A银行信贷决策改进研究

发布时间：2018-05-08 01:41

本文选题：信贷决策 + 财务分析　；参考：《西安工业大学》2014年硕士论文

【摘要】：本文研究的内容是银行信贷决策的改进研究。银行是以风险为经营商品的特殊行业,也是竞争性极强的行业,其核心竞争力集中反映在风险的掌控能力上,而风险的防范与把控都与信贷决策息息相关,银行信贷人员的决策过程关系到以后银行信贷资产是否能够安全回收,只有更全面的去考核借款企业的各项指标,包含财务报表指标、财务非报表指标、非财务因素及信用因素等,才能对信贷资产的安全性做出风险衡量和评级。传统的信贷决策过程主要是借助于定量分析和定性分析为主,即企业的财务指标外加信贷决策人员的经验判断来形成最终的信贷决策结论,现实操作中,由于信息的不对称,信贷人员在做信贷决策时往往会犯两种错误：一是弃真,即拒绝了优质贷款；二是纳伪,即接受了不良贷款。错误的信贷决策给银行的资金安全带来了巨大的风险隐患,而传统的分析方法已经很难适应当今我做市场经济的发展形势和监管要求的改变,怎样才能有效的识别客户是否具有偿还能力,增强信贷决策风险判断力,就必须在信用风险管理体制上进行创新优化。本文从银行的传统决策分析角度出发,重点分析了影响信贷决策的财务分析因素(含非报表因素和报表因素),详细论述了财务非报表因素中目标市场的选择、经营的周期波动性、经营的风险性及管理的风险性问题；并着重论述了财务报表因素中盈利指标、营运指标、偿债指标,并结合财务分析工具即资产负债表、利润表和现金流量表对企业的借款原因、偿还能力、盈利能力进行分析,通过对传统信贷决策中只能对财务报表因素进行风险分析的不足与缺陷,本文通过对财务分析方法的改进——VAR风险分析法来弥补了传统分析方法过于简单、不能够建立系统性和关联性的风险分析指标体系,缺乏科学依据、对行业和现金流量分析缺失的不足,进一步通过实证分析对本文的理论研究成果进行应用检验和对比,本文的研究有助于银行信贷从业人员结合实际环境制定出科学合理的信贷决策,降低犯两种信贷决策错误的概率。
[Abstract]:The content of this paper is the improvement of bank credit decision. The bank is a special industry which takes risk as the management commodity, and is also a highly competitive industry. Its core competitiveness is reflected in the control ability of the risk, and the prevention and control of the risk are closely related to the credit decision. The decision-making process of bank credit personnel is related to whether the bank credit assets can be safely recovered in the future. Only a more comprehensive assessment of the various indicators of the borrowing enterprises, including financial statement indicators, financial non-statement indicators, Only by non-financial factors and credit factors can the security of credit assets be evaluated and rated. The traditional credit decision-making process is mainly by means of quantitative analysis and qualitative analysis, that is, the financial index of enterprises plus the empirical judgment of credit decision makers to form the final credit decision conclusion, in the actual operation, because of the asymmetry of information, Credit personnel often make two kinds of mistakes when making credit decisions: one is to abandon the truth, that is, to reject the quality loan; the other is to accept the fake, that is, to accept the bad loans. The wrong credit decision has brought huge risks to the bank's capital security, but the traditional analysis method has been difficult to adapt to the development situation of the market economy and the change of supervision requirements. How to effectively identify whether the customer has the ability to repay and enhance the judgment of credit decision-making risk, we must carry out innovation and optimization in the credit risk management system. From the point of view of traditional decision analysis of banks, this paper mainly analyzes the financial analysis factors (including non-statement factors and report factors) that affect credit decision-making, and discusses in detail the choice of target market in financial non-statement factors. The paper mainly discusses the profit index, operation index, debt repayment index of the financial statement factors, and combines the financial analysis tool, I. e., balance sheet, with the problems of the cycle volatility of operation, the risk of operation and the risk of management. The profit statement and the cash flow statement analyze the reasons of borrowing, the ability to repay and the profitability of the enterprise. Through the analysis of the deficiency and defect of the risk analysis of the financial statement factors in the traditional credit decision, In this paper, the VAR risk analysis method is improved to make up for the fact that the traditional analysis method is too simple to establish a systematic and relevant index system of risk analysis, which is lack of scientific basis. For the lack of industry and cash flow analysis, further through empirical analysis of the theoretical research results of the application of the test and comparison, The research in this paper is helpful for the bank credit practitioners to make scientific and reasonable credit decisions in combination with the actual environment, and to reduce the probability of making two kinds of credit decision mistakes.
【学位授予单位】：西安工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F832.33;F832.4

【参考文献】