PARADIGM SHIFT IN FINTECH DEVELOPMENT IN THE AGE OF ARTIFICIAL INTELLIGENCE: FROM TOOL EMPOWERMENT TO ECOLOGICAL RECONSTRUCTION

Engineering notes

Key topics: autonomous driving, large language model. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

The rapid advancement of artificial intelligence, particularly the breakthroughs in large language models and AI agents, is driving a fundamental paradigm shift in the fintech sector. This paper proposes a theoretical framework to characterize the transition of fintech from a "tool empowerment" phase, where technology serves as an efficiency-enhancing instrument within existing financial structures, to an "ecological reconstruction" phase, where AI agents, embedded finance, and decentralized technologies fundamentally reshape the organizational forms, value creation mechanisms, and competitive dynamics of the financial industry. We develop a three-dimensional analytical framework encompassing technological architecture, institutional logic, and value network to systematically examine this transformation. Through a mixed-methods approach combining comparative case studies of 12 representative financial institutions and quantitative analysis of patent data from 2015 to 2025, we find that: (1) the paradigm shift follows a non-linear S-curve trajectory, with a critical inflection point occurring around 2023-2024; (2) AI agent-driven autonomous workflows can reduce operational costs by 35-48% while improving risk assessment accuracy by 22-31%; (3) the ecological reconstruction phase exhibits distinct network effects where platform-based financial ecosystems achieve 2.3-3.7 times higher customer lifetime value compared to traditional linear models; (4) the transition presents significant regulatory challenges, particularly regarding algorithmic accountability, data sovereignty, and systemic risk aggregation in interconnected AI-financial networks. Our findings contribute to the theoretical understanding of technology-induced institutional change in financial systems and offer practical implications for financial institutions, technology firms, and policymakers navigating this transformative period.

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