發(fā)布時(shí)間：2018-07-11 10:47

  本文選題：國(guó)有商業(yè)銀行 + 貸款定價(jià)機(jī)制�。� 參考：《云南大學(xué)》2013年博士論文

【摘要】：2004年,在人民銀行的指導(dǎo)下,銀行機(jī)構(gòu)開(kāi)始實(shí)施利率市場(chǎng)化,催生了銀行貸款定價(jià)在理論與實(shí)踐上的發(fā)展。信貸業(yè)務(wù)是商業(yè)銀行的核心業(yè)務(wù),貸款定價(jià)是信貸業(yè)務(wù)的關(guān)鍵環(huán)節(jié)。國(guó)有商業(yè)銀行是我國(guó)銀行體系的主體,是金融機(jī)構(gòu)的龍頭,對(duì)我國(guó)金融市場(chǎng)的運(yùn)行具有重要的影響。因此,國(guó)有商業(yè)銀行貸款定價(jià)機(jī)制的研究具有重要的現(xiàn)實(shí)意義。 由于我國(guó)信貸市場(chǎng)長(zhǎng)期處于利率管制狀態(tài),銀行機(jī)構(gòu)的貸款利率由總行統(tǒng)一規(guī)定,導(dǎo)致在利率市場(chǎng)化之后,國(guó)有商業(yè)銀行的貸款定價(jià)工作仍處于舉步維艱的困境。本研究基于國(guó)有商業(yè)銀行貸款定價(jià)機(jī)制的分析,總結(jié)了對(duì)國(guó)有商業(yè)銀行貸款定價(jià)績(jī)效存在重要影響的因素,構(gòu)建了國(guó)有商業(yè)銀行貸款定價(jià)績(jī)效回歸分析模型,并對(duì)理論模型的顯著性實(shí)施了檢驗(yàn),而為國(guó)有商業(yè)銀行改進(jìn)貸款定價(jià)策略提供了可靠的理論依據(jù)。 本研究的創(chuàng)新性成果主要包括如下三個(gè)方面： (1)構(gòu)建了國(guó)有商業(yè)銀行貸款定價(jià)績(jī)效影響因素模型,選擇了客戶(hù)信用評(píng)估、信貸資金監(jiān)管、利率管理人員培育、貸款成本估算、客戶(hù)市場(chǎng)定位、信貸數(shù)據(jù)整合、信息系統(tǒng)優(yōu)化和宏觀政策識(shí)別等八個(gè)指標(biāo)作為現(xiàn)階段國(guó)有商業(yè)銀行貸款定價(jià)的影響因素,構(gòu)建了國(guó)有商業(yè)銀行貸款定價(jià)績(jī)效模型。 (2)采用多元回歸分析方法檢驗(yàn)了國(guó)有商業(yè)銀行貸款定價(jià)因素的有效性,發(fā)現(xiàn)了國(guó)有商業(yè)銀行總體和個(gè)體貸款定價(jià)因素對(duì)貸款定價(jià)績(jī)效影響的現(xiàn)實(shí)性和功能差異性。 第一、對(duì)于國(guó)有商業(yè)銀行總體而言,客戶(hù)信用評(píng)估、宏觀政策識(shí)別對(duì)貸款定價(jià)績(jī)效產(chǎn)生了較大的支持作用,利率管理人員培育、貸款成本估算和信息系統(tǒng)優(yōu)化對(duì)貸款定價(jià)績(jī)效產(chǎn)生了一般性的支持作用,而信貸資金監(jiān)管、客戶(hù)市場(chǎng)定位和信貸數(shù)據(jù)整合對(duì)貸款定價(jià)績(jī)效沒(méi)有產(chǎn)生有效的支持作用。 第二、對(duì)于中國(guó)工商銀行而言,客戶(hù)信用評(píng)估、利率管理人員培育對(duì)貸款定價(jià)績(jī)效產(chǎn)生了較大的支持作用,信貸資金監(jiān)管、貸款成本估算、信息系統(tǒng)優(yōu)化和宏觀政策識(shí)別對(duì)貸款定價(jià)績(jī)效產(chǎn)生了一般性的支持作用,而客戶(hù)市場(chǎng)定位、信貸數(shù)據(jù)整合對(duì)貸款定價(jià)績(jī)效沒(méi)有產(chǎn)生有效的支持作用。 第三、對(duì)于建設(shè)銀行而言,利率管理人員培育對(duì)于貸款定價(jià)績(jī)效產(chǎn)生了較大的支持作用,客戶(hù)信用評(píng)估、客戶(hù)市場(chǎng)定位、信貸數(shù)據(jù)整合、宏觀政策識(shí)別對(duì)貸款定價(jià)績(jī)效產(chǎn)生了一般性的支持作用,而信貸資金監(jiān)管、貸款成本估算、信息系統(tǒng)優(yōu)化對(duì)貸款定價(jià)績(jī)效沒(méi)有產(chǎn)生有效的支持作用。 第四、對(duì)于農(nóng)業(yè)銀行而言,信息系統(tǒng)優(yōu)化、宏觀政策識(shí)別對(duì)貸款定價(jià)績(jī)效產(chǎn)生了較大的支持作用,客戶(hù)信用評(píng)估、信貸資金監(jiān)管、貸款成本估算對(duì)貸款定價(jià)績(jī)效產(chǎn)生了一般性的支持作用,而利率管理人員培育、客戶(hù)市場(chǎng)定位、信貸數(shù)據(jù)整合對(duì)貸款定價(jià)沒(méi)有產(chǎn)生有效的支持作用。 第五、對(duì)于中國(guó)銀行而言,客戶(hù)信用評(píng)估、宏觀政策識(shí)別對(duì)貸款定價(jià)績(jī)效產(chǎn)生了較大的支持作用,利率管理人員培育、信息系統(tǒng)優(yōu)化對(duì)貸款定價(jià)產(chǎn)生一般性的支持作用,而信貸資金監(jiān)管、貸款成本估算、客戶(hù)市場(chǎng)定位、信貸數(shù)據(jù)整合對(duì)貸款定價(jià)沒(méi)有產(chǎn)生有效的支持作用。 (3)基于理論模型的檢驗(yàn)結(jié)果和國(guó)有商業(yè)銀行貸款定價(jià)的實(shí)踐,提出了具體的國(guó)有商業(yè)銀行總體和個(gè)體貸款定價(jià)的改進(jìn)策略。 第一,對(duì)于國(guó)有商業(yè)銀行總體而言,保持客戶(hù)信用評(píng)估、宏觀政策識(shí)別的優(yōu)勢(shì),改進(jìn)利率管理人員培育、貸款成本估算、信息系統(tǒng)優(yōu)化的功能,挖掘信貸資金監(jiān)管、客戶(hù)市場(chǎng)定位、信貸數(shù)據(jù)整合的潛力。 第二,對(duì)于工商銀行而言,保持客戶(hù)信用評(píng)估、利率管理人員培育的優(yōu)勢(shì),改進(jìn)信貸資金監(jiān)管、貸款成本估算、信息系統(tǒng)優(yōu)化、宏觀政策識(shí)別的功能,挖掘客戶(hù)市場(chǎng)定位、信貸數(shù)據(jù)整合的潛力。 第三,對(duì)于建設(shè)銀行而言,保持利率管理人員培育的優(yōu)勢(shì),改進(jìn)客戶(hù)信用評(píng)估、客戶(hù)市場(chǎng)定位、信貸數(shù)據(jù)整合、宏觀政策識(shí)別的功能,挖掘信貸資金監(jiān)管、信息系統(tǒng)優(yōu)化的潛力。 第四,對(duì)于農(nóng)業(yè)銀行而言,保持信息系統(tǒng)優(yōu)化、宏觀政策識(shí)別的優(yōu)勢(shì),改進(jìn)客戶(hù)信用評(píng)估、信貸資金監(jiān)管、貸款成本估算的功能,挖掘利率管理人員培育、客戶(hù)市場(chǎng)定位、信貸數(shù)據(jù)整合的潛力。 第五,對(duì)于中國(guó)銀行而言,保持客戶(hù)市場(chǎng)定位、宏觀政策識(shí)別的優(yōu)勢(shì),改進(jìn)利率管理人員培育、信息系統(tǒng)優(yōu)化的功能,挖掘信貸資金監(jiān)管、貸款成本估算、客戶(hù)市場(chǎng)定位、信貸數(shù)據(jù)整合的潛力。
[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.
【學(xué)位授予單位】：云南大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2013
【分類(lèi)號(hào)】：F832.4

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 方曉燕;;反思我國(guó)銀行貸款定價(jià)困境問(wèn)題[J];安徽廣播電視大學(xué)學(xué)報(bào);2006年01期

2 謝羅奇,謝鴻杰;從貸款定價(jià)理論看我國(guó)貸款定價(jià)體系的完善[J];財(cái)經(jīng)理論與實(shí)踐;2005年02期

3 史澤友,黎麗,張維梁,劉代光;關(guān)于利率市場(chǎng)化進(jìn)程中人民幣貸款定價(jià)的探討[J];金融論壇;2002年11期

4 畢明強(qiáng);基于貢獻(xiàn)度分析和客戶(hù)關(guān)系的商業(yè)銀行貸款定價(jià)方法研究[J];金融論壇;2004年07期

5 王文星;;貸款定價(jià)模式與提高市場(chǎng)競(jìng)爭(zhēng)力——以工商銀行福建省分行貸款定價(jià)實(shí)踐為例[J];金融論壇;2009年01期

6 譚德俊;彭建剛;;基于“三性”平衡的商業(yè)銀行貸款定價(jià)[J];系統(tǒng)工程;2007年08期

7 中國(guó)人民銀行廣州分行課題組;;擴(kuò)大人民幣貸款利率浮動(dòng)區(qū)間對(duì)金融機(jī)構(gòu)和企業(yè)影響的調(diào)查報(bào)告[J];南方金融;2005年12期

8 邊俊杰;馮蓮娜;劉立剛;;國(guó)有商業(yè)銀行RAROC貸款定價(jià)模型及應(yīng)用[J];改革與戰(zhàn)略;2008年12期

9 朱向華;;基于客戶(hù)關(guān)系的商業(yè)銀行貸款定價(jià)研究[J];江蘇科技大學(xué)學(xué)報(bào)(社會(huì)科學(xué)版);2006年01期

10 趙躍瓊;嚴(yán)廣樂(lè);;KMV模型在銀行貸款定價(jià)中的應(yīng)用[J];上海理工大學(xué)學(xué)報(bào);2006年01期

，

本文編號(hào)：2114893