【作者】 田宇；

【导师】 扈文秀；

【作者基本信息】 西安理工大学 ， 企业管理， 2019， 硕士

【摘要】 近年来,我国银行业信贷资产持续恶化,其中一个重要的原因是担保圈风险事件的频繁爆发。担保圈贷款作为商业银行担保业务的创新,曾被誉为最符合中国国情的贷款模式。在经济上行期,担保圈实现了信用增信,拓宽了企业融资方式。但在经济下行期,担保圈内个别企业发生违约,往往会产生多米诺骨牌效应,造成整个担保圈内的企业陷入困境。这使得担保圈成为商业银行信贷资产的重灾区,严重影响商业银行的发展以及区域金融市场的稳定和安全。因此,研究如何科学、有效地识别和防范担保圈风险迫在眉睫。由于担保圈通常涉及企业较多,担保关系复杂,传统的线性模型难以解决复杂的关联关系问题,本文使用社会网络分析理论对复杂担保网络进行建模研究。首先,对常见的三种担保圈识别方法进行比较研究,选取最佳的方法识别担保圈。其次,通过分析担保圈风险水平的影响因素,构建了担保圈风险测度体系,并对担保圈风险的传染路径进行可视化研究。然后,使用Z商业银行信贷系统中2014-2017年的数据进行了担保圈的识别和风险定量测算,并选取了两个典型高风险担保圈进行了风险控制实证研究。最后,结合研究结论从政府、银行、客户企业三个层面提出了担保圈风险防范对策。通过研究,本文主要获得了以下四个结论:第一,担保圈和社会网络分析领域中成分的定义相似,可以通过使用社会网络分析成分分析的方法进行担保圈的识别。第二,基于SNA成分分析方法是常见三种担保圈识别方法中最优的。第三,担保圈风险水平主要受到担保圈网络结构指标,规模指标以及不良贷款和逾期贷款等触发指标的直接影响。第四,通过稀释担保圈结构密度和降低担保圈规模可以有效降低担保圈风险水平,达到防范和控制担保圈风险的目的。本文的研究有助于商业银行科学、有效地识别担保圈,防范和控制担保圈风险,减少由于担保圈出险而形成的不良贷款,维护金融市场的安全和稳定,具有重要的理论价值和现实意义。更多还原

【Abstract】 In recent years,Chinese banking credit assets continue to deteriorate,one of the most important reasons is frequent outbreak of risk events in the guarantee circle.As an innovation in the guarantee business of commercial banlks,the guarantee circle loan has been hailed as the loan model that best suits China’s national conditions.During the economic upswing period,the guarantee circle realized credit enhancement and increased the financing methods of enterprises.However,during the economic downturn,the default of individual companies in the guarantee circle often produce a domino effect,which will cause whole enterprises irn the circle to be in trouble and become the hardest hit area of commercial banksl,credit assets,seriously affecting the development of commercial banks and stability and safety of regional financial markets.Therefore,it is extremely urgent to study to scientifically and effectively identify and prevent the risk of the guarantee circle.Due to the fact that the guarantee circle usually involves many enterprises with complicated guarantee relationship,thus the traditional linear model is unable to solve the complex problem.This paper uses the social network analysis theory to model the complex guarantee network.First of all,a comparative study of the common three circle identification methods was conducted and select the best method to identify it.Secondly,by analyzing the influencing factors of the risk level of the guarantee circle,the quantitative identification system was constructed while the infection path was visualized.Thirdly,with the data of 2014-2017 acquired from the Z conmmercial bank credit system,the identification of the guarantee circle and the quantitative measurement of the risk were carried out,and two typical high-risk guarantee circles were se.lected to conduct the risk control empirical research.Finally,combined with conclusions,the risk prevention measures for the guarantee circle were proposed from three levels:government,bank and customer company.Through research,this paper came to the following four conclusions.First,the definition of guarantee circle is similar to the components in the field of social network analysis field,and the identification of the guarantee circle can be carried out by using the method of social network analysis component analysis.Second,the SNA component analysis method is the best one among three guarantee circle identification methods.Third,the risk level of the guarantee circle is mainly affected by the guarantee network structure indicators,scale indicators and trigger indicators such as non-performing loans and overdue loans.Fourth,by diluting the structural density and reducing the size of the guarantee circle,the risk level of the guarantee circle can be effectively reduced,and the purpose of preventing and controlling risk can be achieved.The research in this paper is beneficial to commercial banks to scientifically and effectively identify the guarantee circle,prevent and control the risk of the guarantee circle,reduce the non-performing loans formed by the guarantee circle,and maintain the security and stability of the financial market.It has important theoretical and practical significance.更多还原