Hubert Gąsiński is a doctor of economic sciences, academic lecturer and banking practitioner with more than 25 years of professional experience. Since 2001, he has held managerial positions in the Polish banking sector. His academic work focuses on banking systems, financial risk, institutional change, digital financial services and quantitative forecasting. He combines research with practical experience in evaluating investment projects, financial condition and business plans.

Banking Risk Governance for Green AI and Clean Energy Investment A Financial Resilience Framework

Abstract: Clean energy and climate-technology projects require long-term capital, reliable risk assessment and financing structures that can withstand technological, regulatory and market uncertainty. Artificial intelligence can support project appraisal by combining technical performance data with information on energy prices, cash flows, policy incentives and climate exposure. Its use in lending decisions may, however, introduce model opacity, biased data, cybersecurity vulnerabilities and an increased risk of classifying weak environmental claims as credible green investment. This paper develops a banking risk-governance framework for the use of artificial intelligence in financing clean energy and sustainable digital infrastructure. It applies a conceptual synthesis of research on climate finance, investment appraisal, banking risk management, responsible artificial intelligence and energy-efficient information technology. The framework covers four stages of the financing process: project eligibility, risk estimation, financing design and post-financing monitoring. The analysis identifies practical uses of artificial intelligence in scenario testing, cash-flow forecasting, early-warning systems and the monitoring of energy performance and emissions. It also specifies governance conditions for responsible deployment. These include explainable models, independent validation, human review of material credit decisions, verified environmental data and regular assessment of external technology providers. For banks, the assessment of clean energy projects should also account for policy continuity, grid constraints, counterparty capacity and exposure to changing energy markets. The proposed framework connects climate objectives with the financial discipline required to make projects bankable and resilient. It shows how artificial intelligence can improve the allocation and monitoring of capital without replacing professional judgement or institutional accountability. The paper contributes a finance-based perspective to the discussion of clean energy solutions and Green AI by defining how banks can support sustainable investment while controlling algorithmic, technological and environmental risks.

Keywords: Climate Finance; Clean Energy Investment; Green AI; Banking Risk Management; Financial Resilience