我國農(nóng)村中小銀行信用評級模型的評價與構(gòu)建
發(fā)布時間：2018-07-21 13:20
【摘要】：隨著我國金融體制改革的深化及市場化程度的加深,農(nóng)村中小銀行作為縣域廣大小微客戶的金融服務(wù)提供者,必然在經(jīng)濟轉(zhuǎn)型過程中扮演重要角色。然而,與之相對的是目前農(nóng)村中小銀行不良貸款率偏高,資產(chǎn)質(zhì)量不高,同時缺乏對客戶違約風險進行有效識別和預(yù)測的方法和工具,本文以農(nóng)村中小銀行信用風險測度及評級體系建立為切入點,探索我國農(nóng)村中小銀行信用風險管理方法。 首先,本文在系統(tǒng)梳理實踐和理論中涉及的各類小微客戶信用評價指標的基礎(chǔ)上,建立科學完善的小微客戶信用指標體系庫,并基于此構(gòu)建農(nóng)村商業(yè)銀行個體工商戶信用評價指標體系。 其次,本文通過對我國農(nóng)村中小銀行信用風險度量以及信用評級方法進行研究,結(jié)合目前國內(nèi)外研究前沿,在對現(xiàn)有模型進行適用性分析的基礎(chǔ)上探索適合我國農(nóng)村中小銀行的信用風險度量模型,并在此基礎(chǔ)上嘗試構(gòu)造信用風險度量的基于神經(jīng)網(wǎng)絡(luò)的logistic模型的混合模型。根據(jù)本文構(gòu)建的個體工商戶信用評價指標體系,采用農(nóng)商行實際小微客戶信貸交易及授信資料數(shù)據(jù)對logistic模型、神經(jīng)網(wǎng)絡(luò)方法以及混合模型進行檢驗,證實了創(chuàng)新構(gòu)造的混合模型具有預(yù)測精確性高以及預(yù)測穩(wěn)定性強兩方面的優(yōu)越性。 最后,本文基于神經(jīng)網(wǎng)絡(luò)的logistic模型的混合模型的預(yù)測結(jié)果,開發(fā)并設(shè)計了相應(yīng)的農(nóng)村商業(yè)銀行個體工商戶信用評分卡,同時從預(yù)測精度以及穩(wěn)健性兩個方面驗證了信用評分卡的效力。本文的研究不僅為開發(fā)適用于我國農(nóng)村商業(yè)銀行的違約風險估計工具和信用評級體系提供了理論依據(jù),更具有很強的實踐意義,將有助于指導我國農(nóng)村商業(yè)銀行提升信用風險的管控能力和水平。
[Abstract]:With the deepening of China's financial system reform and the deepening of marketization, small and medium-sized rural banks, as the financial service providers of the vast number of small and micro customers in the county area, are bound to play an important role in the process of economic transformation. However, at present, the non-performing loan ratio of small and medium-sized rural banks is on the high side, the quality of assets is not high, and there is a lack of methods and tools to effectively identify and predict the default risk of customers. Based on the establishment of credit risk measurement and rating system of rural small and medium-sized banks, this paper explores the methods of credit risk management in rural small and medium-sized banks in China. First of all, on the basis of systematically combing all kinds of small and micro customer credit evaluation indexes involved in practice and theory, this paper establishes a scientific and perfect small and micro customer credit index system database. Based on this, the index system of individual commercial bank credit evaluation is constructed. Secondly, this paper studies the credit risk measurement and credit rating methods of rural small and medium-sized banks in China, combining with the current research frontier at home and abroad. Based on the analysis of the applicability of the existing models, this paper explores the credit risk measurement model suitable for the rural small and medium-sized banks in China, and then attempts to construct a hybrid model of logistic model based on neural network for credit risk measurement. According to the credit evaluation index system of individual industrial and commercial households in this paper, the logistic model, neural network method and mixed model are tested by using the data of credit transaction and credit data of small and micro customers of agricultural and commercial banks. It is proved that the hybrid model with innovative structure has the advantages of high prediction accuracy and strong predictive stability. Finally, based on the prediction results of the mixed model of logistic model based on neural network, the corresponding credit score card of individual industrial and commercial households in rural commercial banks is developed and designed. At the same time, the effectiveness of credit scoring card is verified from two aspects: prediction accuracy and robustness. The research in this paper not only provides a theoretical basis for the development of default risk estimation tools and credit rating system for rural commercial banks in China, but also has a strong practical significance. It will be helpful to guide the rural commercial banks to improve their credit risk control ability and level.
【學位授予單位】：南京大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F832.35;F224
本文編號：2135655
[Abstract]:With the deepening of China's financial system reform and the deepening of marketization, small and medium-sized rural banks, as the financial service providers of the vast number of small and micro customers in the county area, are bound to play an important role in the process of economic transformation. However, at present, the non-performing loan ratio of small and medium-sized rural banks is on the high side, the quality of assets is not high, and there is a lack of methods and tools to effectively identify and predict the default risk of customers. Based on the establishment of credit risk measurement and rating system of rural small and medium-sized banks, this paper explores the methods of credit risk management in rural small and medium-sized banks in China. First of all, on the basis of systematically combing all kinds of small and micro customer credit evaluation indexes involved in practice and theory, this paper establishes a scientific and perfect small and micro customer credit index system database. Based on this, the index system of individual commercial bank credit evaluation is constructed. Secondly, this paper studies the credit risk measurement and credit rating methods of rural small and medium-sized banks in China, combining with the current research frontier at home and abroad. Based on the analysis of the applicability of the existing models, this paper explores the credit risk measurement model suitable for the rural small and medium-sized banks in China, and then attempts to construct a hybrid model of logistic model based on neural network for credit risk measurement. According to the credit evaluation index system of individual industrial and commercial households in this paper, the logistic model, neural network method and mixed model are tested by using the data of credit transaction and credit data of small and micro customers of agricultural and commercial banks. It is proved that the hybrid model with innovative structure has the advantages of high prediction accuracy and strong predictive stability. Finally, based on the prediction results of the mixed model of logistic model based on neural network, the corresponding credit score card of individual industrial and commercial households in rural commercial banks is developed and designed. At the same time, the effectiveness of credit scoring card is verified from two aspects: prediction accuracy and robustness. The research in this paper not only provides a theoretical basis for the development of default risk estimation tools and credit rating system for rural commercial banks in China, but also has a strong practical significance. It will be helpful to guide the rural commercial banks to improve their credit risk control ability and level.
【學位授予單位】：南京大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F832.35;F224
【參考文獻】
相關(guān)期刊論文 前10條
1 梁琪;企業(yè)信用風險的主成分判別模型及其實證研究[J];財經(jīng)研究;2003年05期
2 于立勇,詹捷輝;基于Logistic回歸分析的違約概率預(yù)測研究[J];財經(jīng)研究;2004年09期
3 宋雪楓;楊朝軍;徐任重;;商業(yè)銀行信用風險評估的生存分析模型及實證研究[J];金融論壇;2006年11期
4 李志輝,李萌;我國商業(yè)銀行信用風險識別模型及其實證研究[J];廣東社會科學;2005年02期
5 陳守東;李曉純;劉兵;;我國信用風險違約概率計量模型的實證比較研究[J];工業(yè)技術(shù)經(jīng)濟;2009年04期
6 程建;連玉君;劉奮軍;;信用風險模型的貝葉斯改進研究[J];國際金融研究;2009年01期
7 程鵬,吳沖鋒,李為冰;信用風險度量和管理方法研究[J];管理工程學報;2002年01期
8 王春峰,萬海暉,張維;組合預(yù)測在商業(yè)銀行信用風險評估中的應(yīng)用[J];管理工程學報;1999年01期
9 馬九杰,郭宇輝,朱勇;縣域中小企業(yè)貸款違約行為與信用風險實證分析[J];管理世界;2004年05期
10 于立勇;商業(yè)銀行信用風險評估預(yù)測模型研究[J];管理科學學報;2003年05期
，本文編號：2135655
本文鏈接：http://www.sikaile.net/guanlilunwen/bankxd/2135655.html
最近更新
教材專著
