本文選題：小額信貸 + 小額貸款公司��； 參考：《西南財經(jīng)大學(xué)》2013年碩士論文

【摘要】：小額信貸(Microcredit)是一種特殊的信貸服務(wù),它專門服務(wù)于一個社會群體,這個社會群體很難通過傳統(tǒng)常規(guī)的融資渠道進(jìn)行融資,而小額信貸通過對他們提供小額度、持續(xù)的貸款來滿足他們?nèi)粘Ｉa(chǎn)經(jīng)營的資金需求。其主要的服務(wù)對象包括了個體工商戶、小作坊主、小業(yè)主、微型、中小型企業(yè)以及中低收入群體。小額信貸放貸機(jī)構(gòu)在中國包括了農(nóng)村商業(yè)銀行、城市商業(yè)銀行、郵政儲蓄銀行等正規(guī)金融機(jī)構(gòu),也包括專業(yè)的小額信貸公司。本文側(cè)重研究的是類似作者曾經(jīng)實習(xí)過的成都某外資小額貸款公司這樣的專業(yè)的商業(yè)小額貸款公司,它們的建立合理的集中了民間資金,規(guī)范了民間借貸市場,同時也有效地解決了個體工商戶、微型、中小型企業(yè)融資難的問題。 小額貸款對滿足個體工商戶、微型、中小型企業(yè)、農(nóng)戶等中小融資強(qiáng)烈的融資需求,規(guī)范民間資本借貸,增加就業(yè),推動經(jīng)濟(jì)發(fā)展起著巨大的促進(jìn)作用。但是,我國小額貸款公司成立時間不長,許多問題亟待解決,特別是信貸風(fēng)險的控制問題。從信用制度和風(fēng)險評估手段來看,農(nóng)戶、城市個體工商戶以及中小企業(yè)沒有完善的信用環(huán)境,也缺乏有效的技術(shù)手段對他們進(jìn)行風(fēng)險管理；從運(yùn)營角度來看,很多省市和地區(qū)并沒有制定對商業(yè)小額貸款公司的具體實施規(guī)范和措施；此外,資金來源受到限制、業(yè)務(wù)單一、貸款缺乏抵押物以及服務(wù)對象的弱勢,導(dǎo)致了小額貸款公司的抗風(fēng)險能力脆弱。因此探索如何控制和規(guī)避小額貸款的風(fēng)險,促進(jìn)其健康發(fā)展具有重要的現(xiàn)實意義。 一、研究目的 中國小額貸款由于發(fā)展時間不長,小額信貸機(jī)構(gòu)逐步的商業(yè)化,開始自主經(jīng)營、自負(fù)盈虧,向著探索能夠?qū)崿F(xiàn)可持續(xù)發(fā)展的目標(biāo)而努力,但在此過程中,仍然面臨了一些亟待解決的問題,如覆蓋率低、難以形成規(guī)模、達(dá)到盈虧平衡點、信用體系建設(shè)滯后、信用風(fēng)險難以被有效的識別和評估以及管理,這些問題嚴(yán)重制約了我國小額信貸業(yè)務(wù)發(fā)展的進(jìn)程。而究其本源,造成這些問題的一個非常主要的原因是：小額信貸機(jī)構(gòu)難以有效的對其目標(biāo)客戶進(jìn)行信用風(fēng)險水平的識別、評估以及管理,若無法對信用風(fēng)險水平進(jìn)行有效的識別就無法保證高比例的償還率,如果沒有一套先進(jìn)的針對于信用風(fēng)險的審批流程,就更加的無法在大規(guī)模拓展業(yè)務(wù)的同時保證其較低的壞賬率水平。正是因為各大商業(yè)銀行在這個問題上覺得難以處理,與較大型的企業(yè)相比其風(fēng)險難控,將這部分群體視為高風(fēng)險群體,避而遠(yuǎn)之,才給了小額信貸機(jī)構(gòu)這樣的一個良機(jī),使得小額信貸機(jī)構(gòu)能夠應(yīng)運(yùn)而生。再加上小額信貸單筆金額小的基本特征就決定了其運(yùn)營機(jī)構(gòu)要達(dá)到收益覆蓋成本這一目標(biāo)必須形成規(guī)模,貸款的量必須上去,這樣對于信用風(fēng)險的審核和控制就顯得更加的重要,它是在小額信貸商業(yè)化進(jìn)程中,實現(xiàn)長期可持續(xù)性發(fā)展中迫在眉睫、亟待突破的一項關(guān)鍵任務(wù)。 文章的選題思路來自于實習(xí)的實際工作中發(fā)現(xiàn)小額信貸信用風(fēng)險管理的不足,如信貸員的激勵機(jī)制而引起的過量放貸問題,以及由于信貸員水平的不同造成的判斷標(biāo)準(zhǔn)不統(tǒng)一的問題,和維持相當(dāng)數(shù)量的信貸員而帶來的不必要的業(yè)務(wù)成本問題等。本文從小額信貸以及小額貸款公司的定義入手,結(jié)合國內(nèi)外對小額信貸信用風(fēng)險的研究,嘗試找出影響商業(yè)小額貸款公司客戶信用風(fēng)險的主要因素,并建立相關(guān)預(yù)測模型。 二、研究內(nèi)容 本文共有五章,主要內(nèi)容如下： 第一章是緒論。介紹本文的研究背景及意義,研究內(nèi)容及結(jié)構(gòu)安排,以及本文的創(chuàng)新之處。 第二章是相關(guān)理論和文獻(xiàn)綜述。首先介紹了小額信貸和小額貸款公司的概念、特征等內(nèi)容；其次,闡述了信用風(fēng)險的定義以及評價方法,并在此基礎(chǔ)上,比較了小額貸公司和商業(yè)銀行信用風(fēng)險管理的差異；然后對小額貸款信用風(fēng)險及其影響因素的相關(guān)文獻(xiàn)進(jìn)行了回顧,最后,對以上內(nèi)容進(jìn)行了相應(yīng)的評述,并得到了本文的研究視角。 第三章是研究設(shè)計。包括樣本的設(shè)計,變量的選擇,假設(shè)的提出,研究程序和模型設(shè)計。 第四章是實證分析。采用logit回歸模型,本著全面、有效的原則,搜集了目前國內(nèi)小額信貸市場活躍的參與群體、具有典型代表性的群體——個體工商戶的第一手資料信息,并且從個人自然特征和經(jīng)濟(jì)特征兩大方面去設(shè)計和統(tǒng)計其指標(biāo)、變量,以達(dá)到有效評估的目的。并在logit回歸基礎(chǔ)上,采用在樣本均值水平上計算出邊際影響和計算平均邊際影響(在每一條觀測上計算出邊際影響并取均值)這兩種方法,對商業(yè)小額貸款公司客戶信用風(fēng)險的違約影響因素進(jìn)行了邊際效應(yīng)分析,并建立了較為簡便有效的客戶信用風(fēng)險預(yù)測模型。 第五章是研究結(jié)論及建議。根據(jù)第四章實證分析得出本文研究結(jié)果,并將研究結(jié)果與預(yù)期假設(shè)進(jìn)行對比；然后針對本文研究對象提出相應(yīng)的政策建議與前景展望。最后對本文研究局限性予以說明。 三、本文的主要貢獻(xiàn) 1.研究視角比較新穎 出于保護(hù)客戶貸款信息的隱私以及防止小額貸款公司商業(yè)機(jī)密的泄露,通常很難獲得商業(yè)小額貸款公司客戶的具體資料。因此,國內(nèi)目前的小額貸款研究中,很多是對小額貸款機(jī)構(gòu)的經(jīng)營模式、規(guī)范發(fā)展和可持續(xù)發(fā)展等理論的研究。對于小額貸款信用風(fēng)險的影響因素,主要的研究領(lǐng)域是：以扶貧和發(fā)展農(nóng)村經(jīng)濟(jì)為主要目標(biāo)的農(nóng)戶小額信貸,以及站在商業(yè)銀行等正規(guī)金融機(jī)構(gòu)的立場上,對客戶進(jìn)行風(fēng)險管理。而選擇以盈利為目的的商業(yè)小額貸款公司為視角,進(jìn)行的相關(guān)實證研究還比較少。而本文在合法的基礎(chǔ)上獲取了大量樣本,借鑒其他金融主體對小額信貸違約影響因素研究,以商業(yè)小額貸款公司為放款主體,分析客戶的信用風(fēng)險影響因素,對其進(jìn)行風(fēng)險控制具有一定意義。 此外,本文實證研究的數(shù)據(jù)來源于成都外資小額貸款公司。數(shù)據(jù)的范圍包括了“大成都地區(qū)”,它包括了溫江、彭州、郫縣、新都、龍泉、華陽等成都郊縣,也包含了較大規(guī)模的個體工商戶的零售市場和批發(fā)市場,比如荷花池、雙流家具市場等。因此,研究樣本較多,原始數(shù)據(jù)材料接近100頁。數(shù)據(jù)涵蓋了整個成都地區(qū)融資需求旺盛的個體工商戶群體,由于這個群體具有自己的特點,因此本文是站在以成都為代表的西部地區(qū)角度上對小額貸款公司客戶的信用風(fēng)險進(jìn)行研究。 2.改善商業(yè)小額貸款公司的風(fēng)險管理 引入logit模型進(jìn)行小額貸款信用評價之后,信貸人員可以挑選對逾期行為有顯著影響的因素進(jìn)行重點審查。 由于模型總體預(yù)測能力較高,因此可以通過模型對客戶資料進(jìn)行信用評價,將得出的數(shù)值與預(yù)先設(shè)定的閾值相比較,對客戶進(jìn)行分類,確定是否放貸或者貸款的定價,避免信貸人員因為業(yè)績壓力或以權(quán)謀私而放寬審核條件而做出的錯誤的信貸決定。同時,公平、客觀的預(yù)測模型也避免了因為信貸員水平的參差不齊、主觀情緒變化、關(guān)注角度的不同而導(dǎo)致的信貸決定的不一致,有利于業(yè)務(wù)的統(tǒng)一性和規(guī)范性。 此外,快速有效的信用預(yù)測模型可以減少信貸人員的數(shù)量和工作量,有利于提高工作效率,降低業(yè)務(wù)成本。因此該研究對于改善商業(yè)小額貸款公司的信用風(fēng)險管理具有實踐意義。 3.變量設(shè)計等方面有一定的創(chuàng)新 在變量設(shè)計方面,本文不僅僅使用從業(yè)時間這一變量來衡量客戶在業(yè)內(nèi)的資歷狀況,更創(chuàng)造性的利用管理經(jīng)驗和當(dāng)前地址經(jīng)營年限這兩個變量,對貸款客戶在其行業(yè)領(lǐng)域中的經(jīng)驗、人脈、營運(yùn)能力和穩(wěn)定性進(jìn)行考察。 本文在logit回歸基礎(chǔ)上,采用在樣本均值水平上計算出邊際影響和計算平均邊際影響(在每一觀測水平上計算出邊際影響并取均值)這兩種方法,對商業(yè)小額貸款公司客戶信用風(fēng)險的逾期影響因素進(jìn)行了邊際效應(yīng)分析,并學(xué)習(xí)借鑒對農(nóng)戶小額信貸風(fēng)險管理的研究,建立了信用風(fēng)險識別模型。 不可否認(rèn)的是,由于實證研究所用的樣本數(shù)據(jù)來源于大成都地區(qū)的客戶,存在一定的地域性,且所掌握的材料有限,因此分析過程中的不足,是今后需要進(jìn)一步加強(qiáng)的地方。另外,鑒于作者的能力水平有限,論文中難免出現(xiàn)偏頗之處,敬請各位專家、學(xué)者指正。
[Abstract]:Microcredit (Microcredit) is a special kind of credit service. It specializes in a social group. This social group is very difficult to finance through traditional regular financing channels. Microcredit meets the demand for their daily production and operation by providing small amount and continuous loans to them. It includes individual business, small workshop owners, small owners, micro, small and medium enterprises and middle and low income groups. Microfinance lending institutions in China include rural commercial banks, urban commercial banks, postal savings banks and other regular financial institutions, including professional microfinance companies. This article focuses on the study of similar author Ceng Jingshi. The specialized commercial small loan companies of a foreign small loan company in Chengdu have been established to centrally centralized the private funds and standardize the private lending market. At the same time, it has also effectively solved the problem of financing for individual business households, micro, small and medium enterprises.
Microfinance to meet individual business households, micro, small and medium-sized enterprises, farmers and other small and medium financing demand, standardize private capital lending, increase employment, promote economic development plays a tremendous role in promoting. However, the establishment of small loan companies in China is not long, many problems need to be solved, especially the control of credit risk. From the credit system and risk assessment means, farmers, urban individual industrial and commercial households, and small and medium-sized enterprises have no perfect credit environment, and lack of effective technical means to manage them. From the point of view of operation, many provinces and cities and regions have not formulated specific implementation norms and measures for commercial small loan companies. In addition, the source of funds is limited, the business is single, the loan is lack of collateral and the weakness of the service object, which leads to the vulnerability of the risk resistance of the microfinance companies. Therefore, it is of great significance to explore how to control and avoid the risk of small loans and promote the healthy development of the small loans.
First, the purpose of the study
Because of the low development time and the gradual commercialization of microfinance institutions in China, small credit institutions have begun to operate independently and take their own profits and losses, and strive to explore the goal of achieving sustainable development. However, in this process, there are still some problems to be solved, such as low coverage, difficulty in forming scale, reaching the balance point of profit and loss, and credit body. It is difficult to identify, evaluate and manage credit risk effectively. These problems seriously restrict the development of microfinance business in China. The main reason for these problems is that microcredit institutions are difficult to identify the credit risk level of their target customers effectively. If there is no effective recognition of the credit risk level, the high rate of reimbursement can not be guaranteed. If there is no advanced needle for the credit risk examination and approval process, it is more impossible to guarantee the lower bad debts at the same time in the large-scale expansion of business. It is because the big commercial banks are in this problem. It is difficult to deal with it, and it is difficult to control the risk compared with the larger enterprise. It is a good opportunity to take this part of the group as a high risk group and avoid it. It has given the micro credit institution a good opportunity to make the microcredit institutions come into being. The target of income cover cost must form the scale, the amount of the loan must go up, so it is more important to audit and control the credit risk. It is an urgent task to be breakthroughs in the development of long-term sustainable development in the process of commercialization of micro credit.
The idea of selecting the topic of the article comes from the lack of credit risk management in the practical work of the practice, such as the excessive loan problem caused by the incentive mechanism of the credit clerk, and the disunity of the judgment standards caused by the different levels of the credit officers, and the unnecessary business of maintaining a considerable number of credit officers. Starting with the definition of microfinance and microfinance companies, this paper tries to find out the main factors that affect the credit risk of commercial microfinance companies and establish a related prediction model.
Two, research content
There are five chapters in this paper. The main contents are as follows:
The first chapter is an introduction. It introduces the background and significance of the study, the contents and structure of the research, as well as the innovation of this paper.
The second chapter is related theory and literature review. First, it introduces the concept and characteristics of microfinance and microfinance companies. Secondly, it expounds the definition and evaluation method of credit risk. On this basis, it compares the differences of credit risk management between microfinance companies and commercial banks. Then, the credit risk of microfinance and the credit risk of microfinance are compared. The relevant literature on influencing factors is reviewed, and finally, the above contents are commented accordingly, and the research perspective of this paper is obtained.
The third chapter is research design, including sample design, variable selection, hypothetical proposition, research procedure and model design.
The fourth chapter is an empirical analysis. By using the logit regression model, in accordance with the comprehensive and effective principles, we have collected the active participation groups in the domestic microcredit market, which have typical representative groups, the first hand information of individual business households, and design and statistics their indicators from two aspects of individual natural characteristics and economic characteristics. On the basis of logit regression, two methods are used to calculate the marginal effect and calculate the average marginal effect on the average level of the sample (the marginal effect of each observation and take the mean value) on the basis of the mean level of the sample. The marginal effect of the factors of default on the customer credit risk of the commercial microfinance company is made. It is necessary to analyze and establish a simple and effective prediction model of customer credit risk.
The fifth chapter is the conclusion and suggestion of the study. According to the empirical analysis of the fourth chapter, the results of this study are obtained, and the results are compared with the expected hypothesis; then the corresponding policy suggestions and prospects are put forward. Finally, the limitations of this paper are explained.
Three, the main contribution of this article
1. the perspective of research is new
In order to protect the privacy of customer loan information and prevent the disclosure of commercial secrets of microfinance companies, it is often difficult to obtain specific data from commercial microfinance companies. Therefore, many of the domestic microfinance research is the research on the management model, standard development and sustainable development of microfinance institutions. The main research fields are: microfinance of farmers with the main goal of poverty alleviation and development of rural economy, and the risk management of customers on the standpoint of commercial banks and other regular financial institutions. The empirical study is still relatively small, and this article has obtained a large number of samples on the basis of legal basis, drawing on the influence factors of other financial entities on microfinance default, taking commercial microfinance companies as the main body of lending, analyzing the factors affecting the credit risk of customers, and having certain significance for the risk control.
In addition, the data of this empirical study came from the Chengdu foreign capital microfinance company. The data range includes the "big Chengdu area". It includes Wenjiang, Pengzhou, Pixian, Xindu, Longquan, Hua Yang and other Chengdu suburbs. It also includes a large scale of individual business households, such as the zero sale market and wholesale market, such as Lotus Pond, double flow furniture market, etc. Therefore, the research sample is more, the original data material is close to 100 pages. The data covers the individual industrial and commercial households with high financing demand in Chengdu area. Because the group has its own characteristics, this paper is to study the credit risk of the small loan company customers in the perspective of the western region represented by Chengdu.
2. improving the risk management of commercial microfinance companies
After introducing the logit model to the credit evaluation of small loans, the credit officers can select key factors that have significant impact on overdue behavior.
As a result of the high overall prediction ability, the model can be used to evaluate the customer data through a model, to compare the value to the predetermined threshold, to classify the customers, to determine whether the loan or loan is priced, and to avoid the mistakes made by the credit personnel because of the pressure of performance or the relaxation of the audit conditions. At the same time, the fair, objective prediction model also avoids the inconsistency of credit decisions because of the uneven level of the credit officers, the change of subjective emotions, and the different angles of concern, which is beneficial to the unity and standardization of business.
In addition, a fast and effective credit prediction model can reduce the number and workload of credit personnel, improve work efficiency and reduce business costs. Therefore, this study is of practical significance to improve the credit risk management of commercial microfinance companies.
There are some innovations in the design of 3. variables.
In terms of variable design, this paper not only uses the variable of working time to measure the customer's seniority in the industry, more creative use of management experience and the current address of the two variables, to examine the experience, human connections, operational power and stability of the loan clients in their industry.
On the basis of logit regression, the two methods are used to calculate the marginal effect and calculate the average marginal influence on the average level of the sample (the marginal effect of each observation level and take the mean value). The marginal effect of the customer credit risk in the commercial microfinance company is analyzed, and the study is used for reference to the farmers. Credit risk identification model is established based on the research of micro credit risk management.
It is undeniable that, because the sample data used in the empirical study originates from the customers in the great Chengdu region, there is a certain regional and limited material, so the shortage in the analysis process is the place to be further strengthened in the future. In addition, in view of the limited ability of the author, it is unavoidable to be biased in the paper. Experts and scholars have corrected them.
【學(xué)位授予單位】：西南財經(jīng)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F832.4

【參考文獻(xiàn)】

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1 馬文勤;孔榮;楊秀珍;;農(nóng)戶小額信貸信用風(fēng)險評估模型構(gòu)建[J];財會月刊;2009年36期

2 杜曉山,孫若梅;中國小額信貸的實踐和政策思考[J];財貿(mào)經(jīng)濟(jì);2000年07期

3 黎月紅;徐藝心;;我國小企業(yè)貸款應(yīng)用信用評分技術(shù)的研究[J];區(qū)域金融研究;2010年12期

4 申韜;;基于軟集合的小額貸款公司信用風(fēng)險評估[J];南方金融;2010年08期

5 曾之明;;后危機(jī)時代小額信貸信用風(fēng)險優(yōu)化管理探討[J];征信;2010年02期

6 劉澤雙;王廣宇;段曉亮;;小額貸款風(fēng)險影響因素的關(guān)系結(jié)構(gòu)分析[J];海南金融;2009年02期

7 李萌;Logit模型在商業(yè)銀行信用風(fēng)險評估中的應(yīng)用研究[J];管理科學(xué);2005年02期

8 杜曉山;中國農(nóng)村小額信貸的實踐嘗試[J];現(xiàn)代經(jīng)濟(jì)探討;2004年02期

9 朱欣樂;;農(nóng)村小額信用貸款的風(fēng)險管理研究[J];經(jīng)濟(jì)縱橫;2010年12期

10 李文政;唐羽;;國內(nèi)外小額信貸理論與實踐研究綜述[J];金融經(jīng)濟(jì);2008年16期

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