河北加快数字纪检监察体系建设 "农村集体'三资'管理领域问题点多面广，这一案件的精准查办得益于农村集体'三资'管理监督模型的搭 建。"晋州市纪委监委有关负责同志说，通过对全市农村产权交易平台相关数据的碰撞比对、分析研 判，目前已经发现农村集体土地流转、集体资产租赁、村集体工程建设项目等预警信息2736条，有效拓 展问题线索来源渠道，提升基层监督能力。 逐步完善数字赋能监督的实践路径，把权力关进"数据铁笼"，省纪委监委坚持改进基层小微权力"监督 一点通"平台建设应用，畅通基层监督渠道，实时公开村（社区）小微权力运行情况，优化群众诉求办 理程序。目前，该平台已实现县级地区全覆盖，有效助力行业部门强化事前服务，快速响应、精准施 策，促使小微权力行使更加规范。 深化治理，放大信息化监督效应 触发一个预警，发现一类问题，健全一批制度，治理一片领域。省纪委监委不断强化监督监管贯通发 力，推动省农业农村厅牵头健全省级"三资"管理平台服务功能，将农村集体资产、资源、合同数据全面 纳入平台监管，督促完善农村集体"三资"监管制度体系。在省纪委监委监督推动下，省农业农村厅制发 以信息化助力一体推进"三不腐" 中央纪委国家监委网站 ...

强化数据集成，促进从"单一作战"向贯通协同跃升 中央纪委国家监委网站 石毅鹏 曹欢欢 湖北省十堰市纪委监委不断强化数字技术与纪检监察工作深度融合，有效提升监督质效。图为近日，该 市纪委监委工作人员运用大数据监督模型对模拟案例进行分析、推演。李芳 摄 习近平总书记强调，"运用大数据提升国家治理现代化水平""使大数据在各项工作中发挥更大作用"，要 求"用科技手段加强监督"，为在纵深推进全面从严治党和反腐败斗争中持续用好大数据等信息化技术指 明了前进方向。 12月8日，湖北省纪委监委举办2025年度数字化监督办案评比评选活动，通过数字化精品案例集中展示 和监督建模新技术应用现场评比，全面展示全省各地开展数字化监督办案的实践成果，引导纪检监察干 部适应数字化、智能化发展趋势，会用、善用大数据监督。 二十届中央纪委四次全会提出，以大数据信息化赋能正风反腐。湖北省纪委监委深入贯彻落实相关部署 要求，把强化科技支撑作为推动纪检监察工作高质量发展的重要抓手，持续深化数字纪检监察体系建 设，推动构建以大数据资源中心为支撑、以职能部门行业监管为前端、以纪检监察专责监督为后墙、监 督整改治理贯通发力的公权力大数据监督格局。市、县纪 ...

今年10月，中央纪委国家监委驻中国石油纪检监察组对4家下属企业开展纠治"四风"监督检查。通过数 智模型筛查发现，某单位存在"同一部门同一人员高频报销""住宿地点与实际不符"等异常情况。最终查 实该单位有关负责人套取资金用于违规接待等问题。目前，相关涉案人员已受到党纪处分，并收缴违纪 款1.1万余元。 中央纪委国家监委网站 陆丽环 转自：中央纪委国家监委网站 充分发挥大数据发现挖掘、分析预警问题线索的作用，实现趋势走向精准研判、规律特点及时把握。 中央纪委国家监委驻中国电信纪检监察组建成监督贯通协同数字化平台，实现与其他领域业务监管系统 的对接。如，推动财务部门持续迭代虚假贸易风险识别模型，实现对客情掌握、谈判应标自主、采购自 主等6个方面15个风险点的实时监督，有效预防虚假业务，严格规范列支。 各派驻中管企业纪检监察组围绕办案应用场景，聚焦数据整理难、关联信息排查难、搜索查询难、快速 锁定突破点难等难题，探索开发常见问题分析等模型，通过对多重数据的关联分析，为查清查透职务犯 罪安上科技"透视镜"。 驻中国电信纪检监察组自研数据治理引擎，节省数据整理时间的同时，关联包括主要社会关系和"经济 往来"等在内的多维数 ...

Core Insights - The article discusses the application of big data technology in combating corruption and enhancing the efficiency of disciplinary inspection and supervision in Wuzhou, Guangxi [2][3]. Group 1: Implementation of Big Data in Anti-Corruption - Wuzhou's disciplinary inspection and supervision commission has utilized big data analysis to identify irregularities in vehicle inspection agencies, revealing potential collusion between public officials and these agencies [2]. - The commission has established a big data supervision working group to enhance data modeling and analysis, ensuring a precise connection between technology and supervision [3][4]. - The use of big data has led to the identification of key evidence in cases involving high-ranking officials, such as the former chairman of a county investment company, facilitating the investigation process [3][5]. Group 2: Case Studies and Outcomes - In the investigation of a former deputy director of the emergency management bureau, big data analysis helped uncover hidden bribery practices, leading to the official's expulsion from the party and legal consequences [5]. - The commission has shifted from single data analysis to comprehensive data analysis for case handling, demonstrating a proactive approach in utilizing data for broader investigations [4][5]. - Continuous training and capacity building for disciplinary inspection personnel in digital literacy are emphasized to enhance their practical application of big data in investigations [5].

Group 1 - The core focus is on addressing issues related to rural public welfare positions, including false claims for subsidies, illegal part-time jobs, and vacant positions, through the use of a big data supervision platform [1] - Jinan's disciplinary inspection and supervision authority has established a digital disciplinary inspection system framework, emphasizing the integration of data resources and business applications to enhance oversight and investigation capabilities [1][2] - The authority has implemented 69 digital supervision analysis models across 16 key areas, including land acquisition and administrative law enforcement, to identify and address issues effectively [2] Group 2 - The Jinan disciplinary inspection agency has developed big data supervision models targeting public welfare sectors such as rural revitalization, education, and healthcare, successfully identifying and addressing violations that harm public interests [2] - In the Licheng District, cross-verification of village committee personnel information with financial data has led to the discovery of 30 cases of improper subsidy distribution, resulting in disciplinary actions against 34 individuals and the recovery of over 6.3 million yuan [3] - The Jinan disciplinary inspection authority is enhancing its investigative capabilities against new and hidden corruption through advanced data analysis techniques, focusing on areas such as stocks, real estate, and loans [4]

Core Viewpoint - The article emphasizes the importance of integrating digital technology into the disciplinary inspection and supervision system to enhance efficiency and effectiveness in combating corruption and ensuring accountability [6][18]. Group 1: Digital Integration in Supervision - Various local governments, including those in Shandong, Chongqing, and Jiangsu, are advancing the construction of digital disciplinary inspection systems, focusing on cultivating digital thinking and literacy among inspectors [19]. - The integration of digital technology into disciplinary inspection processes is seen as a crucial method for improving the quality of supervision and law enforcement [7][9]. - Establishing a comprehensive data resource center and a digital supervision application platform is essential for optimizing data collection, sharing, and analysis [9][10]. Group 2: Data Utilization and Analysis - The development of customized data models and analytical tools is being prioritized to enhance the precision and effectiveness of supervision [8][12]. - A closed-loop governance chain is being established to address issues identified through data analysis, ensuring timely feedback and corrective actions [11][13]. - The use of big data for real-time monitoring and early warning systems is being implemented to detect irregularities in various sectors, such as education and healthcare [12][18]. Group 3: Training and Capacity Building - There is a strong emphasis on enhancing the digital skills and awareness of disciplinary inspection personnel through targeted training programs [15][16]. - The establishment of a talent pool for digital supervision is aimed at fostering a collaborative environment between technical and operational teams [15][19]. - Practical training and real-case simulations are being utilized to improve the operational capabilities of inspectors in data analysis and electronic evidence collection [16][18].

Core Insights - The article highlights the effective use of a smart supervision system developed by the Changde City Discipline Inspection Commission and the traffic police to quickly identify and address violations by public officials, particularly focusing on drunk driving cases [1][2]. Group 1: Smart Supervision System - The "Smart Supervision" mini-program is integrated into the city's big data platform, enabling a full-cycle management process of "comparison—warning—notification" for identifying violations among public officials [1][2]. - The system has led to the discovery of 131 problem clues this year, showcasing its effectiveness in enhancing the quality and efficiency of supervision and law enforcement [1]. Group 2: Data-Driven Analysis - The platform's core advantage lies in its ability to integrate and analyze vast amounts of cross-departmental data, allowing for the identification of issues that traditional methods may overlook [2]. - The "data-driven + intelligent analysis" model has improved case handling efficiency, as demonstrated in a specific case where the investigation took only three weeks from initiation to legal measures against involved personnel [2]. Group 3: Proactive Risk Management - The collaboration with housing departments has led to the development of an intelligent supervision module for public rental housing, which monitors and alerts on various data anomalies in real-time [3][4]. - Since its launch in June, the module has generated nearly 200 warning messages, prompting relevant departments to conduct thorough self-examinations [4].

Core Viewpoint - The article emphasizes the importance of strict supervision and governance in higher education institutions in Jiangsu Province, highlighting the need for comprehensive measures to combat corruption and ensure the integrity of educational practices [3][4][5]. Group 1: Supervision and Governance - Jiangsu Province's disciplinary inspection and supervision bodies are focusing on key areas such as discipline construction, enrollment exams, research funding, and logistics management to enhance daily supervision [3]. - The provincial disciplinary committee has organized a warning education meeting for over 500 participants from various universities to analyze cases of misconduct among university leaders, aiming to set clear boundaries for party members [3][4]. - The article outlines the establishment of collaborative mechanisms among various universities to enhance political supervision and promote high-quality development in higher education [7][8]. Group 2: Political Supervision - The article discusses the necessity of political supervision to ensure the implementation of major decisions made by the central government within universities, addressing issues such as leadership accountability and ideological guidance [6][9]. - It highlights the importance of aligning educational practices with the fundamental task of fostering moral integrity among students, ensuring that educational institutions contribute positively to society [7][8]. Group 3: Anti-Corruption Measures - The article reports on the ongoing efforts to combat corruption within higher education, including the investigation of several university leaders for serious violations of discipline and law [14][15]. - It emphasizes the need for a high-quality approach to case handling, focusing on improving the quality of investigations and addressing systemic issues that contribute to corruption [14][15]. - The article mentions the establishment of a digital supervision platform to enhance the efficiency of anti-corruption efforts through data analysis and monitoring [9][10]. Group 4: Capacity Building - The article outlines initiatives to improve the capabilities of disciplinary inspection personnel through targeted training and practical experience sharing [12][13]. - It stresses the importance of integrating young talent into the disciplinary inspection system to strengthen the overall effectiveness of governance in higher education [11][12].

Group 1 - The meeting emphasized the importance of political supervision in supporting technological innovation, focusing on the implementation of innovation-driven development strategies and the integration of technological and industrial innovation [1][2] - The provincial disciplinary inspection and supervision agencies are required to deepen the use of big data and information technology to enhance anti-corruption efforts, particularly in identifying misconduct and corruption issues [2] - There is a push for the construction of an integrated disciplinary inspection and supervision platform to streamline communication and information sharing among various departments, improving the overall efficiency of corruption governance [2] Group 2 - The meeting highlighted the need for coordination and collaboration between disciplinary inspection agencies and relevant functional departments, aiming to establish a data-sharing mechanism to support high-quality data resource provision for anti-corruption work [2] - The focus is on ensuring that the important discussions and decisions regarding technological innovation by the central government are effectively implemented in Shaanxi province [2] - The meeting was led by the provincial party committee secretary, indicating the high-level commitment to advancing technology and innovation within the region [1]

Group 1 - The core viewpoint emphasizes the integration of big data and information technology to enhance anti-corruption efforts and improve the quality of disciplinary inspection and supervision in Linyi City, Shandong Province [1][2][3] Group 2 - The construction of a digital disciplinary inspection and supervision system is supported by a data center that integrates 329 data sources, collecting 350 million data entries from various public resources and internal business data [1][2] - The platform development focuses on enhancing political, special, daily, and grassroots supervision, with tools like a political ecology monitoring platform and a big data supervision warning platform [2][3] Group 3 - The emphasis on intelligent supervision aims to counter increasingly covert corruption methods by utilizing a "cloud workstation" big data case handling platform and developing 90 analytical methods for supervision and investigation [3][4] - Professional development is prioritized, with training sessions and workshops aimed at improving the ability of disciplinary inspection personnel to effectively use big data in their work [3][4]