L银行中小企业客户信用评价体系优化研究

发布时间：2018-03-22 04:39

本文选题：信用评价　切入点：商业银行　出处：《山东大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着我国市场、经济和社会的开放繁荣和国家政策的支持,为中小企业的发展提供了健康良好的经济政策环境,中小企业在此环境下茁壮成长并逐渐体现出越来越重要的作用。但同时,中小企业仍然面临着一些亟待解决的瓶颈问题,如其中比较突出的融资问题。当中小企业需要贷款时,它们的第一选择是商业银行,从理论上来说,一方面中小企业需要充足的资金以满足它们迅猛的发展态势,另一方面商业银行也需要发放贷款以实现盈利的同时调整贷款结构,这本是一个可以实现双赢的关系。但是在实际中,却存在着银行授信难的同时企业融资难的矛盾。这一问题存在的原因主要有以下两点,一方面是中小企业自身财务数据不完善或不真实,以及规模较小抵御风险能力差等缺陷,另一方面则是商业银行对中小企业信用评价不够及时,也不够准确,使商业银行不能有效的选择出合适的放贷对象和放贷金额。L银行是一家地方性股份制商业银行,在长期的发展和战略的调整之后,L银行已将主要的工作重心转向中小企业市场,中小企业贷款占其全部贷款的90%以上。与此同时,L银行的不良贷款情况也比较严重,近年来一直保持增长的趋势,到2015年不良贷款率达到了 2.72%,在全国城商行中排名前五。在此背景下,本文在整理、归纳和分析信用评价理论和方法,并借鉴国内其他商业银行针对中小企业信用评价的经验的基础上,对当前信用评价的定量和定性分析指标进行了调整和优化。本文在内容上分为三个部分:第一部分:通过大量的阅读文献、整理相关的研究经验和学习相关的理论,确定了本文所研究的信用评价体系侧重于针对中小企业,并通过对了解和梳理各种可以用于信用评价的方法,结合各种方法的优缺点和我国的实际情况确定了用网络层次分析法建立中小企业信用评价体系。第二部分:分析了 L银行的现状和L银行现有信用评价体系存在的缺陷,根据中小企业——尤其是L银行客户以制造行业和零售批发企业为主的的特点,为L银行中小企业信用评价选取了适宜的指标。使用网络层次分析法确定各评价指标的权重,从而最终确定了 L银行针对中小企业信用评价指标体系,弥补了传统中小企业评估方法的某些局限性。第三部分:案例分析及保障措施。选取了 L银行的一个贷款客户,通过案例验证了优化后信用评价体系的有效性,并提出相应的保障措施。本文在指标的选择上,具体分析L银行对中小企业信用评价体系现状和存在的问题,针对L银行贷款客户中小企业的特征,并考虑到L银行贷款客户分布较为密集行业的特征,更加全面地去考虑所有各方面能够对中小企业信用评价产生影响的要素。本文运用的网络层次分析法计算各指标权重,该方法可以考虑到各指标间的相互影响,能更合理地计算出指标的权重,对其他银行也有借鉴意义。
[Abstract]:Along with our country market, open economic and social prosperity and the support of national policy, economic policy provides a good environment for the healthy development of small and medium-sized enterprises, small and medium-sized enterprises thrive under this environment and gradually plays a more and more important role. But at the same time, SMEs are still facing some urgent bottleneck problems, such as the serious financing problems when the SMEs need loans, their first choice is the commercial bank, in theory, on the one hand, SMEs need sufficient funds to meet their rapid development trend, on the other hand, commercial banks also need loans to achieve profitability and structural adjustment loans, this is a one can achieve a win-win relationship. But in practice, there is a bank credit difficult and enterprise financing difficult contradiction. The main reasons of the problem being to Two points, one is the small and medium-sized enterprise financial data is incomplete or untrue, and smaller defects such as poor ability to resist risks, on the other hand, is a commercial bank credit evaluation of SMEs is not timely, it is not accurate enough, so that commercial banks can not effectively select appropriate lending objects and lending Bank.L a local joint-stock commercial banks, after the long-term development and strategic adjustment, L bank has been the main focus of the work to the market of small and medium enterprises, small and medium-sized enterprises above loans accounted for 90% of its total loans. At the same time, non-performing loans of L bank is also more serious in recent years has maintained a growth. The trend, to 2015 non-performing loan ratio reached 2.72%, the top five firms in the city. Under this background, this paper in finishing, induction and analysis of the theories and methods of credit evaluation, and reference to other domestic The basis for commercial banks to SMEs credit evaluation on the experience of the current credit evaluation of quantitative and qualitative indicators were adjusted and optimized. The content is divided into three parts: the first part: through a lot of reading literature, research experience and learning theory, this study determined the credit evaluation system for small and medium enterprises to focus on, and through the understanding and analysis various methods can be used for credit evaluation, combined with the advantages and disadvantages of various methods and the actual situation of our country to determine the method of establishing the credit evaluation system of small and medium-sized enterprises with the analytic network. The second part analyzes the defects of the existing credit evaluation system of the status quo and L Bank of L bank, according to the characteristics of small and medium-sized enterprises, especially the L bank customers in the manufacturing industry and the wholesale and retail enterprises, small and medium-sized enterprises for L bank letter Select the appropriate indicators for evaluation. Using network analysis and AHP to determine the weights of evaluation indexes, and finally determined the L bank for the credit evaluation index system of small and medium-sized enterprises, to make up for some of the limitations of traditional evaluation method of small and medium-sized enterprises. The third part: case analysis and protection measures. A selection of loan customers of L bank through the case, verify the validity of the credit evaluation system after optimization, and puts forward the corresponding measures. In this paper, the choice of indicators, the specific analysis of L bank for small and medium-sized enterprises credit evaluation system of the status quo and existing problems, according to the characteristics of L bank loans to customers of small and medium-sized enterprises, and considering the characteristics of L bank customer distribution is intensive industries, more comprehensive to consider all aspects of factors can affect the credit evaluation of SMEs. This paper uses the calculation of network level analysis The weight of each index can take into account the mutual influence of each index, and can calculate the weight of the index more reasonably, and it can also be used for reference for other banks.

【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F832.33

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