中国国有商业银行贷款定价机制研究

发布时间：2018-07-11 10:47

本文选题：国有商业银行 + 贷款定价机制　；参考：《云南大学》2013年博士论文

【摘要】：2004年,在人民银行的指导下,银行机构开始实施利率市场化,催生了银行贷款定价在理论与实践上的发展。信贷业务是商业银行的核心业务,贷款定价是信贷业务的关键环节。国有商业银行是我国银行体系的主体,是金融机构的龙头,对我国金融市场的运行具有重要的影响。因此,国有商业银行贷款定价机制的研究具有重要的现实意义。由于我国信贷市场长期处于利率管制状态,银行机构的贷款利率由总行统一规定,导致在利率市场化之后,国有商业银行的贷款定价工作仍处于举步维艰的困境。本研究基于国有商业银行贷款定价机制的分析,总结了对国有商业银行贷款定价绩效存在重要影响的因素,构建了国有商业银行贷款定价绩效回归分析模型,并对理论模型的显著性实施了检验,而为国有商业银行改进贷款定价策略提供了可靠的理论依据。本研究的创新性成果主要包括如下三个方面： (1)构建了国有商业银行贷款定价绩效影响因素模型,选择了客户信用评估、信贷资金监管、利率管理人员培育、贷款成本估算、客户市场定位、信贷数据整合、信息系统优化和宏观政策识别等八个指标作为现阶段国有商业银行贷款定价的影响因素,构建了国有商业银行贷款定价绩效模型。 (2)采用多元回归分析方法检验了国有商业银行贷款定价因素的有效性,发现了国有商业银行总体和个体贷款定价因素对贷款定价绩效影响的现实性和功能差异性。第一、对于国有商业银行总体而言,客户信用评估、宏观政策识别对贷款定价绩效产生了较大的支持作用,利率管理人员培育、贷款成本估算和信息系统优化对贷款定价绩效产生了一般性的支持作用,而信贷资金监管、客户市场定位和信贷数据整合对贷款定价绩效没有产生有效的支持作用。第二、对于中国工商银行而言,客户信用评估、利率管理人员培育对贷款定价绩效产生了较大的支持作用,信贷资金监管、贷款成本估算、信息系统优化和宏观政策识别对贷款定价绩效产生了一般性的支持作用,而客户市场定位、信贷数据整合对贷款定价绩效没有产生有效的支持作用。第三、对于建设银行而言,利率管理人员培育对于贷款定价绩效产生了较大的支持作用,客户信用评估、客户市场定位、信贷数据整合、宏观政策识别对贷款定价绩效产生了一般性的支持作用,而信贷资金监管、贷款成本估算、信息系统优化对贷款定价绩效没有产生有效的支持作用。第四、对于农业银行而言,信息系统优化、宏观政策识别对贷款定价绩效产生了较大的支持作用,客户信用评估、信贷资金监管、贷款成本估算对贷款定价绩效产生了一般性的支持作用,而利率管理人员培育、客户市场定位、信贷数据整合对贷款定价没有产生有效的支持作用。第五、对于中国银行而言,客户信用评估、宏观政策识别对贷款定价绩效产生了较大的支持作用,利率管理人员培育、信息系统优化对贷款定价产生一般性的支持作用,而信贷资金监管、贷款成本估算、客户市场定位、信贷数据整合对贷款定价没有产生有效的支持作用。 (3)基于理论模型的检验结果和国有商业银行贷款定价的实践,提出了具体的国有商业银行总体和个体贷款定价的改进策略。第一,对于国有商业银行总体而言,保持客户信用评估、宏观政策识别的优势,改进利率管理人员培育、贷款成本估算、信息系统优化的功能,挖掘信贷资金监管、客户市场定位、信贷数据整合的潜力。第二,对于工商银行而言,保持客户信用评估、利率管理人员培育的优势,改进信贷资金监管、贷款成本估算、信息系统优化、宏观政策识别的功能,挖掘客户市场定位、信贷数据整合的潜力。第三,对于建设银行而言,保持利率管理人员培育的优势,改进客户信用评估、客户市场定位、信贷数据整合、宏观政策识别的功能,挖掘信贷资金监管、信息系统优化的潜力。第四,对于农业银行而言,保持信息系统优化、宏观政策识别的优势,改进客户信用评估、信贷资金监管、贷款成本估算的功能,挖掘利率管理人员培育、客户市场定位、信贷数据整合的潜力。第五,对于中国银行而言,保持客户市场定位、宏观政策识别的优势,改进利率管理人员培育、信息系统优化的功能,挖掘信贷资金监管、贷款成本估算、客户市场定位、信贷数据整合的潜力。
[Abstract]:In 2004, under the guidance of the people's Bank, the banking institutions began to implement interest rate marketization, which gave birth to the development of bank loan pricing in theory and practice. Credit business is the core business of commercial banks. Loan pricing is the key link of credit business. The operation of China's financial market has an important influence. Therefore, the study of the loan pricing mechanism of state-owned commercial banks has important practical significance.
Because the credit market of our country is in the state of interest rate regulation for a long time, the loan interest rate of the bank institutions is stipulated by the general bank. The loan pricing work of the state-owned commercial banks is still in a difficult position after the interest rate marketization. This study is based on the analysis of the fixed price mechanism of the state-owned commercial banks and sums up the loan to the state-owned commercial banks. The factors that have important influence on the price performance of the funds have been influenced, and the regression analysis model of the performance of the loan pricing of the state-owned commercial banks is constructed, and the significance of the theoretical model is tested, which provides a reliable theoretical basis for the state-owned commercial banks to improve the loan pricing strategy.
The innovative achievements of this study include the following three aspects:
(1) the model of the influence factors of the performance of the loan pricing of the state-owned commercial banks is constructed, and eight indexes, such as customer credit evaluation, credit fund supervision, interest rate manager cultivation, loan cost estimation, customer market positioning, credit data integration, information system optimization and macro policy recognition, are selected as the current state commercial banks' loan pricing. The influencing factors of loan pricing performance model of state-owned commercial banks are constructed.
(2) the effectiveness of the loan pricing factors of state-owned commercial banks is tested by multiple regression analysis, and the realities and functional differences of the impact of the overall and individual loan pricing factors on the performance of the loan pricing are found.
First, for the state-owned commercial banks, the customer credit evaluation and the macro policy recognition have a great support for the loan pricing performance. The interest rate managers cultivate, the loan cost estimation and the information system optimization have a general support to the loan pricing performance, and the credit fund supervision, the customer market positioning and the letter. Loan data integration does not play an effective supporting role in loan pricing performance.
Second, for the ICBC, the customer credit evaluation, the interest rate manager cultivation has a great support to the loan pricing performance. The credit fund supervision, the loan cost estimation, the information system optimization and the macro policy recognition have a general support to the loan pricing performance, and the customer market positioning, credit data. Integration does not play an effective supporting role in loan pricing performance.
Third, for the Construction Bank, the cultivation of interest rate managers has a great support for the loan pricing performance. Customer credit assessment, customer market positioning, credit data integration, macro policy recognition have a general support for the performance of loan pricing, and credit funds supervision, loan cost estimation, information system excellence. It has no effective support for loan pricing performance.
Fourth, for the Agricultural Bank, the information system optimization and the macro policy recognition have a great support to the loan pricing performance. The customer credit evaluation, the credit fund supervision and the loan cost estimate have a general support role on the loan pricing performance, while the interest rate managers, the customer market positioning, the credit data integration are the most important. There is no effective support for loan pricing.
Fifth, for the Bank of China, customer credit evaluation and macro policy recognition have a great support for loan pricing performance. Interest rate managers cultivate, information system optimization has a general support for loan pricing, and credit funds supervision, loan based estimation, customer market positioning, credit data integration to loans. Pricing does not have an effective support.
(3) based on the test results of the theoretical model and the practice of the loan pricing of the state-owned commercial banks, this paper puts forward a specific strategy for improving the overall and individual loan pricing of the state-owned commercial banks.
First, for the state-owned commercial banks, to maintain the customer credit assessment, the advantages of the macro policy identification, the improvement of the interest rate managers, the cost estimation of the loan, the function of the information system optimization, the supervision of credit funds, the positioning of the customer market and the integration of credit data.
Second, for the industrial and commercial bank, we should keep the customer credit evaluation, the advantage of the interest rate managers, improve the credit fund supervision, the loan cost estimation, the information system optimization, the macro policy recognition function, excavate the customer market positioning, and the credit data integration potential.
Third, for the Construction Bank, to maintain the advantages of the interest rate managers, improve customer credit evaluation, customer market positioning, credit data integration, macro policy identification functions, mining credit funds supervision, the potential of information system optimization.
Fourth, for the Agricultural Bank, to optimize the information system, the advantage of macro policy identification, improve the customer credit evaluation, credit fund supervision and loan cost estimation function, excavate the potential of the cultivation of interest rate managers, customer market positioning, and credit data integration.
Fifth, for the Bank of China, we should keep the customer market position, the advantage of macro policy recognition, improve the cultivation of the interest rate managers, the function of the information system optimization, excavate the supervision of credit funds, the estimate of the loan cost, the customer market positioning, the potential of the integration of credit data.
【学位授予单位】：云南大学
【学位级别】：博士
【学位授予年份】：2013
【分类号】：F832.4

【参考文献】