蚂蚁数科余滨：“按效果付费”没有颠覆传统商业逻辑

Core Viewpoint - The integration of AI in the financial sector is transforming traditional business models, with a focus on a "pay-for-performance" approach that aligns AI applications with actual business outcomes [7][8][9]. Group 1: AI in Financial Services - AI is becoming a crucial tool for enhancing core competitiveness and reshaping service systems in the financial industry [7]. - The "pay-for-performance" model allows clients to pay based on the actual results achieved through AI applications, rather than traditional project-based or subscription models [8][9]. - Ant Group's AI capabilities are shifting from a tool delivery model to a business outcome-oriented approach, emphasizing collaboration with financial institutions to achieve measurable results [9]. Group 2: Market Demand and Client Needs - There is a significant demand from small and medium-sized financial institutions for solutions that address business growth and asset quality improvement [9]. - Many financial institutions are eager to explore AI applications, with regional banks making up two-thirds of Ant Group's current partnerships [9]. - The primary needs of financial institutions include solving business growth challenges, ensuring business security, and enhancing user experience [10]. Group 3: Data and AI Integration - The construction of a trusted data space is increasingly intertwined with AI applications, providing essential data governance and support for AI model training [10][11]. - The integration of AI and trusted data spaces is accelerating, with both areas overlapping in infrastructure development, such as computing centers and data platforms [11]. - High-quality, standardized data is critical for AI development, and trusted data spaces are key to ensuring data governance and reliability [11].