中小企业银行贷款决策模型研究及应用
发布时间：2018-11-10 08:10
【摘要】：改革开放以来，中小企业在国民经济和社会发展中发挥着巨大作用，近年来浮现的中小企业融资难问题已成为社会各界关注的焦点。一方面，由于财务制度不完善、抵御风险能力弱、银企信息不对称等原因，中小企业很难从银行贷到款，融资问题已成为阻碍其发展的关键因素；另一方面，银行业竞争日益激烈，在目标客户选择上的趋同性致使信贷资源向大客户集中，银行议价能力减弱，利差空间缩小，急需开辟新的业务领域，制造新的利润增长点。如何开发出合适的中小企业贷款决策模型，以实现风险、收益的平衡与中小企业和银行的共赢，成为摆在我们面前的重要课题。 本文在对中小企业融资现状和风险特征进行充分调研与分析的基础上，通过研究银行贷款决策的国内外文献和相关技术，建立了中小企业银行贷款决策模型。该模型计算量小，应用性强，，预测较准确，能有效运用于银行对中小企业的贷款决策。 本文的研究工作主要有以下几个方面： 1.中小企业财务评价指标体系的建立。本论文运用财务分析方法对中小企业财务评价指标进行初选，运用计量经济软件EViews建立回归模型，经模型检验后最终建立由8个核心指标构成的中小企业财务评价指标体系，从而确定出影响银行对中小企业贷款的决定因素。 2.采用组合算法建立中小企业银行贷款决策模型。本论文采集上市公司相关财务数据作为实验样本并进行标准化处理，以MATLAB作为开发语言，通过遗传算法改进RBF神经网络的参数，用梯度下降法对结果进一步寻优，进而得出预测结果。 3.实验仿真与模型应用。本文利用经训练的中小企业银行贷款决策模型，分别使用经遗传算法优化和未经过优化的RBF神经网络进行仿真实验，结果显示引入遗传算法提高了模型预测的准确率。进一步将该模型应用于某商业银行实际的中小企业贷款中，通过对预测结果的分析为贷款决策提供依据。
[Abstract]:Since the reform and opening up, small and medium-sized enterprises (SMEs) have played a great role in the national economy and social development. In recent years, the financing difficulties of SMEs have become the focus of attention. On the one hand, because the financial system is not perfect, the ability to resist risks is weak, and the information of banks and enterprises is not symmetrical, it is very difficult for small and medium-sized enterprises to get loans from banks, so the financing problem has become the key factor that hinders their development. On the other hand, the competition of the banking industry is becoming more and more intense, and the convergence in the choice of target customers leads to the concentration of credit resources to the large customers, the weakening of the bargaining power of the banks, the narrowing of the margin space, the urgent need to open up new business fields and the creation of new profit growth points. How to develop a suitable loan decision model for SMEs to realize the balance of risk and income and the win-win situation between SMEs and banks has become an important subject in front of us. Based on the investigation and analysis of the current financing situation and risk characteristics of small and medium-sized enterprises (SMEs), this paper establishes a decision model of bank loans for small and medium-sized enterprises (SMEs) by studying the domestic and foreign literature and related technologies of bank loan decision-making. The model has the advantages of small calculation, strong application, accurate prediction, and can be effectively applied to the loan decision of the bank to the small and medium-sized enterprises. The main research work of this paper is as follows: 1. The establishment of financial evaluation index system for small and medium-sized enterprises. In this paper, the financial evaluation index of small and medium-sized enterprises is selected by the method of financial analysis, and the regression model is established by using the econometric software EViews, and the financial evaluation index system of small and medium-sized enterprises which is composed of eight core indicators is finally established after the model test. In order to determine the impact of bank loans to small and medium-sized enterprises to determine the factors. 2. The combination algorithm is used to establish the decision model of bank loan for small and medium-sized enterprises. In this paper, the relevant financial data of listed companies are collected as experimental samples and standardized processing. With MATLAB as the development language, the parameters of RBF neural network are improved by genetic algorithm, and the results are further optimized by gradient descent method. Then the prediction results are obtained. 3. Experimental simulation and model application. In this paper, the trained SME bank loan decision model is used to simulate the RBF neural network, which is optimized by genetic algorithm and unoptimized, respectively. The results show that the accuracy of model prediction is improved by introducing genetic algorithm. Furthermore, the model is applied to a commercial bank to provide the basis for the loan decision through the analysis of the forecast results.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F276.3;F832.4;TP183
本文编号：2321895
[Abstract]:Since the reform and opening up, small and medium-sized enterprises (SMEs) have played a great role in the national economy and social development. In recent years, the financing difficulties of SMEs have become the focus of attention. On the one hand, because the financial system is not perfect, the ability to resist risks is weak, and the information of banks and enterprises is not symmetrical, it is very difficult for small and medium-sized enterprises to get loans from banks, so the financing problem has become the key factor that hinders their development. On the other hand, the competition of the banking industry is becoming more and more intense, and the convergence in the choice of target customers leads to the concentration of credit resources to the large customers, the weakening of the bargaining power of the banks, the narrowing of the margin space, the urgent need to open up new business fields and the creation of new profit growth points. How to develop a suitable loan decision model for SMEs to realize the balance of risk and income and the win-win situation between SMEs and banks has become an important subject in front of us. Based on the investigation and analysis of the current financing situation and risk characteristics of small and medium-sized enterprises (SMEs), this paper establishes a decision model of bank loans for small and medium-sized enterprises (SMEs) by studying the domestic and foreign literature and related technologies of bank loan decision-making. The model has the advantages of small calculation, strong application, accurate prediction, and can be effectively applied to the loan decision of the bank to the small and medium-sized enterprises. The main research work of this paper is as follows: 1. The establishment of financial evaluation index system for small and medium-sized enterprises. In this paper, the financial evaluation index of small and medium-sized enterprises is selected by the method of financial analysis, and the regression model is established by using the econometric software EViews, and the financial evaluation index system of small and medium-sized enterprises which is composed of eight core indicators is finally established after the model test. In order to determine the impact of bank loans to small and medium-sized enterprises to determine the factors. 2. The combination algorithm is used to establish the decision model of bank loan for small and medium-sized enterprises. In this paper, the relevant financial data of listed companies are collected as experimental samples and standardized processing. With MATLAB as the development language, the parameters of RBF neural network are improved by genetic algorithm, and the results are further optimized by gradient descent method. Then the prediction results are obtained. 3. Experimental simulation and model application. In this paper, the trained SME bank loan decision model is used to simulate the RBF neural network, which is optimized by genetic algorithm and unoptimized, respectively. The results show that the accuracy of model prediction is improved by introducing genetic algorithm. Furthermore, the model is applied to a commercial bank to provide the basis for the loan decision through the analysis of the forecast results.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F276.3;F832.4;TP183
【参考文献】
相关期刊论文 前10条
1 张程;李文雯;张振新;;公司规模与资产负债率:来自上市公司的证据[J];财经问题研究;2010年11期
2 何自力;;银行中小企业贷款的效益与风险分析[J];金融论坛;2006年01期
3 张超群;郑建国;钱洁;;遗传算法编码方案比较[J];计算机应用研究;2011年03期
4 柯孔林;冯宗宪;;基于粗糙集和神经网络集成的贷款风险5级分类[J];控制理论与应用;2008年04期
5 李朝静;唐幼纯;黄霞;;BP神经网络的应用综述[J];劳动保障世界(理论版);2012年08期
6 张友棠,杨轶;基于“5C”的企业信用评价标准化体系的构建[J];世界标准化与质量管理;2005年09期
7 陈晓红;张泽京;王傅强;;基于KMV模型的我国中小上市公司信用风险研究[J];数理统计与管理;2008年01期
8 田永强;层次分析法在银行贷款投放决策中的应用[J];统计与决策;2004年07期
9 邓继雄;李志舜;梁红;;确定RBF神经网络参数的新方法[J];微处理机;2006年04期
10 郭战琴,周宗放;基于VaR约束的商业银行贷款组合多目标决策[J];系统工程理论方法应用;2005年02期
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