An Integrated Risk Management Algorithm for Economic Catastrophes: From Exogenous Shocks to Endogenous Vulnerabilities

Modern economic catastrophes are increasingly driven by the endogenous accumulation of risk rather than by isolated exogenous shocks. Although natural disasters, financial crises, and trade disruptions continue to act as triggers, their economic impact is largely determined by structural conditions that evolve gradually and rupture under stress. This paper develops an integrated risk management algorithm that conceptualizes catastrophe risk as a dynamic and systemic process rather than a discrete event. Building on a four-layer framework – hazards, exposure, vulnerability, and resilience – the study synthesizes insights from disaster economics, systemic risk theory, and the literature on global trade fragmentation to propose a transferable analytical architecture applicable across economic domains. Time dynamics and governance quality are introduced as cross-cutting dimensions that shape the transmission, amplification, and mitigation of shocks. Instead of aiming at deterministic crisis prediction, the algorithm enables continuous monitoring of slow-forming structural fault lines, interaction effects, and potential threshold points. The paper is designed as a conceptual review and methodological synthesis that demonstrates how integrated risk assessment can support proactive economic governance. Adaptive policy instruments, technological upgrading, diversification, and institutional coordination are interpreted as protective layers that deepen systemic resilience and reduce the probability of catastrophic outcomes. By shifting the analytical focus from ex post crisis response toward structured foresight and resilience-oriented policy design, the framework contributes to contemporary debates on stability in an increasingly fragmented global economy. The proposed algorithm provides a flexible foundation for future empirical modeling and cross-sectoral applications.