一名来自北京的资深招投标专家，在看到"2024年以来已将3.8万名违法专家清理出库，各地专家库中已 查实的违法专家全部'清零'"的新闻后，连连感叹"太正常了"。 他说："评标专家的基本义务是严格按照文件要求公正开展评审。但在实践中，评标专家有太多操作空 间。首先，一个地区专家库的总人数有限，细分到各个行业子专业后，一个地区可能只有20多名相关专 家，再排除因工作繁忙无法参与评标的人员，能够频繁参与评标的专家数量就更有限了。这不到20人的 专家群体，每天评审的都是类似项目，彼此之间会比较熟悉；再加上打分制度中的'软分'（即主观分） 的影响，评审专家的话语权不断上升，这类群体出现问题也就成了正常现象。" 一位来自浙江招投标专家库的专家说，一些专家还会通过"暗语"通知评标时间和地点，比如在朋友圈或 群里发"明天要去某某地方钓鱼"，"话里有话，乙方企业或中间人一看就懂"。 上述北京资深专家认为，评标专家领域的腐败并非个例。要解决这一问题，关键在于采购人招标的环节 ——采购人需要对此做深入研究。但当前招标人既存在投入不足，专业能力欠缺的问题，又缺乏制约评 审专家的有效手段，因此出现问题是必然结果，区别只在于影响范围的大 ...

Core Insights - The reform of the bidding market is crucial for the fairness and vitality of the market economy and directly impacts the construction of a unified national market [2][3] - Recent reforms have led to significant progress, but deep-rooted issues remain to be addressed, necessitating institutional innovation and the use of digital technology to create a transparent bidding market [3][4] Institutional Innovation - Focus on optimizing bidding rules through the implementation of new standards for expert management, revised procurement guidelines for state-owned enterprises, and establishing fair competition benchmarks [4] - The goal is to enhance the entire lifecycle management of bidding processes and ensure that procurement decisions are based on comprehensive cost-effectiveness [4] Digital Empowerment - Emphasizing the use of digital technology to improve market transparency and efficiency, transitioning from a single "institutional constraint" to a multi-faceted "technological governance" model [4] - New technologies are expected to reduce corruption opportunities arising from information asymmetry and reshape market transaction mechanisms [4] Regulatory Strengthening - Historically, regulatory lag has contributed to persistent issues in the bidding market, with inadequate penalties for violations [5] - The establishment of a long-term governance mechanism is essential to ensure orderly development in the bidding market [6] Market Participation - The positive effects of recent reforms are becoming evident, with a notable increase in private enterprise participation in bidding processes [6] - In the first seven months of this year, over 366,000 private enterprises won bids in the engineering construction sector, marking an 11.9% year-on-year increase, with private projects accounting for 76% of total bids [6]

Core Insights - The bidding big data analysis platform integrates multidimensional data resources and intelligent algorithms to provide precise decision support and risk prevention capabilities throughout the project lifecycle [1] Group 1: Pre-project Phase - The platform captures government public bidding data, industry dynamics, and historical bidding records to construct a market opportunity map [3] - Machine learning analyzes bidding frequency and project scale in specific regions and industries to identify high-value projects, generating matching evaluation reports based on enterprise qualifications and performance [3] - For multinational projects, the platform connects to international political and economic databases to monitor risk indicators such as policy stability and exchange rate fluctuations [3] Group 2: Bidding Strategy Development - The platform deep dives into historical winning data to create competitor profiles and pricing models [4] - It analyzes specific enterprises' bidding patterns to predict their potential bidding ranges and uses Monte Carlo simulation to generate optimal bidding strategies [4] - Natural language processing technology is utilized to parse technical parameters in bidding documents, automatically comparing them with enterprise technical solutions to identify advantages and risks [4] Group 3: Risk Prevention - The platform employs blockchain technology for immutable transaction data and full-process traceability, enabling real-time monitoring of abnormal behaviors [4] - It identifies suspicious collusion by comparing features such as inquiry contact numbers and document creation machine codes [4] - A policy compliance knowledge base is established to automatically review bidding documents for discriminatory qualifications or unreasonable technical barriers [4] Group 4: Project Execution Phase - The platform integrates contract performance data, supply chain information, and financial indicators to build a dynamic monitoring system [4] - It tracks the flow of funds, project progress, and subcontractor qualifications to provide early warnings for delays and quality defects [4] - For international projects, it links to cross-border tax databases to automatically calculate tax burdens and generate compliance reports [4] Group 5: Regulatory Innovation - The platform innovates bidding supervision models by integrating transaction data, enterprise credit information, and expert review records to create intelligent early warning models [5] - It identifies risk entities by analyzing indicators such as bidding enterprise activity and abnormal winning rates [5] - The platform's visual regulatory reports provide insights into market competition and industry concentration for policy formulation [5] Group 6: Industry Optimization - The platform enhances industry ecosystem optimization by connecting financial institutions and supply chain companies through open data interfaces [5] - It has helped small and medium-sized enterprises secure over 100 million yuan in loans, alleviating financial pressure [5] - The accumulated historical data can be used to compile industry cost indices and analyze market supply and demand trends for long-term strategic planning [5] Group 7: Data Utilization - The essence of the bidding big data analysis platform is transforming data resources into decision-making productivity [6] - Companies need to focus on accumulating and governing data assets, establishing standardized data collection, cleaning, and analysis processes [6] - With the deep integration of technologies like artificial intelligence and blockchain, the platform aims to transition from auxiliary decision-making to autonomous decision-making, promoting the bidding industry towards intelligence and transparency [6]

本次发布的典型案例具有以下四个方面的特点：一是坚持全领域覆盖，实现全链条打击；二是严格适用 法律，依法精准定性；三是落实宽严相济，确保罪责刑相适应；四是用好司法建议，深化协同治理。 下一步，最高人民法院、国家发展改革委将持续深化与纪检监察、公安、检察、行政监督等部门的协作 配合，依法从严惩处招投标违法犯罪活动，不断深化招投标改革创新，营造公平竞争的招投标市场环 境，为建设全国统一大市场、推动经济社会高质量发展提供有力支撑。 1.被告人张某串通投标案 招标投标市场是全国统一大市场的重要组成部分，对提高资源配置效率效益、推动高质量发展具有重要 作用。当前，串通投标犯罪案件呈现出犯罪主体多元化、犯罪手段隐蔽化、犯罪链条组织化的新特点和 新动向，扰乱了招投标市场秩序，损害了经营主体合法权益。为充分发挥典型案例的警示教育作用，最 高人民法院、国家发展改革委联合发布6件人民法院审结的串通投标及其关联犯罪典型案例。 ——依法惩治损害民营企业合法权益的串通投标行为 基本案情 2022年6月，青岛某公司通过招标系统发布招标需求，被告人张某作为该公司员工,负责主导资源方招 标。为使投标人武某(另案处理)竞得该项目，张某指使其他评 ...