中国光大银行汽车供应链融资业务的风险管理研究 摘要 中国已成为世界上最大的汽车生产和消费市场，然而在汽车供应链融资业务上， 作为重要流通环节的中小汽车经销商却常常面临企业规模偏小、资质一般、财务不健 全、民营私人老板、缺乏可抵押资产等问题，在传统银行信贷审批时很难获得银行融 资。 供应链融资是基于供应链上下游企业的物流、信息流和资金流，由商业银行等金 融机构针对供应链企业开展的新型融资方式。在供应链融资的实践中，中国光大银行 汽车供应链融资业务在市场上运行发展了18年，基于“贸易的自偿性”、依托汽车合 格证监管等手段，对银行来说该项业务已经成为拓展汽车欧亿·体育（中国）有限公司授信客户的一个拳头产 品。 虽然中国光大银行汽车供应链融资业务已经形成了贷前调查、贷中审查审批、贷 中放款及运行、贷后管理的全流程风险管理模式，贯穿以信息流、物流、资金流相互 印证为基础，汽车合格证的监管为手段，销售资金回笼后授信额度释放为途径的风险 控制关键点，但看似完善的风险控制设计，近年来，风险暴露的个案却层出不穷，主 要由于风险监控手段未能及时识别出借款人主营业务以外的其他经营、无法规避第三 方监管公司的作假行为，以及单户管控，成本高、耗时大，难以达到管控效果等问题。 究其背后的原因主要是因为现有的风险控制手段并未很好的规避信息不对称、道德风 险和逆向选择的问题，无法避免商业银行内、外部的委托代理机制的缺陷等原因。 随着金融科技的变革以及互联网技术的发展与大数据在各行各业的实际应用，使 得依托互联网技术与互联网工具，提供金融融资服务成为可能。银行可以利用所能掌 握的海量用户数据和数据资源，构建贷款服务的场景，也可以利用核心企业内部总揽 的信息流、资金流、物流数据，通过数据模型，将信贷作为基础服务和增值服务的内 容。 作者建议在风险管理的每个环节，适时引入风险预警管理系统的实时监控，并运 用大数据收集、分析各风控环节的交易数据，实时与均值进行比对，通过数据模型， 及时识别出客户现有交易行为与均值的偏离度，偏离度在我们的容忍范围内则视为正 常，一旦偏离度超过我们的容忍度范围，系统自动提示异常。 本文通过深入研究汽车供应链融资业务的风险管理方法，提炼出原有业务的风险 控制关键点，通过案例分析，发现原有风险管理模式存在的问题，并挖掘问题背后的 原因，通过原理分析和经销商与整车厂、经销商与第三方监管公司的两个博弈分析， 摘要 得出原有风险管理模式中存在的弊端，通过引入大数据风控模式和风险预警系统对原 有风险管理流程进行改进，不仅可以提高所获信息的准确性和及时性，还可以减少银 行的贷前、贷中、贷后环节的管理成本，提高管理效率，提高收益水平，有利于汽车 供应链融资业务的迅速推广。 在经济转型、利率市场化、金融脱媒、金融科技变革等大环境下，研究光大银行 汽车供应链融资业务风险控制中存在的问题，最主要是研究其业务运行背后的风险控 制模式和风险控制关键点，从而为如何改进原有业务以更加适应当前的经济金融环 境、如何推广至其他供应链融资业务，扩大银行信贷业务规模，更好的服务中小企业 提供了方向和模式。 关键词： 供应链融资，汽车供应链融资风险，风险管理，风险预警，大数据 ABSTRACT Research on Risk Management of China Everbright Bank's Automotive Supply Chain Financing Businesses ABSTRACT China has become the largest automobile production and consumption market in the world. However, in the automotive industry chain financing businesses, small and medium-sized automobile dealers, as an important circulation link, often face issues such as small enterprise scale, ordinary qualifications, financial insufficiency, private owners, and lack of mortgageable assets, making it difficult to obtain bank financing during traditional bank credit approvals. Supply chain financing is based on the logistics, information flow, and capital flow of upstream and downstream enterprises in the supply chain, which is led by financial institutions represented by commercial banks to provide financing for enterprises in the supply chain. In the practice of supply chain financing, China Everbright Bank’s automotive supply chain financing business has been under operation in the market for 18 years. Based on the “self-liquidating nature of trade” and relying on the supervision of automobile certifications, it has become the banks’ promotional product for the expansion of credit customers in the automotive industry. Although China Everbright Bank's automotive supply chain financing business has formed a full-process risk management model of pre-loan investigation, loan review and approval, loan lending and operation, and post-loan management, it is based on the mutual verification of information flow, logistics, and capital flow. The key point of risk control is the supervision of automobile certificate as a means, and the release of credit line after the return of sales funds. However, seemingly perfect risk control design, in recent years, cases of risk exposure have emerged endlessly, which is mainly due to the failure of risk monitoring methods to identify other operations other than the borrower's main business in a timely manner, without regulations to avoid third-party supervision of fraud by companies, single approval for single business, single household management and control, high cost, high time consuming, difficult to achieve control and other issues. The reason behind this is mainly because the existing risk control methods do not well avoid the issue of information unsymmetrized, adverse selection and moral hazard, and can’t avoid the defects of the principal and agent mechanism inside and outside commercial banks. ABSTRACT With the transformation of financial technology and the development of Internet technology and the practical application of big data in various industries, it has become possible to provide financing services relying on Internet technologies and tools. Banks can use the massive amount of user data and data resources that they can master to build a loan service scenario, and they can also use the information flow, capital flow, and logistics data collected by core enterprises to use credit as basic and value-added service contents through data models. The author proposed to introduce real-time monitoring of the risk early-warning management system at each stage of risk management in a timely manner, and to use big data to collect and analyze transaction data of each risk control link, then compare it with the mean in real time, and identify customers in time through the data models to identify degree of deviation between the existing trading behavior and the mean. The degree of deviation is considered normal within our tolerance range. Once the degree of deviation exceeds our tolerance range, the system automatically prompts an exception. In this paper, through in-depth research on the risk management methods of the automotive supply chain financing businesses, the key points of the original business's risk control were extracted. Through case analysis, the issues in the original risk management model were discovered, and the reasons behind the issues were found. Analysis of the two games between dealers and OEMs, dealers and third-party regulatory companies, and the shortcomings of the original risk management model were found. The original risk management process was carried out by introducing a big data separate control model and a risk early warning system. The improvement can not only improve the accuracy and timeliness of the information obtained, but also reduce the management cost of the account manager's pre-loan, loan operation, and post-loan links, improve management efficiency, increase income levels, and help the rapid promotion of the automotive supply chain financing business. In the context of economic transformation, interest rate liberalization, financial disintermediation, and fintech transformation, the issues in the risk control of China Everbright Bank's automotive supply chain financing business were studied. The most important point is to study the risk control mode and risk control behind its business operations, which can provide the direction and model on how to improve the original business to better adapt to the current economic and financial environment, how to promote it to other supply chain financing businesses, expand the scale of bank credit business, and better serve SMEs. ABSTRACT KEYWORDS: Supply Chain Financing, Automotive Supply Chain Financing Risks, Risk Management, Risk Early Wa