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近几年国内商业保理的快速发展在一定程度上有效缓解了中小企业的融资问题。然而由于商业保理交易在进行中存在潜在交易风险,导致国内商业保理业务叙做效率低下。文章为了提高中小企业叙做保理业务的效率,针对中小企业如何选择商业保理公司、以及商业保理公司如何确定交易的对象等问题提出计量模型,并对这些筛选环节的风险进行量化和分析。文章拟选取4家商业保理公司以及6家中小型企业,通过运用并结合KMV模型与BP神经网络模型,从保理公司自身实力和中小型企业信用等级评价两个方面共同作用,得出预测交易发生的参考指标并同时比较商业保理公司和中小企业在进行一笔商业保理交易时的综合性风险高低,为筛选环节存在的问题提供新的解决思路,具有较强的参考意义和应用价值。
In recent years, the rapid development of commercial factoring in China has effectively alleviated the financing problem of SMEs to a certain extent. However, due to the potential transaction risk in the course of commercial factoring transactions, the efficiency of the domestic commercial factoring business has been inefficient. In order to improve the efficiency of SMEs’ business of factoring, this paper proposes a measurement model of how SMEs select commercial factoring companies and how commercial factoring companies determine the target of the transaction, and quantifies and analyzes the risks of these screening processes . This article intends to select four commercial factoring companies and six small and medium-sized enterprises. By using and combining the KMV model with the BP neural network model, the factoring company’s own strength and the evaluation of the SME credit rating are combined in two aspects to obtain the forecast transaction The occurrence of the reference indicators and commercial insurance companies and SMEs at the same time in a commercial factoring transactions when the overall level of risk for the screening of existing problems provide a new way of thinking has a strong reference value and application value .