Climate-Related Operational Risk in Banking: A Critical Review and Methodological Roadmap

Physical climate hazards—floods, storms, heatwaves, and wildfires—are increasingly disrupting banking operations and generating growing litigation and legal-risk exposures, yet operational risk remains one of the least studied channels through which climate change may affect financial institutions. This paper provides a critical review of the emerging literature on climate-related operational risk in banking, covering both physical disruptions and the legal risk dimension explicitly recognised within the Basel operational risk framework. We map the empirical evidence, critically evaluate the methodological toolkit—event studies, fixed-effects regressions, difference-in-differences, dynamic panel estimators, and logit models—and assess their suitability for a domain characterised by data scarcity, rare events, and non-linearity. Building on this assessment, we outline a conceptual methodological roadmap intended to guide future research, organised around three stages: (i) machine learning-based variable selection and anomaly detection applied to operational loss and climate databases; (ii) econometric modelling of climate-related operational events with explicit identification strategies; and (iii) agent-based modelling to simulate system-wide propagation of climate shocks. Each stage can be conceptually related to elements of the Basel operational risk framework, offering a structured research programme for academics and a diagnostic toolkit for supervisors and risk managers.