Document Type : Original Research Paper

Authors

• Reza Farid ¹
• Shahryar Nessabian ²
• Mahnaz Rabiei ³

¹ PhD student in Economics, Department of Economic Sciences, Kish International Branch, Islamic Azad University, Kish, Iran

² Economics Department, Islamic Azad University, Central Tehran Branch, Tehran, Iran

³ Department of Economics, Islamic Azad University, South Tehran Branch, Tehran, Iran

Abstract

Extended Abstract
BACKGROUND AND OBJECTIVES:
Financial system stability constitutes a fundamental prerequisite for sustainable economic growth and the preservation of public confidence in contemporary economies. Within this architecture, banks and insurance companies function as two interconnected pillars whose complementary roles in resource mobilization, capital allocation, and risk management have become increasingly interdependent. The proliferation of joint investments, cross-ownership structures, and institutional interactions has progressively blurred the traditional boundaries between banking and insurance activities, rendering isolated analyses of either sector both theoretically inadequate and practically misleading. Despite the growing body of literature on banking stability and insurance resilience as separate domains, a significant theoretical and empirical gap persists: no coherent framework has yet been developed to systematically analyze the institutional synergy between banks and insurance companies and its cascading implications for financial system stability. This study addresses this lacuna by deploying the Hybrid Institutional Dynamics Model (HIDM) as a novel analytical framework that simultaneously quantifies three critical institutional mechanisms—governance quality, adaptive learning capacity, and network interactions—to examine how bank-insurance synergy can be leveraged to strengthen insurance industry resilience and financial system stability.
METHODS:
This study adopts a pragmatic research paradigm and employs a sequential multi-phase quantitative design. The empirical analysis encompasses a purposive sample of nine Iranian banks, stratified by ownership structure into state-owned, privatized, and private categories, alongside their linked insurance companies, covering a twelve-year period from 2014 to 2025, with particular emphasis on the critical years of 2022 and 2025 during which banking crises, economic shocks, and social unrest converged. Data were sourced from audited financial statements, insurance solvency reports, and macroeconomic indicators. The analytical framework is structured around the HIDM model, which operates across three interconnected phases. Phase 1 employs Dynamic Data Envelopment Analysis with a Network Slack-Based Measure approach and carry-over variables to compute dynamic efficiency scores for each financial institution. Phase 2 utilizes a Dynamic Bayesian Panel Probit model with a lagged dependent variable to estimate the non-linear and threshold effects of institutional quality, adaptive learning capacity, and network centrality on the probability of financial distress and institutional synergy. Model estimation was conducted using Markov Chain Monte Carlo simulation with 10,000 iterations in PyMC3, with convergence confirmed through the Gelman-Rubin diagnostic. Phase 3 calibrates an Agent-Based Model with heterogeneous financial institutions and an adaptive regulator, simulating three policy-relevant scenarios—exchange rate shocks, price shocks, and smart supervision—over a 40-quarter horizon.
FINDINGS:
The empirical results reveal several critical findings. First, a significant institutional efficiency gap exists between state-owned and private financial institutions, with private banks (Eit=0.792) and private insurance companies (Eit=0.753) consistently outperforming their state-owned counterparts by approximately 30 percent. This divergence reflects the adverse effects of government fiscal dominance, weak corporate governance, and political intervention on resource allocation efficiency in both sectors. Second, governance quality emerges as the strongest predictor of institutional synergy, with a coefficient of 0.312 and a Bayes Factor of 10.4, providing decisive statistical evidence for the centrality of transparency, accountability, and regulatory independence in fostering bank-insurance collaboration. Third, adaptive learning capacity exerts both a direct positive effect on institutional synergy (β=0.245) and a significant moderating effect that amplifies the impact of governance quality (Git × Lit interaction β=0.156), functioning as what can be characterized as an "institutional shock absorber." Fourth, network interactions contribute positively to synergy both independently (β=0.198) and through their interaction with governance quality (Git × Nit interaction β=0.127). However, a cautionary finding emerges: dense network connections, in the absence of robust governance mechanisms, can transform from risk-mitigating conduits into channels for accelerated systemic contagion. Fifth, the HIDM model demonstrates 87.9 percent predictive accuracy (AUC=0.879) with a nine-month early warning capability, offering a quantitative, interpretable, and institution-sensitive tool for systemic risk surveillance.
CONCLUSION:
This study establishes that financial system stability is not the product of isolated bank or insurance company performance, but rather emerges from the quality of institutional interactions between these two pillars. The three mechanisms of governance quality, adaptive learning, and network interactions operate synergistically rather than independently, meaning that deficiencies in any single dimension cannot be fully compensated by strengths in the others. The critical policy implication is that regulators must transcend sectoral approaches and adopt an integrated strategy that simultaneously enhances all three mechanisms across the entire financial system. The establishment of a Financial Stability Coordination Council jointly operated by the Central Bank and the Central Insurance authority, the institutionalization of quarterly Git, Lit, and Nit monitoring as supervisory key performance indicators, and the operational deployment of the HIDM Early Warning System within the financial stability directorate represent urgent strategic imperatives for safeguarding financial system stability.

Keywords

• Financial System Stability
• Bank-Insurance Synergy
• Insurance Industry Resilience
• Hybrid Institutional Dynamics Model (HIDM)
• Adaptive Learning

Main Subjects

• Economics of finance / insurance