demonstrates a strong predictive performance and satisfactory explanatory power. The final specification achieves an overall prediction accuracy of 84 percent, with a Pseudo R² value of 0.42, suggesting a substantial improvement over baseline models and confirming the relevance of the selected financial soundness indicators. Capital adequacy variables exhibit a positive and statistically significant relationship with financial solvency, highlighting the importance of strong equity positions and sufficient capital buffers in enhancing insurers’ resilience. Profitability measures, particularly return on assets (ROA), also show a significant positive effect on solvency, reflecting the role of efficient asset utilization and sustainable earnings generation in supporting long-term financial stability. Liquidity-related indicators similarly exert a positive influence, underscoring the importance of maintaining adequate liquid resources to meet short-term obligations and absorb unexpected shocks. In contrast, variables associated with insurance risk exposures such as outstanding claims reserves and policyholder-related liabilities demonstrate statistically significant negative effects on solvency. These results suggest that excessive reserve burdens and growing insurance liabilities can materially weaken insurers’ financial positions if not properly managed. The sensitivity analysis confirms the stability of the estimated coefficients, as both the direction and relative magnitude of key effects remain consistent across alternative model specifications.
CONCLUSION: The findings of this study indicate that capital strength, profitability, and effective liquidity management are central determinants of financial solvency in the Iranian insurance industry, while insufficient control of insurance-related liabilities poses a significant risk to financial stability. By integrating internationally recognized financial soundness frameworks with localized firm-level data, this research provides a practical and analytically robust model for monitoring and forecasting insurers’ financial conditions. The proposed approach offers valuable implications for regulatory authorities seeking to strengthen early-warning systems, for insurance company managers engaged in strategic financial planning, and for policymakers aiming to enhance the resilience and stability of the national insurance system. Overall, the study demonstrates that internationally established solvency assessment frameworks can be effectively adapted to emerging insurance markets when combined with appropriate econometric techniques and context-specific data. The results provide a solid empirical foundation for future research and for the development of more advanced, data-driven solvency monitoring tools in the insurance industry.

Keywords

• Caramels model
• Financial solvency
• Financial soundness
• Insurance company
• Insurance research center
• Logistic regression

Main Subjects

• Financial wealth