Advanced frameworks for operational risk management in banking technology infrastructure and systems
Posted: Oct 28, 2025
Abstract
The evolution of banking technology infrastructure has introduced unprecedented complexity in operational risk management. Traditional frameworks, largely derived from Basel II and III accreditations, have demonstrated significant limitations in addressing the dynamic, interconnected nature of modern financial systems. These conventional approaches predominantly rely on historical loss data, statistical modeling, and predefined risk categories, which fail to capture emergent risks arising from system interdependencies, cyber threats, and technological innovations. The increasing integration of artificial intelligence, cloud computing, and distributed ledger technologies has further complicated the risk landscape, creating vulnerabilities that transcend traditional organizational and technological boundaries. Operational risk in banking technology encompasses a broad spectrum of potential failures, including system outages, data breaches, cyber attacks, and process deficiencies. Current risk management methodologies often treat these elements as discrete, independent factors, overlooking the complex interactions that can amplify individual vulnerabilities into systemic threats. This research addresses these limitations by developing a novel operational risk management framework that integrates quantum-inspired computational methods with adaptive system theory. The proposed Quantum-Resilient Operational Risk Architecture (QRORA) represents a paradigm shift from reactive, historical-based risk assessment to proactive, predictive risk management. By modeling banking technology infrastructure as a complex adaptive system and applying quantum computational principles to risk analysis, QRORA enables financial institutions to identify latent vulnerabilities, predict emergent risk patterns, and implement targeted mitigation strategies.
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