The convergence of Artificial Intelligence (AI) and sustainable banking is transforming the global financial landscape, presenting both extraordinary opportunities and significant challenges. This paper provides an in-depth review of AI applications in the banking sector, elaborating on their role in advancing efficiency, enhancing customer experience and promoting financial inclusion, while also examining their implications for sustainability. Drawing on a thematic analysis of scholarly literature, case studies, industry reports and studies, this analysis identifies key applications of AI in fraud identification, credit risk management, wealth management, customer service automation and regulatory compliance. Further than operational welfare, the review centre is evolving sustainability-focused on uses of AI, comprising environmental, social and governance (ESG) risk calculation and green finance simplification. However, major challenges remain, notably data privacy risks, algorithmic bias, regulatory uncertainty, high operational costs, workforce disruptions and the environmental impact of AI systems. The analysis underscores significant gaps in aligning AI adoption with broader sustainability goals, regulatory expectations and ethical standards. To address the identified loopholes, this research recommends future research strategies focused on the development of accountable AI frameworks, explainable AI, stronger regulatory harmonization and inclusive financial contact. The findings contribute to both theory and practice by combining fragmented insights, providing a structured framework for indulgent AI’s dual role in efficiency and sustainability and offering legal guidance for policymakers, regulators and banking authorities. Ultimately, this study highlights AI not only as a driver of operational conversion but also as a catalyst for building a more comprehensive, robust and practical global banking environment.

As global climate concerns intensify alongside China’s pursuit of carbon neutrality, the low-carbon transition of the manufacture industry has become an urgent necessity. As a key driver in the digital era, how FinTech can effectively facilitate this transition has emerged as a critical issue. Therefore, this study selects panel data from 30 Chinese provinces spanning 2004 to 2023 to examine the mechanisms through which FinTech influences low-carbon development of manufacture industry. The study shows: (1) FinTech exerts a direct promoting effect on the low-carbon development of the manufacture industry, but this effect is only significant in regions with high levels of FinTech. (2) FinTech indirectly facilitates low-carbon transformation through stimulating green technology innovation and reducing energy intensity. (3) Government environmental attention and human capital exhibit stage-specific moderating roles along the transmission pathway, the former amplifies FinTech’s driving force on technological innovation, whereas the latter accelerates the conversion efficiency of innovation outcomes. Building upon these findings, this study proposes the following targeted policy recommendations: regions with underdeveloped financial infrastructure should promote the integration of FinTech with traditional financial services; green technology innovation should be strengthened through dedicated funds, while energy efficiency should be enhanced via integrated “energy-efficiency loans with digital management systems”; government should build a phased and multi-party collaborative policy system, combining stronger policy guidance at the front end with enhanced cultivation of interdisciplinary talent at the back end, ultimately forming a comprehensive support system. This research elucidates the dual pathways and conditional mechanisms through which FinTech drives low-carbon development in manufacturing, offering strategic insights for aligning technological innovation, financial support, and policy guidance.