联系我们

论文查询结果	返回搜索

论文编号：	15706
作者编号：	2320233965
上传时间：	2025/12/9 14:37:30
中文题目：	D商业保理公司融资问题优化研究
英文题目：	Research on the Optimization of Financing Issues in Commercial Factoring Company D
指导老师：	古志辉教授
中文关键字：	商业保理；供应链金融；融资及时性
英文关键字：	Commercial factoring；Supply chain finance；Financing timeliness
中文摘要：	当前国内已将商业保理视为一种安全可靠的贸易融资方式。2024年底，中央经济工作会议时隔14年后重新定调“适度宽松的货币政策”，也给予了商业保理行业良好的外部金融发展环境。D商业保理公司为我国特大型中央企业D集团的全资子企业，通过搭建线上系统，专业运营该集团产业链上下游在全国范围内的商业保理业务。已服务中小企业供应商37174家，业务规模合计3267亿元。广泛的客户群体、庞大的业务规模依靠的是强大的融资获取能力，当前D商业保理公司已获得17家商业银行的授信批复，额度合计257亿元。除银行授信外，股东借款、同业再保理融资、资产证券化也是该公司的重要融资手段。 与此同时，D商业保理公司也面临较大的融资问题。首先是公司要求的融资成本过低，使其只能与放款审批效率较低的大型金融机构合作，产生业务需求时无法及时获得融资资金；其次是D商业保理公司12个月以上期限业务占比高达37.91%，但融资期限均为1年以内，产生期限错配问题；最后是该公司获得一笔融资需要5-30天的周期，但却承诺客户24小时内发放保理款项，存在极大的融资及时性问题。 面对上述融资问题，D商业保理公司早期希望在客户办理业务前，通过观察应收账款债务人对债权人的保理债权确权规模来预测融资需求。实践失败后，近期则通过对历史业务数据的统计来预测融资需求。上述方法的目的是提前确定融资金额，尽早发起融资工作，来抹平融资及时性问题。但第二种方法预测的业务量与实际情况依然偏差巨大。 本文经过研究和分析，提出通过总结单一客户的历史业务记录，分析该客户的融资行为习惯，进而确定各客户获得确权后的业务发起周期，来汇总出更加准确的融资金额预测量。在此基础上引入法人账户透支新融资品种，用D商业保理公司可控财力作为商业保理业务授信管理控制基础，辅以调整组织结构、优化人力资源配置、利用金融科技与大数据、健全合规管理与企业文化等措施，最终实现对D商业保理公司融资问题的优化。
英文摘要：	Commercial factoring is currently regarded as a secure and reliable trade financing method in China. At the end of 2024, the Central Economic Work Conference, for the first time in 14 years, recalibrated its stance to a "moderately accommodative monetary policy",subsequently providing a favorable external financial development environment for the commercial factoring industry. Company D Commercial Factoring is a wholly-owned subsidiary of China’s mega-sized central enterprise, Group D. It specializes in operating nationwide commercial factoring businesses for the upstream and downstream entities of Group D's industrial chain via an online system. The company has served 37,174 small and medium-sized enterprise suppliers, with a cumulative business volume of RMB 326.7 billion. This extensive client base and substantial business scale rely on robust financing acquisition capabilities. Currently, Company D has secured credit approvals from 17 commercial banks, with a total credit line of RMB 25.7 billion. Beyond bank credit, shareholder loans, interbank refactoring, and asset securitization also serve as important financing channels for the company. Concurrently, Company D faces significant financing challenges. Firstly, its stringent requirement for extremely low financing costs necessitates partnerships primarily with large financial institutions that typically have slower loan approval processes. This creates a situation where the company cannot secure funds promptly when business demands arise. Secondly, a maturity mismatch exists: business with terms exceeding 12 months accounts for a high proportion (37.91%) of its portfolio, whereas its financing instruments all have maturities of less than one year. Finally, there is a critical issue of financing timeliness: while securing a single financing facility takes Company D between 5 to 30 days, it commits to disbursing factoring funds to clients within 24 hours, creating a significant gap. To address these financing issues, Company D initially attempted to forecast business volume by monitoring the scale of factored debt confirmation by the accounts receivable debtors owed to creditors before client transactions. After this practice proved unsuccessful, the company recently shifted to predicting business volume based on statistical analysis of historical business data. The objective of these methods was to determine the required financing amount in advance, initiate financing activities earlier, and thereby bridge the timeliness gap. However, the business volume forecasts generated by the second method still exhibit substantial deviations from actual figures. Through research and analysis, this paper proposes a refined approach: by summarizing individual clients’ historical transaction records and analyzing their financing behavior patterns, the company can determine the specific application cycle for each client following receipt of debt confirmation. Aggregating these client-specific predictions is expected to yield a more accurate overall business forecast. Building on this enhanced forecasting, the study proposes introducing the new financing instrument of corporate account overdrafts and establishing the company's "controllable financial capacity" as the foundational basis for credit management control in its factoring operations. These core strategies should be supplemented by measures such as organizational restructuring, optimized human resource allocation, leveraging fintech and big data, and strengthening compliance management and corporate culture. Ultimately, this comprehensive approach aims to optimize the financing problems faced by Company D Commercial Factoring.
查看全文：	预览  下载(下载需要进行登录)