Integrated Risk Management: Banking and Chemical Safety

This study conducted a comparative conceptual analysis of risk management approaches in banking and chemical processing industries, concentrating on credit risk management and process safety risk management, respectively. The research investigated underlying frameworks, including Basel II/III and IFRS ۹ in banking, and HAZOP, LOPA, and Quantitative Risk Assessment (QRA) in chemical safety, revealing significant similarities in risk identification, assessment, mitigation, and monitoring. Parallels in quantitative tools were identified between credit risk indicators (Probability of Default, Loss Given Default, and Exposure at Default) and safety metrics (frequency, consequence analysis, risk matrices). The study examined artificial intelligence applications in predictive modeling for both credit defaults and process safety incidents, uncovering methodological overlap that enhances foresight and decision-making. Human and organisational influences on risk perception and control were investigated. Results produced a conceptual Integrated Risk Management Framework demonstrating the viability of applying unified risk principles across highly regulated but diverse industrial contexts. The framework integrates three pillars: predictive intelligence (leveraging advanced analytics, AI, and historical data), quantitative evaluation (systematic measurement of likelihood, severity, and exposure), and human systems management (addressing behavioural biases and fostering risk-aware cultures). This cross-sectoral approach enables knowledge transfer, establishes unified risk language, and promotes AI development synergies. The framework requires empirical validation through case studies and pilot implementations for practical application across financial and industrial sectors.

کلیدواژه ها:

Integrated risk management ، Credit risk ، Process Safety ، Basel III ، Hazop ، LOPA ، Artificial intelligence ، Risk modeling