【作者】 张文杰；

【导师】 丁志国；

【作者基本信息】 吉林大学 ， 金融硕士（专业学位）， 2021， 硕士

【摘要】 商业银行是我国经济体系中十分重要的资金枢纽,但是随着宏观环境的不断演变以及突发事件的冲击,商业银行的经营环境发生恶化,信用风险不断累积。加之银行业刚兑预期的打破,使得商业银行加强信用风险管理势在必行。贵阳银行地处西南腹地贵州省,近年来,在国家战略以及省内政策的引导下,其业务快速增长,发展迅猛。但宏观经济与行业环境形势严峻、贵州省整体债务水平偏高,以中小微企业为主要客户群体的贵阳银行内忧外患,其信用风险管理水平一再受到挑战。因此,本文选取贵阳银行为研究对象。通过比较信用风险度量模型,本文认为调参后的KMV模型是当前的最优选择。通过KMV模型对贵阳银行违约距离的测度,本文发现,贵阳银行2017年的信用风险整体稳定且都比较小,而从2018年开始,贵阳银行的信用风险显现出大起大落的趋势。具体表现为,在2018年中、2019年前三个季度以及2020年中时,贵阳银行的信用风险相对较高,其他则较低。模型的最新预测结果显示,贵阳银行的信用风险正处于走高阶段。在此基础上,本文构建了贵阳银行信用风险影响因素的量化分析框架,结合当前数据的具体情况,确定以违约距离(DD)为因变量,以贵州省信用债余额(CD)、不良贷款率(BLR)、年化平均资产收益率(ROA)、资本充足率(CAR)、存贷款比率(DRL)为自变量,构建多元线性回归模型,并使用标准化数据带入模型以探究贵阳银行信用风险的影响因素以及影响程度。在95%的置信度下,该模型为贵阳银行信用风险识别出四个显著的影响因素,根据影响程度由大到小依次是贵阳银行流动性水平、贵州省债务环境、贵阳银行资产质量、贵阳银行盈利能力,具体变量则是与贵阳银行信用风险呈显著正相关的存贷款比率(DRL),以及与贵阳银行信用风险呈显著负相关的贵州省信用债余额(CD)、不良贷款率(BLR)和年化平均资产收益率(ROA)。同时,通过与行业平均水平进行比较,发现贵阳银行资本充足率(CAR)相对偏低。针对贵阳银行信用风险管理现存问题,本文提出(1)加强对贵州省债务环境的识别,警惕环境施压;(2)适当降低存贷款比率、结构化控制资产质量以提升信贷质量;(3)提升资本充足率、增强盈利水平、引入信用风险缓释工具以增强信用风险缓冲水平,为优化贵阳银行信用风险管理水平提供具有指导意义的政策建议。同时,本文也为我国中小银行尤其是城市商业银行的健康持续发展提供了可行的研究思路。更多还原

【Abstract】 Commercial banks are a very important capital hub in my country’s economic system.However,with the continuous evolution of the macro environment and the impact of emergencies,the business environment of commercial banks has deteriorated and credit risks continue to accumulate.Coupled with the breaking of expectations in the banking industry,it is imperative for commercial banks to strengthen credit risk management.The Bank of Guiyang is located in the southwestern hinterland of Guizhou Province.In recent years,under the guidance of national strategies and provincial policies,its business has grown rapidly and developed rapidly.However,the macroeconomic and industry environment is severe,the overall debt level of Guizhou Province is relatively high,and Guiyang Bank,which has small,medium and micro enterprises as its main customer group,has internal and external troubles,and its credit risk management level has been repeatedly challenged.Therefore,this article selects the Bank of Guiyang as the research object.By comparing the credit risk measurement models,this article believes that the KMV model after tuning is the current best choice.Through the KMV model to measure the default distance of the Bank of Guiyang,this article finds that the credit risk of the Bank of Guiyang in 2017 is stable and relatively small.Starting in 2018,the credit risk of the Bank of Guiyang has shown a trend of ups and downs.Specifically,in the middle of 2018,the first three quarters of 2019 and the middle of2020,the credit risk of Guiyang Bank is relatively high,while others are relatively low.The latest prediction results of the model show that the credit risk of Guiyang Bank is in a rising stage.On this basis,this paper constructs a quantitative analysis framework for the credit risk influencing factors of the Bank of Guiyang,combined with the specific situation of the current data,determines that the distance to default(DD)is the dependent variable,and the credit debt balance(CD)and non-performing loan ratio of Guizhou Province are used as the dependent variable.(BLR),annualized return on average assets(ROA),capital adequacy ratio(CAR),deposit and loan ratio(DRL)as independent variables,construct a multiple linear regression model,and use standardized data to bring into the model to explore the credit risk of Guiyang Bank The influencing factors and degree of influence.With a 95% confidence level,the model identified four significant factors for the credit risk of the Bank of Guiyang.According to the degree of impact,the liquidity level of the Bank of Guiyang,the debt environment of Guizhou Province,the asset quality of the Bank of Guiyang,and the Bank profitability,the specific variables are the deposit-to-loan ratio(DRL),which is significantly positively correlated with the credit risk of Guiyang Bank,and the credit debt balance(CD)and non-performing loan ratio(BLR)of Guizhou Province,which are significantly negatively correlated with the credit risk of Guiyang Bank.)And annualized return on average assets(ROA).At the same time,by comparing with the industry average,it is found that the capital adequacy ratio(CAR)of the Bank of Guiyang is relatively low.In response to the existing problems in the credit risk management of the Bank of Guiyang,this article proposes(1)Strengthen the identification of the debt environment in Guizhou Province,and be alert to environmental pressure;(2)Appropriately reduce the deposit-loan ratio and structurally control asset quality to improve credit quality;(3)Improve capital adequacy ratio,enhance profitability,introduce credit risk mitigation tools to enhance the level of credit risk buffers,and provide guiding policy recommendations for optimizing the credit risk management level of Guiyang Bank.At the same time,this article also provides feasible research ideas for the healthy and sustainable development of my country’s small and medium-sized banks,especially city commercial banks.更多还原