基于bp人工神經(jīng)絡(luò)的商業(yè)銀行信用風(fēng)險(xiǎn)研究

1、1商業(yè)銀行信用風(fēng)險(xiǎn)評估模型研究——基于BP神經(jīng)網(wǎng)絡(luò)風(fēng)險(xiǎn)評估的改進(jìn)天津財(cái)經(jīng)大學(xué)刑春玉、安菁菁、陳翔穎目錄摘要..................................................................................................................................................2一、商業(yè)銀行信用風(fēng)險(xiǎn)評估體系......

2、..............................................................................................4二、銀行信用風(fēng)險(xiǎn)評估模型發(fā)展....................................................................................................5（一）基于貸款客戶資

3、產(chǎn)價(jià)值數(shù)據(jù)的風(fēng)險(xiǎn)評估模型............................................................51.KMV模型.......................................................................................................................52.CreditMetrics模型...

4、..............................................................................................63.CreditPtfolioView模型...................................................................................64.CreditRiskPlus模型..

5、...........................................................................................7（二）基于貸款客戶財(cái)務(wù)數(shù)據(jù)的風(fēng)險(xiǎn)評估模型....................................................................7（三）商業(yè)銀行財(cái)務(wù)風(fēng)險(xiǎn)的評估模型有待改進(jìn)...................

6、.................................................81.我國商業(yè)銀行現(xiàn)有評估財(cái)務(wù)風(fēng)險(xiǎn)的方法....................................................................82.國際商業(yè)銀行普遍使用的風(fēng)險(xiǎn)評估方法...............................................................

7、.....9三、信用風(fēng)險(xiǎn)評估的實(shí)證分析......................................................................................................10（一）YH銀行采用的貸款違約風(fēng)險(xiǎn)評估模型及評估結(jié)果...............................................101.計(jì)算資產(chǎn)價(jià)值和資產(chǎn)波動(dòng)率.........

8、.............................................................................102.計(jì)算違約距離和期望違約率......................................................................................12（二）基于BP神經(jīng)網(wǎng)絡(luò)信用風(fēng)險(xiǎn)估計(jì)......................

9、.........................................................141.樣本選取......................................................................................................................142.實(shí)證分析.............................

10、.........................................................................................15四、對商業(yè)銀行信用風(fēng)險(xiǎn)評估提出的建議..................................................................................21（一）結(jié)合KMV法與BP神經(jīng)網(wǎng)絡(luò)模型評估財(cái)務(wù)風(fēng)險(xiǎn)...

11、................................................21（二）逐步推進(jìn)內(nèi)部評級法..................................................................................................22（三）建立使用預(yù)期損失模型.............................................

12、.................................................231.預(yù)期損失模型應(yīng)關(guān)注謹(jǐn)慎性和中立性......................................................................232.預(yù)期損失模型提高相關(guān)性兼顧可靠性.............................................................

13、.........23（四）完善財(cái)務(wù)風(fēng)險(xiǎn)披露要求............................................................................................241.提供整體層面的風(fēng)險(xiǎn)信息.........................................................................................

14、.242.報(bào)告多種損失的分布結(jié)果..........................................................................................243.提高信息披露的全面性..............................................................................................25（五）通

15、過健全內(nèi)部控制降低財(cái)務(wù)風(fēng)險(xiǎn)防范成本..............................................................25（六）建立非上市公司信用風(fēng)險(xiǎn)評估模型..........................................................................26（七）針對不同的貸款類型選擇適當(dāng)?shù)娘L(fēng)險(xiǎn)評估方法......................

16、................................26五、總結(jié)..........................................................................................................................................26【參考文獻(xiàn)】....................................

17、..............................................................................................283WiththeeconomicdevelopmentofTianjinBinhaiNewAreathecommercialbankshaveoperationsintheBinhaiNewAreatoprovidefinancialservice

18、stocompaniesintheregion.Riskassessmentisanimptantpartofthecommercialbanktomakeinternalcontroltoestablishthevaluesofthecompanies.Thisresearchmethodmakesuseofthemeasurementstatisticsstructuredresearchmethodstoevaluatethecr

19、editrisk.InstructuringresearchweuseKMVmodeltogettheprobabilityofdefaultof11listedcompaniesinBinhaiNewArea.Inthemeasurementofstatisticalresearchthisarticleuse18companiesedassamplesthataresimilartotheabove11companiesusingB

20、Partificialneuralwkmodeltoassessthecreditriskofthe11listedcompanies.AssessmentresultsshowthatBPneuralwkmodelfittedbetterthantheKMVmodel.Sincethevariousmodelshaveshtcomingscommercialbanksshouldincreasethediversityofmodels

21、maketheuseoftheadvantagesofvariousmodels.ThispaperalsoproposedusingBPartificialneuralwkmodelcombinedwithKMVmodeltoevaluatethecreditriskofnonlistedcompaniestomakeupthatnonlinearmodel’sweakness.Keywds:CreditRiskBPartificia