Digital-Intelligent Banking for Sustainable Finance: Opportunities, Challenges, and Strategic Implications

Abstract

The integration of artificial intelligence, advanced analytics, and FinTech ecosystems into banking has reshaped sustainable finance, yet a unified theoretical framework linking digital intelligence capabilities to sustainability performance outcomes remains absent. Drawing upon Institutional Theory, Stakeholder Theory, and the Resource-Based View augmented by Dynamic Capabilities Theory, this study develops a conceptual framework positioning four dimensions of digital intelligence capabilities — AI and machine learning infrastructure, advanced data analytics and ESG monitoring, FinTech ecosystem integration, and intelligent automation — as mediating constructs translating institutional pressures and stakeholder expectations into four sustainability outcomes: ESG performance, risk management quality, financial inclusion, and environmental responsibility. Three moderating conditions — regulatory environment, institutional capacity, and digital divide conditions — shape the capability–outcome relationship in emerging economy banking contexts. Eight propositions formalise these arguments. The study advances a unified conceptual architecture, a precise mediating model, and contextually grounded moderating conditions with strategic and policy implications for emerging economies.

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