Core Insights - Jiangsu province contributes nearly 10% of China's GDP, with a projected GDP of over 13.7 trillion yuan in 2024, driven by robust industrial clusters and efficient supply chain networks [1] - The traditional supply chain finance model, heavily reliant on core enterprise credit, is facing challenges and is undergoing a transformation towards a data-driven credit system [5][6] Supply Chain Challenges - Many small and medium-sized enterprises (SMEs) in Jiangsu's manufacturing sector struggle with financing due to reliance on traditional collateral methods, which do not suit their operational models [2][3] - The "nuclear control" model, which depends on core enterprises for credit, creates significant credit risks and fails to support the financing needs of smaller enterprises [3][4] Innovative Solutions - The emergence of the "de-nuclearization" model aims to reduce reliance on core enterprise credit by utilizing data credit systems, allowing for a more inclusive financing approach [5][6] - Companies like Qingtian Technology have successfully implemented innovative financing solutions, such as "Quick Payment," which leverages transaction data to facilitate quicker access to loans for SMEs [6][7] Collaborative Financing Models - XuGong Group has developed its own supply chain finance platform, XuGong Rongpiao, to integrate suppliers and financial resources, although it initially faced challenges with traditional financing models [4][8] - New risk-sharing mechanisms have been introduced, allowing for a more collaborative approach between core enterprises and financial institutions, enhancing credit access for SMEs [8][9] Policy and Technological Support - The Chinese government is promoting the "de-nuclearization" model through policies that encourage the use of data credit and support financing for SMEs [11][12] - Jiangsu province is actively exploring digital financial services to innovate supply chain financing, aiming to create a comprehensive credit evaluation system [11][12] Future Directions - The shift towards a decentralized credit system based on real transaction data is expected to enhance the resilience of supply chains and foster closer cooperation among industry players [12][13] - Financial institutions are encouraged to adopt multi-dimensional analyses of supply chain clients to support the development of data credit systems, which will be crucial for the future of supply chain finance [12][13]

Core Insights - The People's Bank of China and other regulatory bodies have issued a notification to regulate the 40 trillion yuan supply chain finance market, pushing the industry from "core enterprise credit reliance" to "data-driven credit" to address financing difficulties faced by SMEs [1][2][7] - The new regulations emphasize a commitment from core enterprises to maintain payment terms within 60 days, reflecting heightened regulatory scrutiny on the risks in the supply chain finance sector [2][5] - The automotive and construction industries are particularly affected by these changes due to their complex supply chains and long payment cycles, which have historically placed financial strain on SMEs [2][3] Market Growth and Regulatory Changes - The supply chain finance market in China has seen explosive growth, surpassing 40 trillion yuan in 2024, with a compound annual growth rate of 13.5% from 2020 to 2024 [2] - The new regulations aim to standardize practices and reduce risks associated with payment delays and credit reliance on core enterprises, which have been known to exploit their market position [2][6] Role of Core Enterprises - Core enterprises play a dual role in the supply chain finance ecosystem, acting as both fund providers and credit bearers, which significantly influences the financial dynamics of the supply chain [4] - While some core enterprises demonstrate social responsibility by adopting buyer interest payment models, many still extend payment terms to alleviate their own cash flow issues, negatively impacting SMEs [4][5] Challenges and Risks - The practice of extending payment terms by dominant core enterprises can lead to significant liquidity issues for SMEs, with some suppliers reporting effective payment cycles extending to 10 months [5] - The existing supply chain finance model poses credit risks, as reliance on core enterprise credit can lead to a domino effect of financial instability throughout the supply chain if a core enterprise faces difficulties [6][7] Transition to Data-Driven Models - The notification encourages banks to explore "de-core" models, which focus on data-driven credit assessments rather than solely relying on core enterprise credit [7][8] - This transition aims to enhance transparency and traceability in the supply chain, allowing financial institutions to evaluate SME credit based on actual transactions [7][8] Industry Participation and Future Outlook - Smaller banks and regional banks are more actively participating in the "de-core" trend, while larger banks are expected to accelerate their product offerings in response to regulatory changes [8] - Recent collaborations, such as that between WeBank and Zhongqi Yunlian, indicate a growing trend towards integrating supply chain data for improved financing efficiency [8]