时报经济眼丨“数据孤岛”串联成链，支撑小微信贷精准直达

Core Viewpoint - The article highlights the significant role of data sharing and financial support mechanisms in facilitating loans for small and micro enterprises, which traditionally faced challenges due to lack of collateral and guarantees [1][3][5]. Group 1: Data Sharing and Financial Mechanisms - The support mechanism for small and micro enterprises has broken down data sharing barriers, allowing financial institutions to better assess the creditworthiness of these businesses, thus reducing financing costs and risks [1][5]. - The "joint consultation mechanism" in Shandong aims to provide tailored financial solutions for enterprises that do not meet lending criteria, involving various departments to address specific financing challenges [4][9]. - The Chongqing financial regulatory bureau has developed a "data sharing + business collaboration" model, which has successfully mapped out the funding landscape for 370,000 market entities, enhancing the precision of financial services [6][9]. Group 2: Individual Case Studies - The experience of Sanyang Import and Export Trade Co., which faced significant cash flow pressures due to delayed payments from overseas clients, illustrates the common struggles of small enterprises in securing financing without collateral [3][4]. - The case of Haosen Motorcycle demonstrates how the introduction of digital tools and data analysis has helped identify financing needs that were previously overlooked, leading to successful loan approvals for businesses that had never borrowed before [8][9]. Group 3: Impact of Digital Technology - The integration of digital technology in financial services has allowed for more efficient matching of financial resources to small enterprises, addressing the psychological barriers that many business owners face regarding loan qualifications [8][9]. - The Chongqing financial regulatory bureau's initiative has resulted in the identification of 10.9 million high-quality small enterprises, with a significant portion having never received loans before, showcasing the potential of data-driven approaches in expanding access to finance [9].