本文選題：操作風險 + 收入模型　； 參考：《西南財經(jīng)大學》2013年碩士論文

【摘要】：操作風險是一項自銀行開展經(jīng)營活動以來就存在的古老風險,但長期都沒有以一種獨立存在的風險形式納入銀行風險管理體系中。20世紀90年代以來,隨著金融深化的逐漸演進銀行規(guī)模越來越大,業(yè)務日趨繁雜,操作風險帶來的危害愈發(fā)彰顯。操作風險案例頻頻暴發(fā)給銀行業(yè)帶來了重大的資金損失和信譽危機,至此人們才意識到對操作風險進行有效監(jiān)管的重要性。在此背景下巴塞爾銀行監(jiān)管委員會積極應對操作風險的研究和監(jiān)管,2004年6月,巴塞爾委員會公布了新協(xié)議定稿“資本計量和資本標準的國際協(xié)議：修訂框架”。新協(xié)議首次提出操作風險資本金的計算方法,并出臺更先進、更貼近市場的監(jiān)管條例督促銀行增強操作風險的管理措施。新協(xié)議一出臺,全球商業(yè)銀行開始有意識地從各個經(jīng)營環(huán)節(jié)改善對操作風險的管控措施,如實施強有力的內部控制制度：建立獨立、專用的操作風險管理后臺部門；制定全行統(tǒng)一的操作風險的戰(zhàn)略部署；傾入人力、物力開發(fā)實際可用的操作風險管理工具和度量模型、加強操作風險文檔建設、建立內部損失數(shù)據(jù)庫等。國際上一系列的舉措讓操作風險的研究和監(jiān)管得到了快速的發(fā)展。 相比之下國內商業(yè)銀行在操作風險管理研究方面起步比較晚,甚至至今都沒有有效的操作風險度量模型,也沒有充足完備的操作風險內部損失數(shù)據(jù)庫。由于金融行業(yè)發(fā)展歷史不長,市場化程度不夠,信息存在短缺,國外較精準的計量操作風險的模型并不能直接移植�，F(xiàn)階段國內學者的研究更多的只停留在對《新巴塞爾協(xié)議》操作風險管理框架的介紹,并沿用已有的模型對我國商業(yè)銀行做實證分析,還沒有涉及太多基于中國實際情況的操作風險度量模型和框架的開發(fā)。 從國內宏觀經(jīng)濟環(huán)境分析操作風險的現(xiàn)狀特征及其計量管理的存在的障礙。現(xiàn)階段我國商業(yè)銀行正處在轉型時期,很多必備的機制都在查漏補缺之中。人員道德問題和信息披露不精確、技術滯后、電子化運作漏洞、制度建設和系統(tǒng)流程管理實施不善等統(tǒng)統(tǒng)都導致了操作風險成為威脅我國銀行業(yè)健壯發(fā)展的最大隱患。另外在操作風險量化管理方面也障礙重重,首先面臨的問題是量化管理操作風險的意識薄弱,即銀行業(yè)根本就沒有利用建立內部數(shù)據(jù)庫累積損失文檔的方式對操作風險進行電子化的管理的經(jīng)驗。其次由于我國商業(yè)銀行傳統(tǒng)的產權歸屬和信息披露不透明的原因,內部數(shù)據(jù)的收集是相當大的難題。而根據(jù)新協(xié)議的規(guī)定利用高級的、精確的操作風險回歸模型或計量方法的前提是有必要的充足的內部數(shù)據(jù)做基礎,數(shù)據(jù)的匱乏意味著對操作風險的量化只能采取最老套、原始的方式。由此得到的數(shù)據(jù)不精準,不能以此為據(jù)計提相應的經(jīng)濟資本,而沒有計提操作風險損失準備金作為抗擊風險的保證操作風險監(jiān)管始終不能有效到位,而低效無保障的管理又會進一步加劇操作風險的潛在隱患,如此一來形成一個監(jiān)控紕漏的惡性循環(huán),操作風險帶來的沖擊將愈演愈烈。再次,由于中國商業(yè)銀行實行行長負責制,稽核部門根本不能與決策部門抗衡,換句話說國內銀行業(yè)實行的行長責任制將權利過多賦予內部高層,稽核審計部門不能獨立地完成對全行整體業(yè)務和風險管理評審的工作,因而其搜集的操作風險監(jiān)管一手資料存在信息不全或者信息偏頗的問題,后續(xù)的量化過程根部無從做起。 鑒于操作風險的度量環(huán)境不佳、內部數(shù)據(jù)不充足的情況,筆者只能借“由上至下”的收入模型對國內操作風險做試探性的研究。收入模型的基本思路是以目標銀行的凈利潤為應變量,凈利潤的波動性代表銀行面臨的總風險,把波動能夠被度量的部分視為有信用風險和市場風險引起,而其不能被度量的部分則是由操作風險導致的。具體的步驟是先確定度量各類風險大小的解釋變量,包括代表市場波動、監(jiān)管部門的約束、放貸企業(yè)的還款能力、銀行自身的經(jīng)營情況的指標,然后基于目標變量建立模型,反應出各種風險指標和凈利潤的關系。計算目標變量的方差,將方差中能被度量的部分看做是信用風險和市場風險的大小,而不能被度量的部分則解釋成操作風險的大小。建模之初筆者選擇了真實GDP增速、上證綜指、法定存款準備金率等七個指標代表市場風險和信用風險,并且將10家國有商業(yè)銀行從2009年第一季度至2012年第三季度的財務數(shù)據(jù)做樣本分別進行時間序列模型回歸,經(jīng)過層層篩選最終得到了以上證綜指、不良貸款率、存貸比率為解釋變量的模型以及九家商業(yè)銀行各自的操作風險占比和損失金額,為其下一步計提操作風險資本金作一個參考。為了進一步說明問題筆者做了更深入的計量研究,將國有銀行和股份制銀行的數(shù)據(jù)分別建立時間序列模型,得到的結果是國有銀行的操作風險占總風險的比例約是股份制銀行操作風險總占比的兩倍,說明股份制銀行治理結構和內控管理有更高的效率,原因在于股份制銀行的營業(yè)網(wǎng)點和員工數(shù)量較少,管理者能夠更容易地對日常運營中的各個環(huán)節(jié)實施監(jiān)控。而國有銀行由于資產規(guī)模大,存在產權結構、信息系統(tǒng)、內控機制等各方面的缺漏,而且基于中國的特色國有銀行存在政府強制干預,其獨立性不足,加之因經(jīng)營時間較長,網(wǎng)店分布較廣,報告監(jiān)管等滯后,管理效率相比更低,操作風險占比自然更大。實證結果與第二章國內銀行業(yè)操作風險現(xiàn)狀尤其是國有商業(yè)銀行存在的問題描述是一致的,基于此國有商業(yè)銀行應該加快制度改革步伐、改善產權結構和激勵約束機制、強化信息透明度和系統(tǒng)配備、轉變攬儲為立行之本的經(jīng)營方式加大發(fā)展中間業(yè)務的力度分散操作風險,積極推進風險管理制度改革。 本文的框架： 第一章,緒論。該部分首先介紹隨著全球商業(yè)銀行操作風險損失事件的頻繁發(fā)生,有必要設計一套可靠的操作風險度量模型、實施量化管理。然后概述了本文的研究思路和行文脈絡。最后對國內外與本文研究主題相關的文獻進行了回顧。 第二章,操作風險的概念介紹。該部分首先描述了操作風險的定義、分類和研究現(xiàn)狀。然后介紹了國內銀行操作風險管理的現(xiàn)狀,并指出了度量操作風險時遇到的障礙。 第三章,操作風險的度量方法及模型介紹。該部分詳細介紹了各種操作風險的定量模型,對國際上商業(yè)銀行的定量研究成果進行綜述。 第四章,操作風險的實證分析。該部分是本文的核心,利用收入法對我國上市商業(yè)銀行操作風險進行實證研究,根據(jù)10家上市銀行的數(shù)據(jù)做回歸分析求出操作風險占的占比和涉及的損失金額,并對回歸結果加以驗證和說明。 第五章,針對國內操作風險現(xiàn)狀和實證回歸結合管理建議。介紹一些有利于我國商業(yè)銀行實現(xiàn)操作風險量化管理的政策建議。 本文的創(chuàng)新之處在于試圖尋找出最能反應我國商業(yè)銀行操作風險現(xiàn)狀的數(shù)據(jù)和模型,為了使結果公正和客觀,筆者盡最大努力保證原始數(shù)據(jù)的充分,樣本要夠大,本文選擇了10家上市銀行15個季度的數(shù)據(jù)作為研究對象。考慮到不同銀行的操作風險的特殊性,并且為了保證模型和估計結果的準確度和可靠性,筆者建立了屬于各家銀行的時間序列模型,通過模型的多次修改和數(shù)據(jù)的回歸篩選最后選取了上證綜指、存貸比、不良貸款率這三個指標,并在統(tǒng)一的模型下求出九家各自的操作風險估計值,為下一步銀行計提操作風險準備金提供依據(jù)。此外,筆者還沿用此模型將股份制銀行和國有銀行分別進行實證分析,對比兩類銀行的回歸結果提出我國操作風險的管理對策。 本文的不足在于收集到的都是公開的財務報表數(shù)據(jù),不能反映銀行所有的經(jīng)營信息。再加上數(shù)量模型本身不可能絕對精確地解釋現(xiàn)實經(jīng)濟狀況。因此計量結果會跟銀行的實際情況有出入。除此之外操作風險的量化值被收入模型定義為引起凈利潤波動的因素中排除市場和信用風險剩下的部分,顯得太過絕對了,與現(xiàn)實情況存在一定的差距,最后得到的估計結果也只是一個大概的取值并不精確,不能直接為銀行提供計提操作風險損失準備金的依據(jù)。事實上巴塞爾委員會的要求,衡量操作風險首先應該收集銀行內部的數(shù)據(jù)資料,然后評估風險事件的發(fā)生概率和預期損失,而收入模型忽略了銀行的內部經(jīng)營情況,也沒有利用風險事件的發(fā)生概率和預期損失計算操作風險所需配置的資本,僅僅從外部數(shù)據(jù)估計處了操作風險的大致占比和涉及的損失金額。未來,我國商業(yè)銀行應當同時利用“由上至下”和“由下至上”的方式對操作風險實施量化管理,前提是要得到更符合實際的結果還需要數(shù)據(jù)的大范疇收納和結合中國銀行業(yè)的切實考察,這是筆者下一步的努力方向。
[Abstract]:Operational risk is an ancient risk since the bank has carried out its business activities, but it has not been incorporated into the bank risk management system in the form of an independent risk for a long time since the 90s.20 century. With the gradual evolution of the financial deepening, the scale of the bank has become increasingly large, the business is increasingly complex, and the harm caused by operational risk is more and more serious. The frequent outbreaks of operational risk cases have brought great financial loss and credit crisis to the banking industry. At this point, people have realized the importance of effective supervision of operational risks. In this context, the Basel Banking Regulatory Commission actively deals with the research and supervision of operational risks. In June 2004, the Basel committee published a new report. The agreement finalized the international agreement on capital measurement and capital standards: the revised framework. The new agreement first proposed the calculation method of operating risk capital, and introduced more advanced, closer to the market regulatory regulations to urge banks to strengthen operational risk management measures. The new agreement was introduced, and the global commercial banks began to operate consciously from each operation. Steps to improve control measures for operational risks, such as implementing strong internal control systems: establishing independent, dedicated operational risk management backstage departments; formulating a strategic deployment of operational risk throughout the whole line; leaning into manpower, material resources to develop practical operational risk management tools and measurement models, and strengthening operational risk documents. Set up an internal loss database and so on. A series of international initiatives have made rapid development of operational risk research and regulation.
In contrast, the domestic commercial banks have a relatively late start in the study of operational risk management, and even now there are no effective operational risk measurement models, and there is not enough complete operational risk internal loss database. Because the history of the development of the financial industry is not long, the degree of marketization is not enough, the information is short, and the foreign more accurate measurement exercises. The model of risk making can not be transplanted directly. At present, more research of domestic scholars is only on the introduction of the framework of the operation risk management of the new Basel agreement and the empirical analysis of the commercial banks in China along with the existing models, and there are not too many operational risk measurement models and frameworks based on the actual situation in China.
From the domestic macro economic environment, the current characteristics of operational risk and the obstacles of measurement management are analyzed. At the present stage, the commercial banks in China are in the period of transition, and many necessary mechanisms are in the missing and missing. The problems of personnel ethics and information disclosure are inaccurate, technology lag, electronic operation loopholes, system construction and system process. The problem of operational risk has become the biggest threat to the robust development of China's banking industry. In addition, there are many obstacles in the quantitative management of operational risk. The first problem is that the awareness of the operational risk of quantitative management is weak. That is, the banking industry has not made use of the accumulated loss documents of the internal database. The collection of internal data is a considerable problem. The premise of using advanced, accurate operation risk regression model or measurement method is necessary according to the regulations of the new agreement. As the basis of adequate internal data, the lack of data means that the quantification of operational risk can only be used in the most old-fashioned, original way. The resulting data is not accurate, and the corresponding economic capital can not be taken as the basis for the operation of the risk. In place, the low efficiency and unguaranteed management will further exacerbate the potential risks of operational risk, so as to form a vicious cycle of monitoring errors, the impact of operational risk will be intensified. Again, because the Bank of China is responsible for the system, the audit department can not compete with the decision-making department at all, in other words domestic The executive responsibility system implemented by the banking industry gives excessive rights to the internal high-level, and the audit audit department can not perform the work on the overall business and risk management review independently. Therefore, there is a problem of incomplete information or biased information on the first-hand data of operational risk supervision, and the root of the follow-up quantitative process can not be done.
In view of the poor measurement environment of operational risk and insufficient internal data, the author can only use the "from top to bottom" income model to study the operational risk in China. The basic idea of the income model is that the net profit of the target bank is the corresponding variable, the wave of net profit represents the total risk that the bank faces, and the fluctuation can be used. The part that is measured is caused by credit risk and market risk, and the part that can not be measured is caused by operational risk. The specific step is to determine the explanatory variables that measure the size of all kinds of risks, including the market volatility, the regulatory authority, the repayment ability of the lending enterprises, and the management of the banks themselves. And then the model is built based on the target variable, and the relationship between the risk index and the net profit is reflected. The variance of the target variable is calculated. The part of the variance can be measured as the size of the credit risk and the market risk, but the part that can not be measured is interpreted as the size of the operation style risk. Speed, Shanghai Composite Index, legal deposit reserve ratio and other seven indicators represent market risk and credit risk, and 10 state-owned commercial banks from the first quarter of 2009 to the third quarter of the third quarter of the financial data to do the time series model regression model, after layers of screening finally got the above index, the rate of non-performing loans, deposit and loan. The ratio is the model of the explanatory variable and the respective operational risk ratio and the loss amount of the nine commercial banks. For the next step, we make a reference for the operation of the venture capital. In order to further explain the problem, the author made a more in-depth measurement and study, and established the time series model of the data of the state-owned banks and the joint-stock bank respectively. The result is that the proportion of the operational risk of the state-owned banks is about two times the total operational risk of the joint-stock banks, which indicates that the governance structure and internal control management of the joint-stock banks have higher efficiency. The reason is that the business outlets and the number of employees in the joint-stock banks are less, and the managers can more easily to each of the daily operations. Because of the large scale of the assets, the state-owned banks have the lack of property right structure, information system, internal control mechanism and so on. Moreover, the state owned banks have the government compulsory intervention based on the Chinese characteristic, and their independence is insufficient. In addition, because of the long operation time, the network stores are distributed widely, the report supervision is lagging behind, and the management efficiency is lower, The operational risk is greater than that of nature. The empirical results are consistent with the current situation of the operational risk of domestic banks in the second chapter, especially the existing problems of state-owned commercial banks. Based on this, the state-owned commercial banks should accelerate the pace of system reform, improve the structure of property rights and incentive and restraint mechanisms, strengthen the transparency and system of information, and change the storage of the banks. The way of running this business is to increase the intensity of developing intermediate business and decentralization of operational risks and actively promote the reform of risk management system.
The framework of this article:
The first chapter, introduction. This section first introduces the frequent occurrence of operational risk loss events in the global commercial banks. It is necessary to design a reliable operational risk measurement model and implement quantitative management. Then it summarizes the research ideas and lines of research in this paper. Finally, it reviews the literature related to the subject of this paper at home and abroad.
The second chapter introduces the concept of operational risk. This section first describes the definition, classification and research status of operational risk, then introduces the current situation of operational risk management in domestic banks, and points out obstacles encountered in measuring operational risk.
The third chapter is the measurement and model introduction of operational risk. This section introduces the quantitative model of various operational risks in detail, and summarizes the quantitative research results of commercial banks in the world.
The fourth chapter is the empirical analysis of operational risk. This part is the core of this article. Using the income method, the operational risk of the listed commercial banks in China is empirically studied. According to the data of 10 listed banks, the proportion of operational risk and the amount involved are calculated, and the results of the regression are verified and explained.
The fifth chapter, in view of the domestic operational risk status and empirical regression combined with management suggestions, introduces some policy suggestions for commercial banks to achieve quantitative management of operational risk in China.
In order to make the result fair and objective, the author tries to make the best effort to ensure the full and large data of the original data, and the sample should be large enough. This paper chooses 15 quarterly data of 10 listed banks as the research object. In order to ensure the accuracy and reliability of the model and the estimated results, the author set up a time series model which belongs to all the banks, and finally selected the three indexes of the Shanghai Composite Index, the loan ratio and the bad loan rate through the multiple modification of the model and the regression screening of the data. The nine respective operational risk estimates provide the basis for the next bank to raise the operational risk reserve. In addition, the author also uses this model to carry out an empirical analysis of the joint-stock banks and the state-owned banks respectively, and compares the regression results of the two types of banks to put forward the management countermeasures of operational risk in China.
The shortage of this article is that all the collected financial statements are collected and do not reflect all the operating information of the bank. And the quantitative model itself can not explain the real economic situation absolutely. Therefore, the measurement results will be different from the actual situation of the bank. The factors that cause the net profit fluctuation to exclude the remaining part of the market and credit risk appear too absolute, and there is a certain gap with the reality. The final results are only an inaccurate estimate of the value, which can not provide the basis for the bank to provide the financial loss reserve. In fact, the Basel committee member is in fact. In order to measure operational risk, it should first collect data from the bank, then evaluate the probability and expected loss of the risk events, and the income model ignores the internal operation of the bank, and does not use the capital to calculate the operational risk of the occurrence probability and expected loss of the risk events, only from the external number. It is estimated that the general proportion of operational risk and the amount of losses involved. In the future, the commercial banks of China should use the "from top to bottom" and "from the bottom to the highest" to implement quantitative management of operational risk. The premise is to get more conforming to the actual results and need the large category of data to receive and combine the Chinese banking sector. In fact, this is the next step of the author's efforts.
【學位授予單位】：西南財經(jīng)大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F832.33

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