Investment Rating - The report suggests a positive investment outlook for the AI and financial services sector, highlighting the potential for significant advancements and cost reductions due to the release of DeepSeek R1 in 2025, which is expected to be a turning point for localized AI deployment in financial institutions [7]. Core Insights - AI applications are rapidly penetrating core business areas and back-office functions of various financial institutions, enhancing both internal efficiency and external value [1][7]. - The report identifies that most financial institutions are currently in the exploration and accumulation phase of AI application, with deep application being an inevitable trend [14]. - AI is expected to transform financial business processes and organizational structures, ushering in a new era of digital intelligence in finance [7]. Summary by Sections Investment Recommendations - The report recommends focusing on several sectors within the financial industry, including: 1. Financial information services with key stocks like Tonghuashun, Jiufang Zhitu Holdings, and Guiding Compass [8]. 2. Third-party payment services, recommending stocks such as Newland and Newguodu, with related stocks like Lakala [9]. 3. Banking IT, with recommended stocks including Yuxin Technology, Jingbeifang, and Guodian Yuntong [9]. 4. Securities IT, recommending stocks like Hengsheng Electronics and Jinzhen Shares [10]. 5. Insurance IT, with recommended stocks including Xinzhi Software and Zhongke Software [11]. Application Stages - Financial institutions' AI applications are categorized into three stages: 1. Initial exploration of large model applications. 2. Development of certain model application capabilities with data accumulation. 3. Achieving deep application of large models [14]. Application Value - AI applications provide value through: 1. Internal cost reduction and efficiency improvement, optimizing operational management and core business processes [21]. 2. External value extraction, enhancing marketing and customer service to improve sales conversion and customer value [21]. Application Pathways - Different types of financial institutions exhibit varied pathways for AI application deployment: 1. Large institutions leverage strong self-research capabilities for deep AI application penetration. 2. Smaller institutions focus on cost-effective solutions, utilizing lightweight models and integrated systems for agile development [26]. AI Empowerment in Banking - AI is enhancing front-office quality and efficiency, optimizing back-office processes across various banking functions [43]. - In credit risk management, AI models can analyze financial data to identify potential risks and improve decision-making processes [47]. AI Empowerment in Securities - The number of securities firms exploring large models is rapidly increasing, with applications extending across various business functions, including investment advisory and research [58][59].

Core Viewpoint - Postal Savings Bank has demonstrated resilience in a challenging banking environment, achieving significant growth in assets, revenue, and profit while maintaining a strong net interest margin of 1.87% in 2024 [2][3] Financial Performance - The bank's total assets exceeded 17 trillion yuan, reaching 17.08 trillion yuan, an increase of 8.64% from the previous year [3] - Revenue grew by 1.83% year-on-year, totaling 945.92 billion yuan, while net profit increased by 3.27% [2] - Net interest income reached 286.12 billion yuan, up 1.53% year-on-year, and non-interest income rose to 626.52 billion yuan, a growth of 3.21% [5] Strategic Focus - The bank emphasizes "long-termism" and does not pursue blind expansion, instead opting for refined management to balance scale and efficiency [2][3] - A dual strategy of stabilizing net interest income and enhancing non-interest income has been pivotal for growth [3] Customer-Centric Innovations - The bank has accelerated service model innovations in inclusive finance, with agricultural loans and microloans both growing over 12% [4] - In technology finance, the bank served over 90,000 tech enterprises, with financing balances exceeding 500 billion yuan, marking a growth of over 40% [4] Risk Management - The non-performing loan ratio remained below 1%, with a provision coverage ratio of 286.15%, indicating strong risk control measures [5] Organizational Reforms - The bank is undergoing comprehensive reforms in organizational structure, incentive mechanisms, and digital transformation to enhance internal motivation and operational efficiency [10][11] - Cost-to-income ratio decreased by 0.59 percentage points, reflecting the effectiveness of internal reforms [12] Future Outlook - Postal Savings Bank aims to integrate into national development plans and expand financial support for new productive forces, targeting high-quality growth in the coming years [13]

Core Viewpoint - Postal Savings Bank of China (PSBC) demonstrated strong resilience in its development amidst a general narrowing of net interest margins in the industry, achieving growth in both revenue and profit for the year 2024 [1][2]. Financial Performance - In 2024, PSBC reported total operating revenue of 348.775 billion yuan, a year-on-year increase of 1.83%, ranking among the top state-owned banks [2][6]. - The bank's total assets exceeded 17 trillion yuan, reaching 17.08 trillion yuan, with a year-on-year growth of 8.64% [5][6]. - Net interest margin stood at 1.87%, leading among state-owned banks, and was 31 basis points higher than the average of commercial banks [7][8]. Asset and Liability Management - PSBC's total liabilities reached 16.05 trillion yuan, growing by 8.69% year-on-year [5]. - The bank achieved a net interest income of 286.123 billion yuan, reflecting a 1.53% increase despite industry pressures [7]. Loan and Deposit Growth - Customer loans increased by 9.38% year-on-year, surpassing the industry average, with personal loans growing by 6.74% [8]. - Customer deposits rose by 9.54%, with personal deposits accounting for 89.15% of the total [8]. Non-Interest Income - Non-interest income contributed 3.21% to total revenue, with significant growth in the corporate segment's intermediary income, which surged by 43% [9]. - The bank's assets under management (AUM) reached 16.69 trillion yuan, a 9.6% increase from the previous year [9]. Strategic Focus Areas - PSBC aims to deepen its focus on rural finance, inclusive finance, and personal finance, positioning itself as a leader in these areas [3][12]. - The bank has established a wealth management department to enhance its wealth management business [10]. Technological Advancements - PSBC invested 12.296 billion yuan in information technology, accounting for 3.53% of its revenue, to support its digital transformation [18]. - The bank has developed its own AI model, "Youzhi," which enhances operational efficiency and customer service [19][20]. Risk Management - The bank maintained a low non-performing loan ratio of 0.90% and a provision coverage ratio of 286.15%, indicating strong asset quality [22].

Core Viewpoint - The article discusses the advancements in the deployment of the DeepSeek open-source large model by major banks in China, highlighting its role in enhancing financial services through intelligent upgrades and operational efficiencies [2][6][10]. Group 1: Deployment and Adoption - As of March 8, Industrial and Commercial Bank of China (ICBC) has completed the private deployment of the latest DeepSeek model, integrating it into its "ICBC Intelligent Surge" model matrix to enhance financial business scenarios [2][6]. - Over 20 banks have adopted the DeepSeek model, with major state-owned banks like Postal Savings Bank and China Construction Bank also initiating their deployments [3][8]. Group 2: Focus Areas of Application - Banks are focusing on four main areas for the application of DeepSeek: intelligent customer service upgrades, business process optimization, intelligent decision-making and risk management, and intelligent marketing and customer insights [4][12]. - DeepSeek is expected to replace repetitive tasks and enhance cognitive capabilities, driving business process optimization and innovation [4][16]. Group 3: Specific Implementations - ICBC has empowered over 20 major business areas with the DeepSeek model, implementing more than 200 practical scenarios, including a smart dialogue trading product and a remote banking assistant that improves service efficiency by reducing call durations by approximately 10% [6][12]. - Postal Savings Bank has integrated DeepSeek models to enhance its "Little Postal Assistant," improving service efficiency and customer experience through advanced logical reasoning capabilities [9][13]. Group 4: Future Implications - The integration of DeepSeek into banking services signifies a shift from "informationization" to "cognition" in financial services, indicating a transformative phase in how banks interact with customers and manage operations [16][17]. - The technology is expected to reshape the banking industry's approach to AI applications, focusing on personalized customer interactions and efficient resource allocation [17][19].