Core Insights - The fund advisory business has evolved over six years, achieving steady growth in management scale and user base, with over 60 institutions now operating in this space and several exceeding 10 billion yuan in scale [1][2] - The industry has shifted from a "product-oriented" approach to a "service-oriented" model, with "user trust" becoming a central focus, significantly enhancing the investor experience [1][2] - Future developments will see advisory fees becoming the primary source of profit for advisory institutions, pushing the industry back to its wealth management roots [1][5] Development Milestones - The fund advisory business began its pilot phase in October 2019, coinciding with a golden period for public funds, leading to rapid scale expansion [1] - In 2022, institutions started to reflect on their strategies, moving towards "dynamic buy advisory strategies" to help users with timing and selection challenges in equity investments [2] - By October 15, 2023, the user accounts of a specific advisory program reported a profit ratio of 94.43%, demonstrating the effectiveness of the new strategies [2] Trust Building Challenges - Building investor trust is both a key focus and a challenge for the industry, requiring performance, companionship, and time [3][4] - Some advisory institutions have chosen to prioritize trust over scale, with a notable example being a firm that maintained close communication with clients, managing an average of 500 clients per advisor [3] - Data shows that advisory services have outperformed non-advisory accounts in terms of returns, with specific figures indicating a 7.01% higher return over the past year [4] New Opportunities - Recent reforms in fund fee structures emphasize prioritizing investor interests and preventing conflicts of interest, indicating a shift towards advisory fees as the main revenue source [5] - Institutions like Yingmi Fund are adapting their fee structures to align with these reforms, moving from transaction fee deductions to monthly advisory fees [5] - The transition to a more professional and personalized advisory service model is expected to create opportunities for outstanding institutions to thrive amid industry changes [6]

Core Viewpoint - Yingmi Fund has won the "Fund Advisory Institution Golden Bull Award" and the "Fund Advisory Excellent Return Golden Bull Award" at the "Third Fund Advisory Golden Bull Award" selection, emphasizing the importance of aligning with client interests and providing long-term support to navigate market cycles [1] Group 1: Investment Advisory Evolution - The buy-side advisory is transitioning from a fund portfolio-following 1.0 model to a client account management 2.0 model, focusing on personalized solutions based on clients' investment goals and risk tolerance [4] - Yingmi Fund's digital service system has significantly improved client investment experiences, with advisory clients showing a much longer average holding period compared to self-directed clients [4] Group 2: Client Education and Behavior Change - The complexity of financial products and market volatility creates a gap in understanding for the general public, which buy-side advisory aims to bridge by providing tailored solutions and enhancing client investment knowledge [2][3] - The goal of client education is to foster healthier investment habits and reduce emotional trading behaviors, ultimately leading to better investment outcomes [2] Group 3: Industry Trends and Future Outlook - The public fund industry is shifting from a focus on scale to prioritizing investor returns, aligning with the core philosophy of fund advisory services [4] - Yingmi Fund reports that over 89% of advisory clients on its platform were profitable as of June 30, 2025, with an average holding period of 690 days, indicating a successful adaptation to long-term investment strategies [4] - The future of fund advisory is expected to see more diverse institutions emerging, exploring various business models and enhancing the advisory ecosystem [5]

Core Insights - The launch of Manus and the popularity of the Model Context Protocol (MCP) have accelerated the development of intelligent agents among major companies since April 2023 [1][24] - Various companies have introduced MCP services, enhancing the capabilities of their intelligent agents and breaking down software barriers, leading to improved efficiency and accuracy [3][24] Group 1: Company Developments - Alibaba Cloud launched the MCP service on April 9, 2023, followed by Ant Group, ByteDance, and Baidu introducing their respective MCP integrations throughout April [1] - By April 29, 2023, multiple domestic companies, including Yingmi Fund and Guangfa Securities, had begun offering services through Alibaba's MCP platform, covering areas such as fund advisory and stock analysis [3][19] - Baidu's integration of MCP into its products allows users to complete transactions directly through intelligent agents, marking a significant step in e-commerce capabilities [13][16] Group 2: Performance Testing - Initial tests of Alibaba's MCP service showed a limited range of services, but subsequent tests revealed a growing number of providers and functionalities [3][19] - The intelligent agent created by the reporter was able to recommend specific funds after integrating with Yingmi Fund's MCP service, showcasing the enhanced capabilities of MCP [5][4] - ByteDance's intelligent agent demonstrated significant improvements in task execution speed and accuracy after integrating MCP, completing complex tasks in a fraction of the time compared to previous methods [9][12] Group 3: Market Trends and Challenges - The integration of MCP services is transforming platforms into application stores for AI, with companies exploring new business models and user engagement strategies [23][24] - The varying number of MCP services across different platforms indicates a competitive landscape, with each company aiming to enhance their offerings [19][20] - Concerns regarding the security of MCP protocols have been raised, highlighting the need for robust measures to protect user data and ensure safe interactions between intelligent agents [29][30]