Group 1 - The core objective of the company is to leverage AI to address real industry problems, with a 10-year strategic plan called "New 310" aimed at providing comprehensive user insights, personalized expert services, and real-time interactions, ultimately becoming the AI CFO for millions of small and micro enterprises [1] - The company aims to develop an "AI credit expert" to facilitate online approval for medium to large loans, ensuring stable credit limits, supported by two AI assistants: one for industry research and another for due diligence [1] - In the area of AI wealth management, the company plans to introduce tools like the "Redemption Intelligent Operation Engine" and "Capital Structure Adjustment Engine" to enhance the stability of returns for partner institutions, with the former already implemented in 14 institutions, reducing return volatility by 5 basis points compared to market averages [1] Group 2 - In AI marketing, the company is shifting from broad marketing strategies to personalized approaches, aiming for "one strategy per person" to enhance user engagement and satisfaction [2] - The company emphasizes that the application of AI technology is not about replacing human roles but empowering individuals to become "super individuals," enhancing the capabilities of ordinary credit officers, wealth managers, and marketing personnel to better serve users and create incremental value [2]

Group 1: AI Applications in Banking - AI credit applications are crucial for banks, focusing on improving efficiency and quality in loan processes [2] - AI marketing utilizes user characteristics for intelligent modeling and enhances marketing strategies [3] - AI data capabilities help clients improve data analysis through natural language processing and data language conversion [3] - AI regulatory tools establish a bridge between raw data and final metrics for compliance and reporting [3] - AI knowledge bases assist clients in visualizing workflows and addressing specific business queries [3] Group 2: Challenges in AI Implementation - The accuracy of large models is generally high, but measures are in place to manage potential inaccuracies in client applications [4] - Implementing AI in client systems is complex due to existing architecture and processes, requiring a phased, modular approach [5] - Continuous technological advancements necessitate ongoing evaluation of new AI technologies for compatibility and application [5] - Communication barriers between technical and business teams can lead to mismatched requirements, which the company addresses by integrating algorithm personnel into business research [6] Group 3: Talent and Capability Development - Transitioning from IT product capabilities to business empowerment requires hybrid talent that understands both business needs and AI technology [6] - Product managers are essential for designing AI solutions that enhance client business capabilities and drive growth [6] Group 4: Risk Awareness - The content discussed in the investor relations activity does not constitute a substantive commitment from the company regarding future development plans or performance expectations [6]