广西梧州深化探索信息化技术实践应用 让数据说话 为反腐赋能 前不久，广西壮族自治区梧州市纪委监委工作人员到部分机动车检测机构监督检查时发现，个别机构存 在使用第三方收款二维码额外收取年检费用的现象。 "这其中可能存在公职人员与机动车检测机构利益勾连，违规审核通过问题车辆年检的问题。"工作人员 介绍。由于涉及面广，核查数据多且无明确指向性，运用常规手段进行数据比对、线下核实取证难度 大。该市纪委监委随即利用大数据分析模型，按照年检审核通过率、重复上线检测车辆、审核人员等规 则进行碰撞分析，针对相关问题展开核查。 经查，该市公安局交警支队车管所的大型机动车年检审核数据存在异常情况，该市纪委监委工作人员将 其作为预警信息按程序转为问题线索进行处置。办案部门在梳理涉案人员资金流向过程中，运用大数据 分析平台开展综合分析，迅速锁定关键证据。目前，已立案5件，留置2人，为该市城镇机动车辆检验检 测突出问题整治工作打开了突破口。 以大数据信息化赋能正风反腐是推动纪检监察工作高质量发展的重要举措。梧州市纪委监委持续探索数 字技术实践应用，聚焦重点领域和关键环节开展数据建模，运用多维度数据碰撞比对，精准识别不正之 风和腐败问题 ...

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]