机构对奇富科技长期基本面保持乐观。根据近期机构观点（2026年2月），奇富科技-S目标均价为 123.10港元，较当前价存在上行空间，评级以买入或增持为主；盈利预测显示，尽管短期承压，公司信 贷科技优势及轻资产转型有望支撑复苏。 近期事件 近期无公司-specific重大公告或事件。市场层面，中概股受宏观因素压制，如国际地缘政治紧张及行业 监管不确定性，可能加剧波动。 机构观点 来源：经济观察网 经济观察网 近一周（2026年2月18日至24日），奇富科技股价整体承压。在港股市场，奇富科技-S （03660.HK）区间累计下跌7.87%，最新收盘价为56.75港元（2月24日），单日下跌3.40%；在美股市 场，奇富科技（QFIN.OQ）区间累计下跌7.44%，最新收盘价为14.56美元（2月23日），单日下跌 2.54%。下跌主要受中概股整体环境疲软影响，纳斯达克中国金龙指数在此期间波动下行。同期，港股 恒生指数下跌1.82%，美股纳斯达克指数下跌1.13%，信贷板块表现亦较弱。 以上内容基于公开资料整理，不构成投资建议。 ...

Core Viewpoint - Qifu Technology is expected to report a net profit of between 5.88 billion to 6.08 billion yuan for the full year of 2025, reflecting a year-on-year change of -2% to +1%, with a significant loss of approximately 420 million yuan in the fourth quarter due to the discounted disposal of a personal consumption bad asset package valued at 7.429 billion yuan, resulting in a discount rate of only 4.15% [1] Financial Performance - The company is transitioning to a light capital model following the implementation of new lending regulations in 2025, but the high costs associated with this transition have not yet translated into significant financial returns, compounded by fluctuations in the macroeconomic environment, leading to short-term operational pressure [1] Stock Performance - Recently, Qifu Technology's stock price has shown volatility, with an 8.44% rebound from February 5 to 11, 2026, closing at 64.85 HKD, but with low trading volume (average daily turnover of approximately 1.06 million HKD), indicating low investor participation [1] - As of February 13, 2026, the stock closed at 61.20 HKD, down 2.16% for the day, with a five-day fluctuation of 3.73% and a narrowing amplitude of 1.68%, while the US stock performance was weaker, closing at 15.55 USD with a five-day decline of 3.30% and an amplitude of 11.75% [1] - The stock price fluctuations reflect market concerns regarding the company's performance losses, deteriorating asset quality, and increasing industry regulation [1]

Core Viewpoint - Qfin Holdings (QFIN) is upgraded from Hold to Buy, with an expected upside of 61% over the next 12 months despite no growth in revenues or earnings [1] Summary by Category Company Performance - The company is currently not showing growth in revenues or earnings [1] Valuation - The current valuation of Qfin Holdings has dipped, prompting the upgrade recommendation [1]

Economic Overview - The Chinese economy is perceived to be in a precarious position, influenced by ongoing geopolitical tensions and macroeconomic issues such as excessive price wars [1] Investment Strategy - The investment approach focuses on cash flow and fundamentals, emphasizing the importance of intrinsic value over mere price movements [1] - A contrarian strategy is adopted, targeting stocks that are overlooked or deemed risky by institutional investors [1] Analysis Methodology - The analysis process involves thorough due diligence, including scrutiny of macro-events, news, and financial statements to assess intrinsic value [1] - Valuation methods employed include Discounted Cash Flow (DCF), Residual Income Model (RIM), or Dividend Discount Model (DDM) [1] - Active monitoring of investment theses is conducted, with updates provided as financial results are released [1]

Group 1 - The core discussion revolves around the necessity of a unified standard for the practical implementation of AI in finance, as highlighted by industry experts [1][3] - Yang Yehui from Qifu Technology emphasizes that AI serves as a tool in high-barrier industries like finance and healthcare, which are likened to fertile land for AI applications [1] - The FCMBench framework aims to create a standardized evaluation system for financial AI models, addressing the confusion among financial institutions regarding model selection [1] Group 2 - Professor Xu Yanwu from South China University of Technology points out that AI has already made significant contributions in areas such as insurance pricing, asset evaluation, and quantitative trading, although these impacts may not be visible in consumer-facing products [2] - Professor Chen Tao from Fudan University stresses the importance of developing a financial reasoning chain within AI models, moving beyond generic pre-training and fine-tuning to ensure models understand interest rates, regulations, and risks [4]

Core Insights - The Beijing Financial Technology Industry Alliance announced the results of the "Top Five Group Standards" for 2025, recognizing the contributions of Qifu Technology in the standardization of financial large models [1][5] - Qifu Technology's participation in the development of two important group standards, namely "Technical Requirements for Financial Applications of Large Language Models" and "Evaluation Specifications for Financial Applications of Large Language Models," has been acknowledged as a significant achievement [1][3] Group 1: Standardization Efforts - Qifu Technology, as a core participating unit, has leveraged nine years of experience in financial technology to provide essential support across dimensions such as technology implementation, risk control, and business adaptation [3] - The standards were led by Industrial and Commercial Bank of China and involved collaboration with major industry players like China Mobile, Huawei, Tencent, and Alibaba, addressing the lack of unified norms in the application of large models in the financial sector [3][4] - The standards define core requirements including application framework, task capabilities, and security trustworthiness, establishing a comprehensive evaluation system for financial institutions' model construction, assessment, and risk management [3][4] Group 2: Company Initiatives - Qifu Technology is one of the early entrants in the financial large model sector, consistently advancing both "technology research" and "standard development" in tandem [4] - In 2023, the company formed a specialized large model team and collaborated with the China Academy of Information and Communications Technology to compile the first financial industry large model standard [4] - The company aims to launch a super intelligent agent in 2025 that enhances core lending operations by integrating modules for credit decision-making, credit assessment, and compliance assistance, thereby providing a practical example of standardized technology implementation [4][5] Group 3: Future Directions - The recognition as one of the "Top Five Group Standards" is seen as a positive affirmation of Qifu Technology's efforts in promoting industry standardization [5] - The company plans to continue collaborating with academic and research partners to deepen technological research and practical transformation, actively participating in the construction of industry standard ecosystems [5]

Core Insights - Qifu Technology, in collaboration with Fudan University and South China University of Technology, has launched the first multimodal evaluation benchmark for credit scenarios, named FCMBench-V1.0, aimed at enhancing AI applications in credit assessment [1][2] - The benchmark is designed to address real credit business scenarios, focusing on multi-modal evaluation tasks that reflect practical business needs, thereby promoting academic research and application in credit AI [1] - Unlike traditional evaluations that focus on single recognition or understanding capabilities, this benchmark assesses model capabilities relevant to key processes in micro-enterprise credit granting, such as multi-document recognition and risk clue discovery [1] Summary by Sections - **Benchmark Development**: The FCMBench-V1.0 provides a standardized evaluation platform to foster collaboration between academia and industry, enabling fair comparisons of AI model capabilities in the credit field [1] - **Data and Framework**: The benchmark includes a highly consistent evaluation framework with 18 core credit document types, comprising 4,043 compliant images and 8,446 test samples, covering the entire credit review process [2] - **Industry Impact**: This initiative aims to break down data and knowledge barriers within the industry, facilitating a shift from "single-point optimization" to "collaborative innovation" between academia and financial technology companies [1]

Group 1 - The core viewpoint of the news is the recognition of Qifu Technology as one of the top 100 private service enterprises in the Yangtze River Delta for 2025, highlighting its contributions to the artificial intelligence sector and the real economy [1] Group 2 - Qifu Technology has significantly enhanced risk identification accuracy, operational efficiency, and user experience by integrating AI capabilities into the financial service chain, effectively connecting financial institutions with small and micro market entities and individual consumers [3] - As of the end of the third quarter this year, Qifu Technology has established partnerships with 167 financial institutions, providing stable and efficient digital credit support to over 62 million credit users, thereby supporting the operational development of small and micro enterprises and meeting individual consumption needs [3] - Looking ahead, Qifu Technology aims to deepen technological innovation and cultivate new productive forces centered around AI, with a commitment to improving development quality and creating new advantages for future growth [3]

Core Insights - The 2025 Black and Gray Industry Detection Skills Competition concluded successfully, showcasing the practical capabilities in cybersecurity, with over 200 top teams participating nationwide [1] - Qifu Technology won the "Team Gold Award" in the Thunder Group of the Black and Gray Industry Technology Countermeasure Track, highlighting its strong capabilities in financial fraud prevention technology [1] - Qifu Technology's expert, Wu Yechao, received the "Outstanding Coach Award," further emphasizing the company's expertise in the field [1] Company Achievements - Qifu Technology has established a comprehensive defense system centered around the "Shanhai" anti-fraud system, integrating "domain name resolution + content features + AI risk analysis" for multi-dimensional assessment [1] - The company's model processes an average of 600,000 high-risk clues daily, has issued over 1.22 million warnings for malicious websites, and has blocked over 7,400 counterfeit websites/apps, preventing fraudulent transactions worth 287 million yuan [1][2] - The model achieves over 95% accuracy in identifying fraudulent websites, addressing industry challenges such as "zero-sample" fraud detection and incomplete risk tracing [1] Future Directions - Qifu Technology aims to deepen the application of AI large models in fraud prevention, sharing technical experiences and promoting the establishment of industry standards for fraud prevention technology [3] - The company is committed to enhancing risk control levels across the industry and contributing to the fight against financial black and gray industries, thereby maintaining social security and stability [3]

Core Viewpoint - The event highlighted the importance of corporate social responsibility (CSR) in sustainable development and recognized companies that excel in this area [1] Group 1: Event Overview - The "Technology Empowerment · Capital Breakthrough" sharing session was held online by Gelonghui [1] - The annual list of outstanding companies was announced during the event [1] Group 2: Award Recognition - Qifu Technology-S (3660.HK) received the "Annual Social Responsibility Award" in the Gelonghui "Golden Award" annual selection [1] - The award acknowledges the company's long-term commitment to fulfilling social responsibilities and recognizes its management quality and personnel competence [1] - A strong sense of social responsibility is deemed essential for a company's sustainable development and competitiveness [1]