Digital Transformation in Green Financial Management: Leveraging Technology for Efficiency and Profitability

Edwin Agus Buniarto, Ratih Astiakurnia Putri, Arung Lamba, Alfredo Dos Santos, Loso Judijanto

Abstract

This study investigates the role of digital transformation in green financial management, focusing on how digital technologies such as artificial intelligence (AI), blockchain, and big data enhance efficiency and profitability while supporting sustainability goals. The research aims to answer how these technologies can be effectively leveraged to improve green finance practices and contribute to sustainable development. A qualitative approach, primarily using literature review and thematic analysis, was employed to explore existing studies and synthesize insights on the application of digital tools in green financial management. The findings reveal that digital technologies significantly improve operational efficiency by optimizing resource management, reducing costs, and enhancing decision-making processes in green finance. Blockchain technology, in particular, was found to increase transparency and investor confidence in green financial products like green bonds. However, barriers such as high initial investment costs, security concerns, and the lack of technical expertise remain challenges to widespread adoption. This study contributes to the literature by providing a deeper understanding of the practical applications and challenges of digital transformation in green financial management, expanding current models of sustainable finance. The findings offer practical implications for policymakers and businesses, emphasizing the importance of technological readiness and government support in fostering digital adoption. Future research should explore the long-term environmental impacts of digital tools and the role of organizational culture in facilitating their integration.

 

Keywords: digital transformation, green financial management, artificial intelligence, blockchain, operational efficiency.

 

DOI https://doi.org/10.55463/issn.1674-2974.52.11.8


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