Summary:
This study investigates how digital transformation of financial infrastructure can alleviate long-standing financing constraints faced by micro, small, and medium enterprises (MSMEs) in China. As inclusive finance and digital finance are elevated to national priorities under China's financial reform agenda—highlighted in the Central Financial Work Conference and recent State Council guidelines—this research provides timely empirical insights into how digital innovation within financial institutions can enhance credit access for financially constrained firms. The focus of this research is on the People's Bank of China's Accounts Receivable Financing Service Platform (ARFSP), a centralized digital infrastructure that facilitates receivables-based collateral lending in supply chains. Traditionally, MSMEs have struggled to access formal credit markets due to their lack of fixed assets, limited credit histories, and informational opacity. The ARFSP was initially launched in 2013 to address this issue by improving receivables transparency and enabling supplier firms to pledge accounts receivable to secure loans. While the early phase relied heavily on manual data upload and verification by core firms, the platform underwent a digital upgrade in 2016 that allowed for real-time system-to-system (S2S) integration with core enterprises' ERP systems. This innovation enabled automated, authenticated transmission of transaction data between firms and financial institutions, significantly reducing the cost and frictions of receivables verification, which in turn lowered the barrier to bank financing for suppliers. Using detailed loan-level and firm-level data from the ARFSP between 2014 and 2022, the study empirically evaluates whether this digital infrastructure enhanced access to finance and improved loan terms for MSME suppliers. A difference-in-differences strategy exploits the staggered adoption of the S2S integration among core firms, comparing outcomes for suppliers associated with digitally connected firms to those still using the manual mode or not participating in the platform. To strengthen identification, the analysis further incorporates propensity score matching and triple-difference models. The findings show that digital connectivity significantly increases both the number of suppliers obtaining loans and the total loan volume extended through the platform. Importantly, the allocation of credit shifts toward smaller firms: account receivables of MSMEs rise in both frequency and value share. Moreover, the new loans enabled by digital connectivity are more inclusive in design—smaller in size, longer in duration, and lower in interest rates—thus directly aligning with the goals of inclusive finance. These financial improvements are accompanied by tangible enhancements in business performance. Suppliers connected through digitally integrated core firms exhibit better liquidity management, lower debt service costs, and stronger sales and profitability. The benefits are not confined to suppliers alone: core firms also experience gains in revenue and financial resilience, likely reflecting improved operational efficiency and supply chain coordination. Such results provide rare micro-level evidence that digital financial infrastructure can produce win-win outcomes across supply chain tiers, particularly in ecosystems involving resource-constrained firms. This reinforces theoretical arguments that public infrastructure for information sharing can act as a collective good, reducing credit frictions and enhancing allocation efficiency in financial markets. The mechanism analysis further reveals that, on the one hand, the S2S connection significantly reduces the cost of uploading and processing account receivables data—an efficiency advantage that becomes particularly prominent for core firms with extensive supplier networks. On the other hand, in regions where bank lending is more constrained, the financing facilitation brought by digitalization is especially pronounced, underscoring its potential to improve the geographic distribution of credit and promote more balanced regional development. These insights highlight how digital infrastructure not only addresses information frictions at the firm level, but also functions as a policy lever for achieving broader spatial equity in credit allocation. The study contributes to multiple academic literatures. Within supply chain finance, it highlights the role of institutional infrastructure—beyond inter-firm contracting—in shaping financing dynamics. In the financial intermediation and development literature, it empirically validates how information systems can reduce credit risk, extend lending horizons, and promote inclusive finance. Furthermore, by leveraging detailed administrative data and advanced causal inference techniques, the research sets a methodological benchmark for evaluating policy innovations in financial markets. Notably, the findings suggest that digital transformation of financial infrastructure should be treated as a core component of inclusive finance strategy, rather than a supplementary tool. Policy implications from this research are clear and actionable. Authorities should accelerate the adoption and integration of digital platforms like the ARFSP, especially among large core firms with extensive MSME supplier networks. Financial regulators may consider offering technical or fiscal incentives to encourage ERP integration with national platforms. Equally important is the need to promote a narrative of mutual benefit around data sharing, as many core firms remain hesitant to expose transaction-level data. The study shows that such sharing not only benefits MSMEs but also improves the financial performance of the core firms themselves, creating a virtuous cycle that strengthens supply chain resilience. This research opens avenues for comparative studies across different country contexts, especially in emerging markets where digital financial infrastructure remains underdeveloped. Future work could also examine the broader spillover effects of such platforms, including labor market responses and innovation incentives. Additionally, as digital ecosystems evolve, it will be important to understand how firms dynamically adapt their financing behavior, investment strategies, and risk management practices in response to enhanced financial infrastructure. Overall, this study affirms the transformative potential of digital public goods in the financial sector, and underscores their central role in building an inclusive, efficient, and resilient economic system.
何昊楠, 彭玲玲, 李劢, 陈泽丰, 刘晓蕾. 金融基础设施数字化建设与普惠金融发展——基于应收账款融资的微观证据[J]. 金融研究, 2025, 537(3): 94-112.
HE Haonan, PENG Lingling, LI Mai, CHEN Zefeng, LIU Xiaolei. Digitalization of Financial Infrastructure and the Development of Inclusive Finance: Evidence from Accounts-Receivable Financing. Journal of Financial Research, 2025, 537(3): 94-112.
[1]成程、田轩和徐照宜,2023,《供应链金融与企业效率升级——来自上市公司公告与地方政策文件的双重证据》,《金融研究》第6期,第132~149页。 [2]邓海清,2015,《兵马未动,粮草先行:“一带一路”与金融基础设施建设》,《国际经济评论》第4期,第45~52页。 [3]江伟和姚文韬,2016,《〈物权法〉的实施与供应链金融——来自应收账款质押融资的经验证据》,《经济研究》第1期,第141~154页。 [4]刘畅、曹光宇和马光荣,2020,《地方政府融资平台挤出了中小企业贷款吗?》,《社会科学文摘》第6期,第12~14页。 [5]李欢、李丹和王丹,2018,《客户效应与上市公司债务融资能力——来自我国供应链客户关系的证据》,《金融研究》第6期,第138~154页。 [6]林毅夫和李永军,2001,《中小金融机构发展与中小企业融资》,《经济研究》第1期,第10~18页。 [7]林毅夫和孙希芳,2005,《信息、非正规金融与中小企业融资》,《经济研究》第7期,第35~44页。 [8]钱小安,2003,《金融民营化与金融基础设施建设——兼论发展民营金融的定位与对策》,《金融研究》第2期,第1~11页。 [9]石晓军、张顺明,2010,《经济周期中商业信用与银行借款替代行为研究》,《管理科学学报》第12期,第10~22页。 [10]宋华、韩思齐和刘文诣,2022,《数字技术如何构建供应链金融网络信任关系?》,《管理世界》第3期,第182~200页。 [11]吴超鹏和张媛,2017,《风险投资对上市公司股利政策影响的实证研究》,《金融研究》第9期,第178~191页。 [12]王霄和张捷,2003,《银行信贷配给与中小企业贷款——一个内生化抵押品和企业规模的理论模型》,《经济研究》第7期,第68~75页。 [13]杨龙见、吴斌珍、李世刚和彭凡嘉,2021,《“以税增信”是否有助于小微企业贷款?——来自“银税互动”政策的证据》,《经济研究》第7期,第96~112页。 [14]杨汀和史燕平,2022,《金融基础设施有助于提升融资租赁的债务治理效应吗?——基于中登网实施前后的实证检验》,《金融发展研究》第6期,第13~21页。 [15]邹传伟,2019,《区块链与金融基础设施——兼论Libra项目的风险与监管》,《金融监管研究》第7期,第18~33页。 [16]张一林、林毅夫和龚强,2019,《企业规模、银行规模与最优银行业结构——基于新结构经济学的视角》,《管理世界》第3期,第31~47页。 [17]郑志刚、朱光顺、李倩和黄继承,2021,《双重股权结构、日落条款与企业创新——来自美国中概股企业的证据》,《经济研究》第12期,第94~110页。 [18]Baker, A. C., D. F. Larcker, and C. CY Wang, 2022, “How much should we trust staggered difference-in-differences estimates?”, Journal of Financial Economics, 144(2), pp.370~395. [19]Chen, Z. and Z. Jiang, 2024, “The Liquidity Premium of Digital Payment Vehicle”, Management Science, forthcoming. [20]Doblas-Madrid, A. and R. Minetti, 2013, “Sharing Information in the Credit Market: Contract level Evidence from US Firms”, Journal of Financial Economics, 109(1), pp.198~223. [21]Gan, J., Y. Guo, and C. Xu, 2018, “Decentralized Privatization and Change of Control Rights in China”, The Review of Financial Studies, 31(10), pp.3854~3894. [22]Jappelli, T. and M. Pagano, 2002, “Information Sharing, Lending and Defaults: Cross-Country Evidence”, Journal of Banking & Finance, 26(10), pp.2017~2045. [23]Liberti, J., J. Sturgess, and A. Sutherland, 2022, “How Voluntary Information Sharing Systems Form: Evidence from a U.S. Commercial Credit Bureau”, Journal of Financial Economics, 145(3), pp.827~849. [24]Liu, L., G. Lu, and W. Xiong, 2022, “The Big Tech Lending Model”, NBER Working Paper No. w30160. [25]Liu, X. L.,M. Q. Mao, and G. Nini, 2018. “Customer Risk and Corporate Financial Policy: Evidence from Receivables Securitization”, Journal of Corporate Finance, 50, pp.453~467. [26]Stiglitz, J. E. and A. Weiss, 1981, “Credit Rationing in Markets with Imperfect Information”, American Economic Review, 71(3), pp.393~410.