农村金融数字化转型
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两会丨杨伟坤:完善多层次、差异化、分工协作的农村金融体系
券商中国· 2026-03-09 00:38
Core Viewpoint - Rural finance is essential for supporting the "three rural issues" (agriculture, rural areas, and farmers) and is a crucial element in promoting comprehensive rural revitalization during the 14th Five-Year Plan period [1]. Group 1: Transformation of Rural Finance - Rural finance is transitioning from a single funding provider to a composite support system that includes capital allocation, industrial empowerment, and livelihood security, becoming a key financial force in rural revitalization and agricultural modernization [3]. - The core functions of rural finance are categorized into three dimensions: 1. It acts as a "lifeblood" for capital investment in agriculture, supporting long-term investments in critical areas such as high-standard farmland and modern irrigation [4]. 2. It serves as an "empowerment hub" by injecting innovative energy into rural industries through new service models like supply chain finance and digital inclusive finance [4]. 3. It strengthens the foundation of rural livelihood security by enhancing financial service coverage and developing multi-layered insurance and risk-sharing mechanisms [4]. Group 2: Enhancing Rural Financial Services - To improve rural financial services for the "three rural issues," it is suggested to strengthen fiscal-financial collaboration, enhance a multi-layered rural financial system, and reinforce financial supply in key areas [5]. - The fiscal-financial collaboration should involve a model of "fiscal subsidies + risk compensation + credit support" to effectively share credit risks and expand agricultural credit guarantee coverage [6]. - A multi-layered, differentiated, and collaborative rural financial system is necessary, where various financial institutions clarify their roles and cooperate to provide sustainable financial services [6]. - Financial institutions should focus on supporting the development of new agricultural productivity and innovate project support methods, enhancing credit support and utilizing digital technology to improve service efficiency [6]. Group 3: Digital and Green Transformation - Rural finance must keep pace with digital and green transformation trends, necessitating the development of a high-quality, composite financial talent pool [7]. - Digital transformation in rural finance is crucial for improving service quality and accessibility, with recommendations to establish digital credit archives and agricultural big data platforms for risk assessment [7]. - Green development should be promoted through the creation of green financial products, supporting ecological agriculture and sustainable agricultural practices [7]. Group 4: Talent Development - The development of composite financial talents who understand finance, agriculture, and technology is essential for the future of rural finance [8]. - Financial institutions should enhance training programs and attract professionals with expertise in finance and agricultural technology to strengthen their workforce [8].
以AI安全技术助力农村金融数字化转型——绿盟科技农信机构AI安全实践
Xin Lang Cai Jing· 2025-12-26 12:21
Core Insights - The digital transformation wave is significantly impacting the rural financial sector, with rural credit institutions playing a crucial role in bridging the "last mile" of financial services for rural revitalization [1][12] - The reform process of the rural credit system in China has accelerated, presenting dual pressures of risk prevention and compliance construction for rural credit institutions [1][12] Group 1: Security Challenges in Rural Financial Digital Transformation - The risk landscape is increasingly complex, with evolving attack methods and new threats such as supply chain attacks and data theft, making traditional defense mechanisms inadequate [3][13] - Regulatory compliance requirements have intensified, necessitating rural credit institutions to meet various laws and standards, including the Cybersecurity Law and Data Security Law, to build a security operation system that supports compliance reporting and risk control [2][13] - Operational capabilities are limited, with rural financial institutions struggling to respond quickly to security incidents due to insufficient manpower and expertise at county and township levels [3][13] Group 2: AI-Driven Security Operations Innovation - Green Alliance Technology has developed the "Fengyunwei" AI security capability platform, which integrates a technical foundation, capability framework, and application functions to transform security operations from passive defense to proactive prediction [4][14] - The platform's architecture supports centralized management and distributed operations, featuring a dual-engine of computing power and knowledge for effective security management [5][15] - The capability framework standardizes reusable modules to enhance security task performance and support diverse security needs in inclusive finance [6][16] - The application function layer includes eight core modules tailored to the security operation needs of rural credit institutions, enabling automated and assisted operations [7][17] Group 3: Implementation Path for Security Capability Upgrade - Green Alliance Technology employs a phased construction strategy—foundation building, deepening protection, and comprehensive assurance—to ensure effective and sustainable technology implementation [8][18] Group 4: Value of Technology Implementation in Rural Credit - The AI security solution has significantly improved operational efficiency, with the platform capable of automatically identifying high-value alerts and achieving a noise reduction rate of over 95% [9][19] - Compliance capabilities have been enhanced, with the platform effectively supporting regulatory data reporting and improving the quality of data submissions [9][19] Group 5: Future of Security Protection in Rural Finance - As digital finance in rural areas enters a phase of deep integration, security demands will evolve towards more intelligent and precise solutions [10][20] - Green Alliance Technology aims to continue focusing on the integration of technology and scenarios, enhancing AI applications to ensure the security of financial operations [11][21]