本文選題：商業(yè)銀行 + 信用風(fēng)險(xiǎn)　； 參考：《南京工業(yè)大學(xué)》2012年碩士論文

【摘要】：商業(yè)銀行是金融交易的主要中介，關(guān)系著整個(gè)國(guó)民經(jīng)濟(jì)能否順暢運(yùn)行。目前，中國(guó)的商業(yè)銀行尚處于轉(zhuǎn)軌和新興發(fā)展階段，積聚了大量的信用風(fēng)險(xiǎn)。雖然近年來(lái)中國(guó)商業(yè)銀行采取了多種措施使得不良貸款率有所降低，但是2009年以來(lái)，貸款規(guī)模迅速擴(kuò)張，損失準(zhǔn)備不足，信用風(fēng)險(xiǎn)仍是商業(yè)銀行目前面臨的主要風(fēng)險(xiǎn)之一，因此提高商業(yè)銀行信用風(fēng)險(xiǎn)管理水平已經(jīng)成為銀行業(yè)面臨的重要課題。 本文在總結(jié)前人研究的基礎(chǔ)上，首先根據(jù)2005-2010年銀行業(yè)相關(guān)數(shù)據(jù)，采用縱向比較的方法簡(jiǎn)析了目前我國(guó)商業(yè)銀行信用風(fēng)險(xiǎn)現(xiàn)狀，其次分別利用信號(hào)博弈和重復(fù)博弈的方法建立商業(yè)銀行信用風(fēng)險(xiǎn)管理博弈方程，定性地分析了企業(yè)簽約前的逆向選擇行為和簽約后的道德風(fēng)險(xiǎn)行為給銀行帶來(lái)的信用風(fēng)險(xiǎn)，然后以蘇州市25家上市公司的股票數(shù)據(jù)和財(cái)務(wù)數(shù)據(jù)為基礎(chǔ)，通過(guò)KMV模型定量地預(yù)測(cè)博弈方程其中的一個(gè)關(guān)鍵要素：企業(yè)的預(yù)期違約概率，最后有針對(duì)性地提出完善商業(yè)銀行信用風(fēng)險(xiǎn)管理的對(duì)策。 論文研究發(fā)現(xiàn)，，由于貸款規(guī)模迅速擴(kuò)張、貸款分布行業(yè)過(guò)度集中以及資本充足率存在下滑趨勢(shì)，導(dǎo)致商業(yè)銀行信用風(fēng)險(xiǎn)高居不下，運(yùn)用論文建立的博弈模型分析得出影響其信用風(fēng)險(xiǎn)管理水平的具體因素：企業(yè)經(jīng)營(yíng)報(bào)告的掩飾成本、企業(yè)的違約概率和博弈雙方（銀行和企業(yè)）對(duì)下次交易的可能性的預(yù)期因子�；谏鲜鲅芯拷Y(jié)論，本文從完善銀行內(nèi)部信用風(fēng)險(xiǎn)管理體系，增強(qiáng)企業(yè)內(nèi)部信用建立和維持機(jī)制和提高外部監(jiān)管機(jī)構(gòu)的監(jiān)管效率三個(gè)方面提出了一系列提高商業(yè)銀行信用風(fēng)險(xiǎn)管理水平的對(duì)策。
[Abstract]:Commercial bank is the main intermediary of financial transaction, which is related to the smooth operation of the whole national economy. At present, China's commercial banks are still in the transition and emerging stage of development, accumulated a large number of credit risks. Although China's commercial banks have taken various measures in recent years to reduce the ratio of non-performing loans, since 2009, the scale of loans has expanded rapidly, and losses have not been prepared enough. Credit risk is still one of the main risks faced by commercial banks at present. Therefore, improving the level of credit risk management of commercial banks has become an important issue facing the banking industry. On the basis of summarizing the previous studies, this paper firstly analyzes the present situation of credit risk of commercial banks in China by means of longitudinal comparison according to the relevant data of banking from 2005 to 2010. Secondly, the paper establishes the credit risk management game equation of commercial bank by the methods of signal game and repeated game, and qualitatively analyzes the adverse selection behavior before the contract and the credit risk brought by the moral hazard behavior after the contract. Then, based on the stock data and financial data of 25 listed companies in Suzhou, the paper quantitatively predicts one of the key elements of the game equation by KMV model: the expected default probability of the enterprise. Finally, the paper puts forward the countermeasures to perfect the credit risk management of commercial banks. The paper finds that due to the rapid expansion of loan scale, the excessive concentration of loan distribution industry and the downward trend of capital adequacy ratio, commercial banks have high credit risk. By using the game model established in the paper, the author concludes that the specific factors that affect the level of credit risk management are: the cost of covering up the business report, The probability of default of the firm and the expected factors of the parties (banks and firms) to the possibility of the next transaction. Based on the above conclusions, this paper improves the internal credit risk management system of banks. This paper puts forward a series of countermeasures to improve the level of credit risk management of commercial banks from three aspects: strengthening the internal credit establishment and maintenance mechanism and improving the supervision efficiency of external regulatory bodies.
【學(xué)位授予單位】：南京工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F832.33;F224.32

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