Climate Stress Testing and Banks’ Capital Buffer Resilience
- Erhabor Osaruyi Ph.D 1*, Imafidon Anthony 2
- DOI: 10.5281/zenodo.17399549
- UKR Journal of Economics, Business and Management (UKRJEBM)
This study examined the effect of climate stress testing (CST) on banks’ capital buffer resilience (BCBR) in Edo State, Nigeria, focusing on Zenith Bank Plc and Access Bank Plc. With increasing global concern over the financial impacts of climate-related shocks, the study aimed to assess how integrating CST influences capital adequacy and risk management among Nigerian deposit money banks. A survey research design was adopted, targeting 136 senior managers directly involved in risk, compliance, and capital planning. Using a structured questionnaire, data were analyzed with Percentage Distribution and Pearson Product Moment Correlation (PPMC) via SPSS version 25 at a 0.05 significance level. Results from the descriptive analysis revealed that 78% of respondents acknowledged their banks’ engagement in climate risk assessments, and 72% agreed that CST improves capital planning and regulatory preparedness. The inferential analysis demonstrated a strong positive correlation (r = 0.692, p < 0.05) between CST and BCBR, indicating that enhanced climate stress testing practices significantly improve capital buffer resilience. This finding implies that banks that actively simulate climate risk scenarios tend to maintain stronger capital adequacy ratios and are better positioned to absorb financial shocks arising from environmental risks. The analysis aligns with earlier empirical evidence from Nguyen (2023) and Okoye (2021), emphasizing that proactive CST adoption strengthens forward-looking risk management and supports regulatory compliance. Consequently, the study concludes that CST is an essential component of sustainable financial governance and systemic stability. It recommends that Nigerian banks institutionalize CST as part of their risk management framework, and that the Central Bank of Nigeria should standardize climate risk modeling to enhance comparability and regulatory oversight across institutions.

