Risk Perception Lag in Banking Systems: A Causal Panel Data Study of Temporal Inefficiencies in Risk Transmission and Model Adjustment

This study introduces Risk Perception Lag (RPL), defined as the temporal delay between actual changes in banking risk exposure and their reflection in internal risk measurement and governance systems. While traditional banking literature focuses on risk magnitude and predictive accuracy, this paper emphasizes the timing dimension of risk recognition. Using a bank-level panel data framework, the study decomposes RPL into three structural components: informational frictions, model inertia, and institutional delay. A multi-method empirical strategy is proposed, combining fixed effects models, difference-in-differences identification, instrumental variables, and dynamic System GMM estimation to address endogeneity and persistence in risk adjustment processes. The framework identifies macro-financial shocks and governance heterogeneity as key drivers of variation in RPL across institutions. Banks with slower model update cycles and higher governance complexity exhibit significantly higher lag in risk recognition, particularly during periods of financial stress. The contribution of this study is threefold. First, it introduces RPL as a measurable empirical construct in banking risk management. Second, it provides a causal identification strategy for estimating temporal inefficiencies in risk systems. Third, it extends Basel III and IFRS 9 literature by shifting attention from risk accuracy to risk responsiveness. The findings suggest that financial stability depends not only on how accurately risk is measured, but also on how quickly risk is incorporated into decision-making systems.