外文翻譯--基于灰色關(guān)聯(lián)分析商業(yè)銀行信貸風(fēng)險(xiǎn)管理(存儲(chǔ)版)
【正文】 has summarized credit risk assessment theory and put forward relevant theoretical basis and basic practices. These models and methods are mostly used to measure the size of the risk and then conclude the form of the asset portfolio to avoid or reduce the occurrence of credit risk. On considering concrete influent factors, the amount of research done is low. Fang and Zeng (2021) have built the credit risk evaluation function using multivariate statistical methods on the borrowing enterprise39。s influence to the mercial bank credit risk will be demonstrated from the angle of the grey system 毆顯泉纏敢恍欹胙韻僦伐炙狴 In the risk control system, from the angle of industry, the industry risk factors can be determined according to grey correlation degree of different industries factors and bad assets loans which shown below: Equation 14 According to the industry risk factors of different industries, the deviation between actual risk and the expected risk can be set as: Equation 15 According to formula (10), the greater the industry correlation is, the smaller the risk deviation is. In the real lending process, the greater the influence of the industry with the credit risk is, the greater attention of the management department should be. The repayment ability is needed to be noted specially. Under the control of risk, the industry with big correlation relatively has a small risk range which is also in accord with the actual 犏氣郊霏詘仟疼鋱參遼光 憋繞 Therefore, according to the judgment of credit risk at the industry angle, the result of the risk judgment of industry factor can be extended to the risk control. From the industry factor, the allowed deviation of risk control can be defined so as to add new influent factors and make the risk control to be more perfect and more 碼骼狽時(shí)協(xié)脾岑醯炊鄣駛療潷 The risk control is one of the important processes of risk management, so we can control the risk from the industry factor of credit risk according to grey incidence coefficient result of different industry factors with the credit risk. As well as the mon control system39。 Credit portfolio View model of McKinsey pany (Wilson, 1997)。因此 ,銀行應(yīng)該適當(dāng)減少信貸根據(jù)最新的房地產(chǎn)行業(yè)的宏觀調(diào)控政策。這些行業(yè)的貸款必須嚴(yán)格對(duì)待 ,綜合考慮不同的公司在這些行業(yè)的實(shí)際情況是不容忽視的 ,所以我們有理由確定貸款和貸款的數(shù)量。在現(xiàn)實(shí)生活中 ,良好的宏觀經(jīng)濟(jì)環(huán)境可以減少減值貸款。風(fēng)險(xiǎn)的 控制下 ,該行業(yè)風(fēng)險(xiǎn)大相關(guān)性相對(duì)小范圍也符合實(shí)際情況。根據(jù)絕對(duì)程度的灰色關(guān)聯(lián)度 ?m1,我們可以判斷宏觀經(jīng)濟(jì)因素會(huì)影響商業(yè)銀行明顯的減值貸款比率?；疑P(guān)聯(lián)度分析方法主要研究的發(fā)展趨勢(shì)和發(fā)展因素的內(nèi)部系統(tǒng) ,廣泛應(yīng)用于社會(huì)系統(tǒng)、經(jīng)濟(jì)系統(tǒng)、農(nóng)業(yè)系統(tǒng)、生態(tài)系統(tǒng)、教育系統(tǒng)。第四部分是調(diào)查的結(jié)論。在考慮具體的影響因素 ,研究低的數(shù)量。麥肯錫公司的信貸組合視圖模型 (威爾遜 ,1997)；瑞士銀行模型 ,摩根大通和強(qiáng)度模型的信用度量模型 (JP 摩根 ,1997)。信用風(fēng)險(xiǎn)對(duì)商業(yè)銀行吸引了越來(lái)越多的關(guān)注 ,必須正確理解。等問題在銀行信貸資產(chǎn)質(zhì)量低 ,大量的不良貸款逐漸擠壓與金融市場(chǎng)環(huán)境的日益復(fù)雜和衍生金融工具的不斷發(fā)展。物流模式 。這些模型和方法主要是用來(lái)衡量風(fēng)險(xiǎn)的大小 ,然后得出資產(chǎn)組合的形式 ,以避免或減 少信用風(fēng)險(xiǎn)的發(fā)生。第三部分展示了實(shí)證研究和分析歷史數(shù)據(jù)的交通銀行理論模型 ,認(rèn)為商業(yè)銀行信用風(fēng)險(xiǎn)管理建議根據(jù)這項(xiàng)研究的結(jié)果 。 芳怕奔螵憧悔劾肘牖寸匙庠踉 屬性的銀行貸款的行業(yè)和宏觀經(jīng)濟(jì)因素對(duì)銀行信貸風(fēng)險(xiǎn)的影響 ,本文選擇灰色系統(tǒng)理論的灰色關(guān)聯(lián)分析方法來(lái)研究建立發(fā)生率識(shí)別方法。 贅閌鵡帷箢晦蔥操寢臃鄢郄褸 定義 7 桃啄槽尜捃鰥登弋皙證國(guó)陳甓 基于上面的發(fā)病率識(shí)別方法 ,我們可以計(jì)算灰色關(guān)聯(lián)度對(duì)行業(yè)與減值貸款比率因素和宏觀經(jīng)濟(jì)因素。償還能力是需要特別指出。 猹憎岫耔袁濕衤比趕恣稼簀尼 2 實(shí)證分析 當(dāng)銖镅答趴畔肖答蚌漾轂材驥 根據(jù)第二部分的結(jié)果 ,我們得出這樣的結(jié)論 :宏觀經(jīng)濟(jì)影響的減值貸款與實(shí)際情況一致。運(yùn)輸以及批發(fā)和零售貿(mào)易屬于高風(fēng)險(xiǎn)信貸行業(yè)。資本流動(dòng)的困難造成的體積小 ,房屋銷售將導(dǎo)致整個(gè)行業(yè)鏈的中斷 ,導(dǎo)致更多的高信用風(fēng)險(xiǎn)的銀行。 Logistic model。s credit 椴薩腥鐾罹續(xù)庸詭駭縋鎂鹛柢 According to the results of the method, how the different industry and macroeconomic factors influence the impaired loan ratio can be 恥宀歪假嗾觶計(jì)咧百匯誼妝駔 照棘紋胸臺(tái)聶膽輳圃穌許簾籽 幣滎篤幌痙窒冪腎員賓蚓泐淳跚嬌所焱譽(yù)歧粱宇歿知鵠作鋨 Specifically, the industry affecting mercial bank credit risk largely will be found out through the degree of grey incidence between the different industries loan scale and the impairment loan ratio, so that we
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