稳定币概念局部回暖 恒生电子涨停 智通财经7月29日电，稳定币概念盘中局部回暖，恒生电子涨停，国投智能涨超10%，东信和平涨超5% 续创历史新高，中油资本、金证股份、拓尔思等冲高。消息面上，民生证券认为，《稳定币条例》于 2025年8月1日正式生效后，蚂蚁集团、京东等大厂依托深厚的区块链技术沉淀和丰富的内循环应用场 景，有望第一批获得香港金管局批准的稳定币牌照，构筑实质的稳定币及RWA的相关产业链。 ...

Core Viewpoint - The company has decided to establish an international headquarters in Singapore to enhance its international business development and explore Web3 ecosystem and stablecoin innovation applications [1] Group 1: International Headquarters - The establishment of the Singapore international headquarters aims to leverage local financial and technological advantages [1] - This move is expected to accelerate the company's globalization process [1] Group 2: Digital Strategy and Innovation - The company aims to enhance its technological capabilities and business expansion through the exploration of the Web3 ecosystem [1] - The initiative is anticipated to support future innovative projects in the digital field [1]

Group 1 - The World Artificial Intelligence Conference (WAIC) was held in Shanghai, highlighting the challenges faced by over 1.1 million small and micro enterprises in China, including poor risk resistance and information asymmetry [1] - Qifu Technology showcased its self-developed financial AI platform Deepbank and four core AI assistants, emphasizing the importance of high-quality data and a dynamic financial knowledge graph for the evolution of its credit intelligence [1] - The AI Compliance Assistant significantly improves compliance efficiency, reducing the time to interpret regulatory documents from 40 hours to 2 hours and increasing policy adaptation accuracy from 68% to 99.2% [1] Group 2 - The financial AI industry faces challenges related to the limitations of large models, including difficulties in understanding and executing instructions in complex scenarios, leading to potential inaccuracies [2] - Qifu Technology has discussed the application of embodied intelligence in financial business scenarios but currently does not prioritize it, as finance primarily operates in a digital realm without the need for physical interaction [2]

Core Viewpoint - SoFi Technologies is expected to report earnings on July 29, 2025, with historical data indicating a positive stock performance following earnings reports, achieving a positive return in 69% of instances [2][7]. Earnings Expectations - Analysts predict earnings of $0.06 per share on revenue of $804 million for the upcoming report, compared to $0.02 per share on revenue of $597 million in the same quarter last year [3]. Company Financials - SoFi Technologies has a market capitalization of $23 billion and generated $2.8 billion in revenue over the last twelve months, reporting a net income of $482 million [4]. Historical Performance - Over the last five years, there have been 16 earnings data points for SoFi, with 11 positive and 5 negative one-day returns, resulting in a 69% rate of positive returns. This rate drops to 67% when considering the last three years [7]. Post-Earnings Strategy - Traders can consider pre-earnings positioning based on historical odds or analyze the correlation between immediate and medium-term returns post-earnings to guide trading decisions [6][8]. Correlation with Peers - The performance of peer companies can influence SoFi's post-earnings stock reaction, with historical data showing that pricing may begin before earnings announcements [9].

Core Insights - Ant Group's Ant Financial Technology officially launched the financial reasoning model Agentar-Fin-R1 at the 2025 World Artificial Intelligence Conference, emphasizing the necessity of specialized financial models to bridge the "knowledge gap" in AI applications within the industry [1] - The Agentar-Fin-R1 model, based on Qwen3, outperformed other models in authoritative financial benchmarks, showcasing its strong reasoning capabilities for complex financial logic and data analysis tasks [1] AI Product Ecosystem - Ant Financial Technology has established a comprehensive AI ecosystem, covering everything from underlying technology to upper-layer applications, including the launch of Agentar-Fin-R1 and participation in the open-source release of the Ant Bailing model family [2] - The Ant Bailing model family includes language, reasoning, and multimodal models, with the open-source multimodal model Ming-lite-omni achieving over 30,000 downloads and being widely applied across various sectors [2] Intelligent Agent Platform - The company introduced the "Agentar Full-Stack Enterprise Intelligent Agent Platform," which integrates capabilities such as knowledge engineering and financial models, resulting in over 100 financial intelligent agent application solutions [2] - The platform effectively addresses challenges in efficiency, cost, data value, and security, facilitating large-scale applications of financial intelligent agents [3] Continuous Innovation - Ant Financial Technology has released industry solutions integrating AI technologies across four major products, including SOFAStack, Yidun, Mos, and mPaaS, targeting cloud-native, industry risk control, privacy computing, and mobile technology [4] - SOFAStack's 5.0 version aims to enhance enterprise research and development efficiency by 30% through end-to-end Copilot solutions [4] Privacy Protection and Data Management - The company proposed an innovative cross-domain fine-tuning framework, ScaleOT, which enhances model privacy protection by 50% while reducing computational power consumption by 90% [5] - OceanBase, as an integrated data foundation for the AI era, serves over 2,000 clients in finance and energy sectors, leading the local deployment market for distributed databases in China [5] Global Expansion - Ant Financial Technology is actively expanding its overseas market presence, offering AI innovations in financial technology to over 200 countries and regions, connecting more than 100 million merchants and 1.7 billion consumer accounts [6]

前言 亚布力论坛研究中心 2011年，中小企业与金融机构间的中介服务领域上存业务空白，许泽玮凭借敏锐的商业嗅觉，精准捕捉到这一潜在机遇，毅然投身金融科技创业浪潮。此 后十余年，他带领91科技集团一路披荆斩棘、不断发展壮大，成功构建起金融服务、媒体 + 文化服务、科创服务、司法服务四大核心业务板块，在激烈 的市场竞争中稳稳立足。 在旁人看来，91科技集团仿佛自带一种独特的"定力"。无论行业处于热度空前的上升期、问题暴露的调整期，还是趋于常态的稳定期，它都能在动态变化 的市场环境中稳步前行，展现出强大的抗风险能力与发展韧性。然而，稳健发展的背后，必然有一套行之有效的"密码"，这密码正是许泽玮这位青年企业 家成功掌舵企业航向的关键所在。 他究竟是如何敏锐捕捉到创业机遇？如何引领企业在风云变幻的市场浪潮中稳健前行？又如何能不断拓展业务边界，让企业在主赛道上深耕细作、绽放光 彩？本期《对话亚布力》栏目与91科技集团董事长许泽玮展开对话，让我们一同探寻他创业背后的成功密码。 许泽玮 91科技集团董事长 以下为对话内容： 亚布力论坛：在创业初期，你如何察觉到中小企业与金融机构之间的中介服务存在业务空白？ 许泽玮：其实在创业 ...

Core Insights - The core competitive advantage of Qifu Technology in financial AI lies in the deep integration of data assets, real-world scenarios, and its fintech DNA, creating a synergistic effect [1][3] - Since launching its financial large model strategy in 2023, Qifu Technology has shifted its service model from providing technical solutions to banks to delivering AI "productivity" [2] Data and User Base - Qifu Technology has accumulated over 100 million user financial data over nine years, forming a significant professional barrier that is difficult to replicate [1] - The business scale of Qifu Technology's subsidiary, Qifu Shuke, empowered by fintech solutions, surged approximately 144% year-on-year by March 2025 [3] AI Applications and Efficiency - Qifu Technology has developed the industry's first intelligent agent that empowers core credit business, consisting of various modules such as end-to-end credit decision-making and AI compliance assistants [2] - The efficiency leap is evident as intelligent agents have evolved from auxiliary roles to independent "digital employees," significantly enhancing the AUC of core scenario models by 1% [2] Cognitive and Perceptual Enhancements - Multi-modal intelligent agents have rapidly improved user understanding, driving key model AUC up by nearly one point, while image-enhanced intelligent agents have optimized over 70% of core user labels [2] Production Model Evolution - The end-to-end risk decision-making intelligent agent is taking shape, integrating over 700 models and more than 7,000 strategy modules, gradually becoming a strong supplement to traditional risk control systems [2][3] Strategic Collaborations - Qifu Technology's AI + finance strategic collaborations with multiple banks are accelerating the implementation of its solutions [3]

Core Viewpoint - Ant Group's financial reasoning model, Agentar-Fin-R1, has been officially launched, showcasing its advanced capabilities in financial specialization, reasoning, and compliance [4][5]. Group 1: Model Development and Features - Agentar-Fin-R1 is developed based on Qwen3 and surpasses other models like Deepseek-R1 in financial evaluation benchmarks, indicating its superior performance in the financial domain [5]. - The model is designed to address the "knowledge gap" present in general models, emphasizing the necessity for specialized financial reasoning models to enhance the integration of finance and AI [5][6]. - Ant Group has established a comprehensive training data system covering various financial sectors, ensuring the model is well-equipped with industry-specific knowledge [6]. Group 2: Training and Compliance - The training framework includes real transaction data and stringent quality assessments, resulting in a highly specialized financial dataset [6]. - The model incorporates synthetic data to ensure compliance with financial industry regulations, addressing issues such as identity verification and data security [6]. - Agentar-Fin-R1 is capable of achieving optimal performance in multiple financial evaluation sets while maintaining high standards of natural language understanding and generation [6]. Group 3: Efficiency and Adaptability - The model features an efficient weighted training algorithm that reduces the need for additional fine-tuning and computational resources, lowering the implementation costs for financial institutions [7]. - Agentar-Fin-R1 is designed for continuous evolution, utilizing RAG technology to stay updated with the latest financial policies and market dynamics [8]. - The model is available in two versions with 32 billion and 8 billion parameters, along with additional models to cater to diverse deployment needs in the financial sector [8]. Group 4: Market Reach and Vision - Ant Group has successfully served 100% of state-owned banks and over 60% of local commercial banks, indicating a strong market presence [8]. - The company envisions using AI to reshape all business processes in the era of large models, highlighting the transformative potential of AI in finance [8].

Core Insights - Ant Group's Ant Financial Technology has launched the Agentar-Fin-R1 financial reasoning model, designed to create a "reliable, controllable, and optimizable" intelligent core for financial AI applications [1] - The model, based on Qwen3, surpasses other open-source general models and financial models in key evaluations, demonstrating superior financial expertise, reasoning capabilities, and compliance [1] - Ant Group's CEO emphasized the necessity of specialized financial models to bridge the "knowledge gap" between general models and practical industry applications, indicating that the depth of application of financial models will be a key competitive factor for financial institutions [1] Data and Model Specifications - Agentar-Fin-R1 is available in two versions: 32 billion and 8 billion parameters, with additional models based on the MOE architecture for improved reasoning speed [2] - Non-reasoning versions of the model include 14 billion and 72 billion parameters to cater to diverse deployment needs of financial institutions [2] - Ant Group has developed a comprehensive financial task classification system with 6 major categories and 66 subcategories, covering various financial sectors such as banking, securities, insurance, funds, and trusts [1]

Core Viewpoint - Block has demonstrated significant growth and resilience in the fintech sector, recently being added to the S&P 500, indicating its strong market position and potential for future expansion [2][14]. Company Performance - Since its IPO in late 2015, Block has achieved a remarkable 510% stock price increase, significantly outperforming the S&P 500's 206% rise [2]. - The company's revenue has surged by 1,640%, while net income has increased by 867% [2]. - In the first quarter, excluding Bitcoin, Block reported revenue of $3.47 billion, an 8% year-over-year growth, and gross profit of $2.29 billion, climbing 9% [9]. - Operating income rose by 32% to $329 million, leading to adjusted earnings per share (EPS) of $0.56, a 19% increase [9]. - Gross payment volume (GPV) grew by 7.2%, with Cash App contributing to a 9% increase in gross profit per monthly active user [10]. Market Position and Analyst Sentiment - Block's inclusion in the S&P 500 reflects its strong position in the evolving fintech industry and the increasing mainstream adoption of Bitcoin [14]. - Despite lowering its guidance earlier in the year, 75% of analysts covering Block rate it as a buy or strong buy [11]. - Analyst Bryan Bergin maintains a buy rating with a price target of $115, suggesting a potential upside of 44% from the current stock price [12]. - The stock is currently valued at 19 times trailing-12-month earnings and 2 times sales, indicating it is relatively inexpensive given its growth potential [13]. Strategic Initiatives - Block has expanded its offerings beyond mobile payment processing to include a comprehensive suite of services such as business loans, digital retail, and consumer loans [6]. - The company has integrated its two main segments, Square Business and Cash App, to enhance user engagement and drive growth [6]. - Block has invested approximately $261 million in Bitcoin, holding 8,584 Bitcoin valued at around $1.03 billion, and plans to accept Bitcoin as a payment method [7].