工商銀行湖南分行內(nèi)部信用評級管理研究
發(fā)布時間：2018-11-02 08:54
【摘要】：中國的商業(yè)銀行開展客戶評級、貸款評級的的時間不是太長，數(shù)量也不多，目前還沒有一套科學(xué)的成熟可靠的信用評級體系。各以工農(nóng)中建四大國有商業(yè)銀行為首的中國商業(yè)銀行正在摸索和建設(shè)自己的內(nèi)部評級體系。但是我國目前既沒有建立一個比較權(quán)威性的第三方評估機構(gòu)，又缺乏一套科學(xué)而有效的評級體系。沒有制定行業(yè)內(nèi)通行的統(tǒng)一規(guī)范，，各家商業(yè)銀行推行自己的客戶評級標(biāo)準(zhǔn)。同一公司客戶在不同銀行的信用評級結(jié)果差異頗大。而國外發(fā)達國家，既有正規(guī)的第三方評級機構(gòu)，也有可靠而有效的評級體系。國內(nèi)商業(yè)銀行的信用風(fēng)險管理水平和意識還有待加強和提高。由于信用評級結(jié)果的可靠性取決于參與評級客戶所提供數(shù)據(jù)的真實性，故根據(jù)銀行內(nèi)部信貸數(shù)據(jù)來構(gòu)建一套客戶信用風(fēng)險評級體系顯得尤為重要。 本文首先介紹了信用風(fēng)險的定義、新巴塞爾協(xié)議下的內(nèi)部評級法（IRB）的主要內(nèi)容。對比分析了國內(nèi)外對違約概率模型PD的研究情況。接著介紹了工商銀行湖南分行內(nèi)部信用評級工作的開展情況，對比分析了工商銀行內(nèi)部評級一期和二期項目所取得的成就及不足之處。最后運用Logistic回歸模型對湖南工行所屬的企業(yè)客戶進行實證分析，構(gòu)建湖南工行企業(yè)信用風(fēng)險評估模型。在模型的構(gòu)建時，隨機選取了72家企業(yè)作為建模樣本組，隨機選取了58家企業(yè)作為檢驗樣本組，通過處理樣本企業(yè)2012年的數(shù)據(jù)得到相應(yīng)的40個財務(wù)指標(biāo)，利用SPSS軟件進行正態(tài)性檢驗、假設(shè)檢驗、相關(guān)性檢驗來篩選指標(biāo)，最后再利用Logistic回歸模型對篩選出來的指標(biāo)進行回歸分析。 通過使用檢驗樣本組對該模型進行驗證，發(fā)現(xiàn)該模型的準(zhǔn)確率達到了84.5%。本文所得出的公司客戶信用評價模型對于湖南工行現(xiàn)有的情況來說是較為有效的。
[Abstract]:China's commercial banks carry out customer rating, loan rating is not too long, the number is not much, there is no scientific and reliable credit rating system. China's commercial banks, led by four state-owned commercial banks, are groping and building their own internal rating system. However, there is neither an authoritative third-party evaluation institution nor a scientific and effective rating system in China. There is no uniform standard in the industry, commercial banks promote their own customer rating standards. The credit rating results of the same company's customers in different banks vary greatly. Foreign developed countries, both formal third-party rating agencies, but also reliable and effective rating system. The credit risk management level and consciousness of domestic commercial banks need to be strengthened and improved. Because the reliability of the credit rating results depends on the authenticity of the data provided by the participating rating customers, it is particularly important to construct a set of customer credit risk rating system based on the internal credit data of the bank. This paper first introduces the definition of credit risk and the main content of (IRB). The research of default probability model (PD) at home and abroad is compared and analyzed. Then it introduces the development of the internal credit rating of ICBC Hunan Branch, and compares and analyzes the achievements and shortcomings of ICBC's internal rating projects in the first and second phases. Finally, the Logistic regression model is used to analyze the customers of Hunan Industrial and Commercial Bank of China (ICBC), and the credit risk assessment model of ICBC is constructed. When the model was constructed, 72 enterprises were randomly selected as modeling sample group, 58 enterprises were randomly selected as test sample group, and 40 financial indexes were obtained by processing the data of sample enterprises in 2012. The SPSS software is used for normality test, hypothesis test and correlation test to screen the indexes. Finally, the Logistic regression model is used to analyze the selected indexes. It is found that the accuracy of the model is 84.55by using the test sample group to verify the model. The customer credit evaluation model obtained in this paper is effective for the current situation of Hunan Industrial and Commercial Bank of China (ICBC).
【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F832.33
本文編號：2305543
[Abstract]:China's commercial banks carry out customer rating, loan rating is not too long, the number is not much, there is no scientific and reliable credit rating system. China's commercial banks, led by four state-owned commercial banks, are groping and building their own internal rating system. However, there is neither an authoritative third-party evaluation institution nor a scientific and effective rating system in China. There is no uniform standard in the industry, commercial banks promote their own customer rating standards. The credit rating results of the same company's customers in different banks vary greatly. Foreign developed countries, both formal third-party rating agencies, but also reliable and effective rating system. The credit risk management level and consciousness of domestic commercial banks need to be strengthened and improved. Because the reliability of the credit rating results depends on the authenticity of the data provided by the participating rating customers, it is particularly important to construct a set of customer credit risk rating system based on the internal credit data of the bank. This paper first introduces the definition of credit risk and the main content of (IRB). The research of default probability model (PD) at home and abroad is compared and analyzed. Then it introduces the development of the internal credit rating of ICBC Hunan Branch, and compares and analyzes the achievements and shortcomings of ICBC's internal rating projects in the first and second phases. Finally, the Logistic regression model is used to analyze the customers of Hunan Industrial and Commercial Bank of China (ICBC), and the credit risk assessment model of ICBC is constructed. When the model was constructed, 72 enterprises were randomly selected as modeling sample group, 58 enterprises were randomly selected as test sample group, and 40 financial indexes were obtained by processing the data of sample enterprises in 2012. The SPSS software is used for normality test, hypothesis test and correlation test to screen the indexes. Finally, the Logistic regression model is used to analyze the selected indexes. It is found that the accuracy of the model is 84.55by using the test sample group to verify the model. The customer credit evaluation model obtained in this paper is effective for the current situation of Hunan Industrial and Commercial Bank of China (ICBC).
【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F832.33
【參考文獻】
相關(guān)期刊論文 前10條
1 張玲,曾維火;基于Z值模型的我國上市公司信用評級研究[J];財經(jīng)研究;2004年06期
2 齊治平,余妙志;Logistic模型在上市公司財務(wù)狀況評價中的運用[J];東北財經(jīng)大學(xué)學(xué)報;2002年01期
3 陳衛(wèi)東;新巴塞爾資本協(xié)議評析[J];國際金融研究;2001年03期
4 陳四清;試論商業(yè)銀行風(fēng)險管理[J];國際金融研究;2003年07期
5 巢劍雄;企業(yè)財務(wù)困境預(yù)警模型[J];湖南大學(xué)學(xué)報(自然科學(xué)版);2005年01期
6 閆曉莉;徐建中;;商業(yè)銀行信用風(fēng)險評估模型比較研究[J];哈爾濱工業(yè)大學(xué)學(xué)報(社會科學(xué)版);2007年02期
7 趙子銥,趙素云;信用評分模型在中小企業(yè)信用風(fēng)險評估中的應(yīng)用[J];經(jīng)濟與管理;2005年11期
8 李志輝,李萌;我國商業(yè)銀行信用風(fēng)險識別模型及其實證研究[J];經(jīng)濟科學(xué);2005年05期
9 梁琪;企業(yè)信用風(fēng)險的量化度量研究[J];南開經(jīng)濟研究;2000年06期
10 周穎,毛定祥;銀行信用風(fēng)險評估中的非財務(wù)分析[J];上海大學(xué)學(xué)報(社會科學(xué)版);2003年02期
相關(guān)博士學(xué)位論文 前1條
1 張凌云;中國商業(yè)銀行內(nèi)部評級法研究[D];華中科技大學(xué);2010年
本文編號：2305543
本文鏈接：http://sikaile.net/guanlilunwen/bankxd/2305543.html
最近更新
教材專著
