本文關(guān)鍵詞：信用卡信用評分模型與最優(yōu)臨界策略研究　出處：《復(fù)旦大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 信用卡 信用評分模型 臨界值 客戶拓展戰(zhàn)略 風(fēng)險調(diào)整后的資本回報率

【摘要】：近些年來,我國銀行卡業(yè)務(wù)一直處于高速發(fā)展期,據(jù)中國人民銀行報告,國內(nèi)信用卡發(fā)卡量在2012年第二季度已經(jīng)突破3億張門檻,截至第四季度末,總信用卡發(fā)卡量已達到3131億張。我們可以看到,商業(yè)銀行為獲取信用卡帶來的高額利潤,不斷通過各種營銷手段擴大市場份額,但同時潛在的壞賬風(fēng)險也隨之而來。 信用評分模型技術(shù)的發(fā)展和應(yīng)用,為商業(yè)銀行進行消費信貸風(fēng)險管理,提供了非常有效的決策依據(jù),銀行依據(jù)信用評分模型可以客觀、全面、準(zhǔn)確地評估消費者的還款能力和還款意愿,以此來控制潛在壞賬損失,進行風(fēng)險管理。根據(jù)信用評分模型,銀行可以計算出每一位申請者的信用評分,而此信用評分就代表該申請者的風(fēng)險程度大小,銀行根據(jù)自身所能承受的風(fēng)險和其經(jīng)營管理目標(biāo)來制定拓展客戶的策略。通常,銀行會為信用評分設(shè)置一個標(biāo)準(zhǔn)分?jǐn)?shù),通常我們稱之為臨界值(cutoff score),信用評分在臨界值之上的客戶的申請會被接受,而信用評分低于臨界值的客戶的申請會被拒絕。臨界值的設(shè)定,將直接影響信用卡客戶的批準(zhǔn)比例、壞賬率和給銀行帶來的利潤。在巴塞爾協(xié)議框架下,銀行如何設(shè)置最優(yōu)的臨界值,為合理分配好信貸資本實現(xiàn)中長期經(jīng)營目標(biāo),并控制好利潤,壞賬以及批準(zhǔn)率等之間的關(guān)系,已成為信貸風(fēng)險管理生命周期中,商業(yè)銀行制定客戶拓展戰(zhàn)略的核心。 學(xué)術(shù)界,有很多的理論研究都側(cè)重于信用評分模型的開發(fā),但是對如何設(shè)置適當(dāng)?shù)男庞迷u分臨界分?jǐn)?shù),制定最優(yōu)的拓展客戶戰(zhàn)略方面的研究卻并不多。對制定戰(zhàn)略方面在學(xué)術(shù)界缺乏重視的主要原因主要還是研究者偏向于對信用評分技術(shù)以及決策模型方法等進行持續(xù)的更深層次的探索,因為他們相信這樣可以不斷提高信用評分模型的辨別和決策能力。但是,對經(jīng)營實踐者例如銀行來說,在操作層面如何有效地利用信用評分工具,制定最優(yōu)的臨界值策略也是一樣的非常重要。 國內(nèi)外歷史文獻中關(guān)于信用卡信用評分模型最優(yōu)臨界策略的研究重點,主要都是放在信貸成本,盈虧目標(biāo),壞賬率或批準(zhǔn)比例分析上,而忽視了巴塞爾協(xié)議下銀行面臨的資本約束和資本配置問題。本論文通過實證分析比較了設(shè)置最優(yōu)臨界值策略的幾種不同方法,進而提出銀行在巴塞爾協(xié)議框架下,進行信貸業(yè)務(wù)風(fēng)險管理,要確定風(fēng)險調(diào)整后的資本回報率(RAROC),以此來衡量銀行風(fēng)險收益績效,銀行在設(shè)置信用評分臨界值來實現(xiàn)拓展客戶戰(zhàn)略時,不僅僅要考慮壞賬損失,利潤及市場份額,更應(yīng)把風(fēng)險調(diào)整后的資本回報率作為主要衡量指標(biāo)來做最后決策。
[Abstract]:In recent years, China's bank card business has been in a period of rapid development, according to the people's Bank of China report, the number of domestic credit card issued in in the second quarter of 2012 has exceeded 300 million threshold, up to the end of 4th quarters. The total number of credit cards issued has reached 313.1 billion. We can see that commercial banks continue to expand their market share through various marketing means in order to obtain the high profits brought by credit cards. But at the same time, the potential risk of bad debts also followed. The development and application of credit scoring model technology provides a very effective decision basis for commercial banks to manage consumer credit risk. Banks can objectively and comprehensively according to the credit scoring model. Accurately assess consumers' ability and willingness to repay to control potential bad debt losses and manage risk. According to the credit rating model, banks can calculate the credit score of each applicant. And this credit score represents the applicant's level of risk, and banks develop customer outreach strategies based on the risks they can take and their management objectives. The bank sets a standard score for the credit score, usually called the threshold value cutoff score, and customers whose credit scores are above the threshold are accepted. Customers whose credit score is below the threshold will be rejected. The setting of the threshold will directly affect the approval ratio of credit card customers, the bad debt rate and the profits to banks. How to set the optimal critical value for the rational allocation of credit capital to achieve the medium- and long-term business objectives, and to control the relationship between profits, bad debts and approval rate, has become the life cycle of credit risk management. The core of the development of customer expansion strategy by commercial banks. In academia, there are many theoretical studies focused on the development of credit scoring model, but how to set the appropriate critical credit score. The main reason for the lack of attention to the development of strategy in academic circles is that researchers prefer credit scoring techniques and decision model methods. A deeper exploration. Because they believe this will improve the ability to identify and make decisions on credit scoring models. However, for business practitioners such as banks, how can credit scoring tools be used effectively at the operational level. It is equally important to develop an optimal critical value strategy. Domestic and foreign historical literature on credit card credit rating model optimal critical strategy research emphasis, mainly on the credit cost, profit and loss targets, bad debt ratio or approval ratio analysis. The capital constraints and capital allocation problems faced by banks under the Basel Accord are ignored. This paper compares several different methods of setting the optimal critical value strategy through empirical analysis. Furthermore, it is proposed that banks should manage the risk of credit business under the framework of Basel Accord, and determine the return on capital after risk adjustment, so as to measure the risk return performance of banks. Banks should not only consider the loss of bad debts, profits and market share when setting credit rating threshold to achieve customer expansion strategy. Risk-adjusted rate of return on capital should be taken as the main measure to make final decision.
【學(xué)位授予單位】：復(fù)旦大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F832.2

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