Core Insights - The integration of AI in the financial sector is enhancing operational efficiency and service quality, with AI's accuracy in risk control audits reaching 90% [1][8] - The 2025 Financial Street Forum highlighted the transition of AI from a technological application to a value-creating tool in finance, sparking discussions among experts [1][2] AI in Financial Services - AI is driving the intelligent upgrade of traditional insurance processes, improving pricing accuracy and risk prevention, thus addressing the shortcomings of conventional insurance models [1][2] - The penetration rate of large models in the financial sector is currently at 35%, with a focus on understanding specific scene demands and pain points for effective implementation [2] Data Governance and Collaboration - Emphasis on enhancing data governance through better data integration, quality improvement, and risk prevention is crucial for the development of digital insurance [2] - Collaboration between insurance institutions and academic research organizations is necessary to cultivate interdisciplinary talent for digital insurance [2] Financial Institutions' Practices - The financial support for technological innovation is increasing, but challenges remain, such as the reliance on indirect financing and mismatches in risk control for tech enterprises [3] - Asset management institutions are encouraged to focus on human-centered approaches to discover new asset values and optimize investor demand profiles [3] AI's Role in Banking - AI is becoming essential for city commercial banks to navigate challenges like narrowing net interest margins and intensified competition, transitioning from a cost center to a core service and value creation tool [4][5] - Different financial institutions are advised to adopt AI evolution paths suited to their capabilities, with regional banks encouraged to start with practical applications [5] Regional Financial Cooperation - The digital financial landscape among Shanghai Cooperation Organization (SCO) countries presents opportunities for collaboration despite existing disparities in digital finance levels [5] - Beijing is positioned to lead in areas such as digital currency, cross-border settlement, and data security, leveraging its technological and policy advantages [5][6] AI and Risk Management - Experts agree that AI is transforming financial business models, necessitating the establishment of matching risk governance systems [7] - The challenges posed by AI, including algorithmic opacity and data integrity, require a focus on human-machine collaboration and clear accountability in decision-making [7][8]
金融街论坛年会观察:金融AI应用如何创造价值?