AI-Enabled ESG Integration in Banking Decision-Making: Governance Implications in European and Emerging Financial Systems

This study analyses how artificial intelligence (AI) enables the integration of environmental, social, and governance (ESG) factors into banking decision-making and examines its implications for sustainable governance in developed and developing financial systems. The study adopts a qualitative, multi-case comparative design based on the documentary analysis of ESG reports, annual reports, risk management reports, and governance documents from selected banks. The sample includes European banks with advanced AI–ESG integration, namely ING Group, BNP Paribas, Nordea Bank, and NLB Group Slovenia, alongside Raiffeisen Bank Kosovo as a case from a developing financial system. Methodologically, the study employs qualitative documentary analysis through deductive–inductive content analysis, supported by cross-case comparison and selective process tracing, to examine the links among ESG data, AI-based analytics, and financial decision-making. The findings indicate that European banks have more deeply embedded AI and ESG into risk management, lending, and portfolio allocation, supported by stronger governance and control mechanisms. In contrast, banks in emerging financial systems show partial integration, mainly focused on reporting and regulatory compliance. The study highlights the need to strengthen AI governance, transparency, and model risk management to support sustainable banking decision-making.