中国国有商业银行贷款定价机制研究
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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。
In2004Chinese banking institutions began to implement market-oriented interest rate reform under the guidance of the People's Bank (Central Bank of China), which gave birth to the development of bank loans theory and practice. The credit business is the core business of commercial banks, and loan pricing is the key link of the credit business. The state-owned commercial banks are the main body of China's financial system, leading financial institutions, and has an important impact on the change of China's financial market. Therefore, the research of loan pricing mechanism of state-owned commercial bank has an important practical significance.
Being that the China's credit markets is in the state of interest rate controls in long-term, and the lending rate is stipulated to uniform provisions by head office, the loan pricing power of state-owned commercial bank is still in a difficult predicament, after lending rates is float, not suited to the development of modern financial market. Based on the analysis of the state-owned commercial bank loan pricing mechanism, the study sums up the factors affecting the loan pricing performance, and builds a regression analysis model of state-owned commercial bank loan pricing, and certifies the theory model and provides a reliable theoretical reference for state-owned commercial banks to improve loan pricing strategy.
The innovative results of this study includes following three aspects:
(1) Construction of state-owned commercial bank loan pricing performance influencing factors model. This study selects customer credit evaluation, credit funds supervision, cultivating the interest rate manager, estimating loans cost, customer market positioning, the credit data integration, information system optimization and macroeconomic policies identification as the impact factors of state-owned commercial banks loan pricing, so as to build the loan pricing performance model of state-owned commercial banks.
(2) Using multiple regression analysis to test the effectiveness of the state-owned commercial bank loan pricing factors, thereby discovering realistic and functional differences of loan pricing factors for loan pricing performance in both overall and individual commercial banks.
Firstly, regarding as loan pricing performance of overall state-owned commercial banks, such factors as customer credit assessment and macroeconomic policy recognition take a great role, such factors as interest rate management staff training, estimating loan cost and information system optimization take a general role, and such factors as credit funds supervision, customer market positioning, and credit data integration do not produce an effective role.
Secondly, for the loan pricing performance improvement of Industrial and Commercial Bank of China, such factors as customer credit assessment and interest rate staff training take a great role, such factors as credit fund supervision, loans cost estimating, information system optimization and macroeconomic policies identification take a general role, and such factors as customer market positioning and credit data integration do not produce an effective role.
Thirdly, for the performance improvement of the Construction Bank, interest rate staff cultivating takes a great role, and such factors as customer credit estimation, customer market positioning, credit data integration and macroeconomic policies identification takes a general role, and credit funds supervision, loans cost estimating and information system optimization do not produce an effective role.
Fourthly, for the performance improvement of the Agricultural Bank, such factors as information system optimization and macroeconomic policies identification take a great role, such factors as customer credit assessment, credit fund supervision and loan costs estimating take a general role, and such factors as interest rate manager training, customer market positioning and credit data integration do not produce an effective role.
Fifthly, for the performance improvement of the Bank of China, such factors as customer credit assessment and macroeconomic policies recognition takes a great role, such factors as interest rate management staff cultivating and information system optimization take a general role, and the such factors as credit funds supervision, loan cost estimating, customer market positioning and credit data integration do not produce an effective role.
(3) Based on the test result of the theoretical model and loan pricing realistic practice of state-owned commercial bank, providing the personalized loan pricing improvement strategy in both overall and individual commercial banks.
Firstly, for the overall state-owned commercial banks, to maintain the advantage of customer credit assessment and macroeconomic policy identification, cultivate the function of interest rate management staff training, loan cost estimating and information system optimization, mining the potential of credit funds supervision, clients market positioning and credit data integration.
Secondly, for the Industrial and Commercial Bank, to maintain the advantage of customer credit assessment and interest rate management staff training, cultivate the function of credit funds supervision, loan cost estimating, information system optimization and macroeconomic policies identification, mining the potential of customer market positioning and credit data integration.
Thirdly, for the Construction Bank, to keep the advantage of interest rate staff cultivating, improve the function of customer credit assessment, customer market positioning, credit data integration and macro-policy identification, mining the potential of credit funds supervision and information system optimization.
Fourthly, for the Agricultural Bank, to keep the advantage of macro-policy identification and information system optimization, and cultivate the function of customer credit assessment, credit funds supervision and estimating loan cost, and mining the potential of interest rate staff training, customer market positioning and credit data integration.
Fifthly, for the Bank of China, to keep the advantage of customer market positioning and macro-policy identification, improve the function interest rate management staff training and information system optimization, mining the potential of credit funds supervision, loan cost estimating, customer market positioning and credit data integration.
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。
In2004Chinese banking institutions began to implement market-oriented interest rate reform under the guidance of the People's Bank (Central Bank of China), which gave birth to the development of bank loans theory and practice. The credit business is the core business of commercial banks, and loan pricing is the key link of the credit business. The state-owned commercial banks are the main body of China's financial system, leading financial institutions, and has an important impact on the change of China's financial market. Therefore, the research of loan pricing mechanism of state-owned commercial bank has an important practical significance.
Being that the China's credit markets is in the state of interest rate controls in long-term, and the lending rate is stipulated to uniform provisions by head office, the loan pricing power of state-owned commercial bank is still in a difficult predicament, after lending rates is float, not suited to the development of modern financial market. Based on the analysis of the state-owned commercial bank loan pricing mechanism, the study sums up the factors affecting the loan pricing performance, and builds a regression analysis model of state-owned commercial bank loan pricing, and certifies the theory model and provides a reliable theoretical reference for state-owned commercial banks to improve loan pricing strategy.
The innovative results of this study includes following three aspects:
(1) Construction of state-owned commercial bank loan pricing performance influencing factors model. This study selects customer credit evaluation, credit funds supervision, cultivating the interest rate manager, estimating loans cost, customer market positioning, the credit data integration, information system optimization and macroeconomic policies identification as the impact factors of state-owned commercial banks loan pricing, so as to build the loan pricing performance model of state-owned commercial banks.
(2) Using multiple regression analysis to test the effectiveness of the state-owned commercial bank loan pricing factors, thereby discovering realistic and functional differences of loan pricing factors for loan pricing performance in both overall and individual commercial banks.
Firstly, regarding as loan pricing performance of overall state-owned commercial banks, such factors as customer credit assessment and macroeconomic policy recognition take a great role, such factors as interest rate management staff training, estimating loan cost and information system optimization take a general role, and such factors as credit funds supervision, customer market positioning, and credit data integration do not produce an effective role.
Secondly, for the loan pricing performance improvement of Industrial and Commercial Bank of China, such factors as customer credit assessment and interest rate staff training take a great role, such factors as credit fund supervision, loans cost estimating, information system optimization and macroeconomic policies identification take a general role, and such factors as customer market positioning and credit data integration do not produce an effective role.
Thirdly, for the performance improvement of the Construction Bank, interest rate staff cultivating takes a great role, and such factors as customer credit estimation, customer market positioning, credit data integration and macroeconomic policies identification takes a general role, and credit funds supervision, loans cost estimating and information system optimization do not produce an effective role.
Fourthly, for the performance improvement of the Agricultural Bank, such factors as information system optimization and macroeconomic policies identification take a great role, such factors as customer credit assessment, credit fund supervision and loan costs estimating take a general role, and such factors as interest rate manager training, customer market positioning and credit data integration do not produce an effective role.
Fifthly, for the performance improvement of the Bank of China, such factors as customer credit assessment and macroeconomic policies recognition takes a great role, such factors as interest rate management staff cultivating and information system optimization take a general role, and the such factors as credit funds supervision, loan cost estimating, customer market positioning and credit data integration do not produce an effective role.
(3) Based on the test result of the theoretical model and loan pricing realistic practice of state-owned commercial bank, providing the personalized loan pricing improvement strategy in both overall and individual commercial banks.
Firstly, for the overall state-owned commercial banks, to maintain the advantage of customer credit assessment and macroeconomic policy identification, cultivate the function of interest rate management staff training, loan cost estimating and information system optimization, mining the potential of credit funds supervision, clients market positioning and credit data integration.
Secondly, for the Industrial and Commercial Bank, to maintain the advantage of customer credit assessment and interest rate management staff training, cultivate the function of credit funds supervision, loan cost estimating, information system optimization and macroeconomic policies identification, mining the potential of customer market positioning and credit data integration.
Thirdly, for the Construction Bank, to keep the advantage of interest rate staff cultivating, improve the function of customer credit assessment, customer market positioning, credit data integration and macro-policy identification, mining the potential of credit funds supervision and information system optimization.
Fourthly, for the Agricultural Bank, to keep the advantage of macro-policy identification and information system optimization, and cultivate the function of customer credit assessment, credit funds supervision and estimating loan cost, and mining the potential of interest rate staff training, customer market positioning and credit data integration.
Fifthly, for the Bank of China, to keep the advantage of customer market positioning and macro-policy identification, improve the function interest rate management staff training and information system optimization, mining the potential of credit funds supervision, loan cost estimating, customer market positioning and credit data integration.
引文
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