同时，东吴证券持续打造的"反洗钱系统""全面风险管理平台"等，精准对接监管要求，构建实时动 态的合规与风险管理跟踪流程闭环，打造全景穿透式监测体系，实现高穿透的可视化风险管理分析、评 估和监测，全方位支撑公司业务合规专业开展。 当前，证券行业文化建设迈入新阶段，科技正成为重塑行业生态、筑牢专业根基的核心引擎。《证 券行业文化建设十要素》中指出，证券公司作为资本市场最重要的中介机构之一，是资本市场的"看门 人"、直接融资的"服务商"、社会财富的"管理者"、金融创新的"领头羊"，专业是行业机构安身立命之 本和核心竞争力之所在。十五五阶段，持续提升金融科技将是证券公司适应国际化发展趋势，打造差异 化发展的"硬实力"；积极运用数字化手段重构商业模式、提升客户服务质量和水平，用专业赢得口碑、 信赖与尊重，将是增强证券公司专业化发展的"软实力"。 东吴证券积极响应"科技自立自强""引领发展新质生产力"等国家战略，践行"五要五不"原则，扎实 推进"五篇大文章"，严格遵循《进一步巩固推进证券行业文化建设工作安排》《树立证券行业荣辱观的 倡议书》等文件要求，持续夯实企业文化根基。公司以"科技+文化"深度融合为路径，依托业技融合 ...

Core Insights - The emergence of large models like DeepSeek has initiated a quiet AI revolution in the brokerage industry since early 2025, with a noticeable acceleration in AI deployment during the recent holiday period, leading to the launch of new features such as smart investment advisory and trading tools [1][3]. Group 1: AI Applications in Brokerage - Brokerages are transforming their apps from mere trading tools into comprehensive investment assistants, exemplified by Guotai Junan Securities' launch of the AI-driven app "Guotai Junan Lingxi," which integrates general large models with specialized models [1][3]. - Dongwu Securities has introduced a personalized AI service officer "AI Xiaoshuidi" in its self-developed "Xiucai APP," offering multi-turn dialogue investment advisory covering 13 dimensions, including market trends and data analysis [3][5]. - AI applications in brokerage services are diversifying, enhancing areas from wealth management to investor education, with firms like Huatai Securities and GF Securities actively integrating AI into their operations [5][9]. Group 2: Intelligent Investment Advisory - Intelligent investment advisory services have become one of the most mature AI applications in brokerage apps, allowing for tailored investment plans based on in-depth analysis of customer behavior and preferences [7][11]. - Guojin Securities' AI advisory system utilizes multi-dimensional user profiling to create customized investment strategies, providing real-time trading signals and visual prompts through its app [7][9]. Group 3: Operational Efficiency and Training - Brokerages are enhancing operational efficiency through AI, with some firms implementing intelligent front-office systems that automate tasks like business documentation and client verification, significantly reducing processing times [11][13]. - Employee training programs focused on AI are being established to improve staff's digital literacy and skills, ensuring that the workforce is equipped to leverage AI technologies effectively [5][11]. Group 4: Regulatory Developments - The China Securities Association has proposed new standards for the stability of information systems in the brokerage industry, emphasizing the integration of AI algorithms and big data analytics into stability management processes [14][16]. - The shift towards AI-driven decision-making in trading raises questions about the balance between algorithmic efficiency and human judgment in investment strategies [16].

Core Insights - The article discusses the increasing integration of artificial intelligence (AI) in the wealth management sector of brokerage firms, transforming operations from a "human sea tactic" to "human-machine collaboration" [1][8] - AI applications are now systematically embedded in various aspects of brokerage services, including client engagement, investment decision-making, trade execution, and operational management [1][8] AI Product Development - Brokerage firms have been actively launching new AI products since the beginning of the year, with significant advancements in their wealth management services [3] - Notable developments include the upgrade of the "易淘金APP" by Guangfa Securities, which features over ten AI modules, and the introduction of the "国泰海通灵犀" app by Guotai Junan, which offers three main intelligent service interfaces [3] - Other firms like Caida Securities and Dongwu Securities have also integrated AI algorithms into their apps to provide comprehensive intelligent solutions throughout the investment cycle [3] Investment Advisory Services - In the investment advisory domain, firms like Guojin Securities and China Galaxy Securities have launched AI-driven advisory services, offering features such as AI stock selection and fund optimization [4] - Digital employees powered by AI are being deployed for investor education and to assist in various advisory tasks, enhancing the efficiency of human advisors [4] Wealth Management Transformation - AI is reshaping the wealth management landscape by enhancing decision-making, customer insights, and risk control, transitioning from auxiliary tools to core intelligence [6][8] - Successful case studies highlight the operational efficiency improvements achieved through AI, such as reducing the time required for institutional account openings by 60% and lowering rejection rates by 48% [7] Industry Challenges and Future Outlook - The industry is moving from a reliance on physical branches and personnel to a model driven by data and AI capabilities, emphasizing the need for personalized financial services [8][9] - Despite the advancements, challenges remain, including the gap between AI models and real-world applications, as well as the need for better alignment between business needs and technological resources [9] - The future of brokerage firms will depend on their ability to leverage data effectively and integrate AI into all aspects of their operations [9]

Core Insights - The integration of artificial intelligence (AI) in the wealth management sector of brokerage firms is transforming operations from traditional human-driven methods to intelligent, data-driven approaches [1][7][8] - AI applications are being deployed across various functions, including customer engagement, investment advisory, trading execution, and operational management, leading to enhanced efficiency and competitive advantages [1][4][7] Group 1: AI Product Development - Brokerage firms are continuously launching new AI products, enhancing their wealth management services with features like AI-driven investment assistants and trading tools [2][3] - Notable examples include Guangfa Securities' AI-native upgrade of its "Yitaojin APP" and the introduction of comprehensive AI services by firms like Guotai Junan and Dongxing Securities [2][3] Group 2: Operational Efficiency - AI is being utilized to streamline operations, such as automating customer service and improving response times through intelligent platforms [5][6] - A central brokerage firm reported a 60% reduction in operational time for institutional account openings by implementing AI-driven processes [4][6] Group 3: Market Transformation - The industry is shifting from a "people-intensive" model to one that emphasizes "human-machine collaboration," with AI playing a crucial role in decision-making and risk management [1][7] - The competitive landscape is evolving, focusing on data-driven insights and personalized financial services to meet the diverse needs of clients [7][8] Group 4: Challenges and Future Outlook - Despite the advancements, challenges remain in aligning AI capabilities with real business needs, as well as resource constraints for some brokerage firms [8] - The future of AI in the industry is expected to involve a complete restructuring of business and technology platforms, emphasizing the importance of data as a core asset [8]