金程教育FRM根底班講義

OperationalRiskManagement講師：吳堅雋日期：2021年8月地點：■上海□北京□深圳11吳堅雋金程職稱：金程資深培訓師教授課程：操作風險新巴塞爾協議經濟資本教育背景及資歷：經濟學博士FRM相關工作背景：擁有近5年的風險管理、經濟資本、新巴塞爾協議研究、實施經驗，四年FRM授課經驗，吳先生現供職于某會計師事務所，從事金融風險管理咨詢工作。他在風險管理領域的專長包括金融工具定量分析、監管及經濟資本管理，新巴塞爾資本協議的實施與合規等。相關研究成果曾在?財經研究?、?上海金融?等核心期刊發表。他曾參與3家上市商業銀行新巴塞爾協議、經濟資本的內部培訓工程。他還曾受邀參加首屆全球風險與保險經濟學大會〔WRIEC〕，發表并宣讀會議論文。聯系方式：：021－2StudySessionProportionQuestionFoundationsofRiskManagement10%14questionsQuantitativeAnalysis10%14questionsFinancialMarketsandProducts15%21questionsValuationandRiskModels15%21questionsMarketRiskMeasurementandManagement10%14questionsCreditRiskMeasurementandManagement10%14questionsOperationalandIntegratedRiskManagement10%14questionsRiskManagementandInvestmentManagement10%14questionsCurrentIssuesinFinancialMarkets10%14questionsTotal:

100FRM課程框架3OutlineOperationalRiskWarmUp:WhyOperationalRisk?DefinitionofOperationalRiskMeasurementofOperationalRiskManagementofOperationalRiskOtherRisksrelatedtoOperationalRiskTechnologyRiskDaylightOverdraftRiskModelRisk4WhatIsRiskandRiskManagement?ReputationalRiskRiskEarningsVolatilityManagementofthedriversofearningsvolatilityManagementoftheperceptionofmanagementstrengthandcorporateculture5DriversofEarningsVolatilityEarningsVolatilityCreditRiskMarketRiskOperationalRisksBusiness/StrategicRisks6TheRiskTree7CaseHistoriesofOperationalRiskFeb2002AlliedIrishBank(US$691mloss)Aroguetrader,JohnRusnack,

hides3yearsoflosingtradesontheyen/dollarexchangerateattheU.S.

subsidiary.Thebank’sreputationisdamaged.Mar1997NatWest($127mloss)Aswaptiontrader,KyriacosPapouis,

deliberatelycoversuplossesbymis-pricingandover-valuingoptioncontracts.

Thebank’sreputationisdamaged:NatWestiseventuallytakenoverbytheRoyal

BankofScotland.Sept1996MorganGranfell(US$720million)Afund

manager,PeterYoung,exceedshisguidelines,leadingtoalargeloss.Deutsche

Bank,theGermanownerofMGAM,agreestocompensatetheinvestorsinthefund.8Jun1996Sumitomo(US$2.6billionloss)Acoppertraderamassesunreportedlossesover3years.YasuoHamanaka,knownas“Mr.FivePercent,〞aftertheproportionofthecoppermarkethecontrolled,issentencedtoprisonforforgeryandfraud.Thebanks’reputationisseverelydamagedSep1995:Daiwa($1.1bloss)Abondtrader,ToshihideIgushi,amassesunreportedlossesover11yearsattheU.S.subsidiary.Thebankisdeclaredinsolvent.Feb1995:Barings($1.3bloss)NickLeeson,aderivativestraderamassesunreportedlossesover2years.Baringsgoesbankrupt.Oct1994:BankersTrust($150mloss)Thebankbecomesembroiledinahigh-profilelawsuitwithacustomerthataccusesitofimpropersellingpractices.Bankerssettlesbutitsreputationisbadlydamaged.ItislaterboughtoutbyDeutscheBank.CaseHistoriesofOperationalRisk9LessonsfromtheCaseHistoriesInvolvingroguetradersorinternalfrauds.Involvingamixofmarketriskandoperationalrisk(failure

tosupervise).Costs:Directcost-monetarylossesIndirectcost–

reputational

damage,liquidityproblem,insolvency,bankruptcy…10OperationalRiskOperationalRiskMostfinancialdisasterscanbeattributedtoacombinationofmarketandcreditriskalongwithsomefailureofcontrols,whichisaformofoperationalriskNocommondefinitionsforthisriskclassBaselIIforthefirsttimeestablishesDefinitionforoperationalriskLosseventtypesCapitalchargesforoperationalrisk11DefinitionforOperationalRisk“...theriskoflossresultingfrominadequateorfailedinternalprocesses,peopleandsystemsorfromexternalevents.Thedefinitionincludeslegalriskbutexcludesstrategicandreputationrisk.〞.12BaselIIDefinitionofOp-RiskRisklossresultinginadequateorfailed

internalprocess,peopleandsystemsorfromexternaleventsInclude:LegalRiskExclude:strategicandreputationrisk定義的方式causeimpact定義中引起操作風險的原因People(humanfactor)Internalprocessessystemsexternalfactors.定義中不包含的風險strategicriskandreputationalrisk定義中包含的風險legalrisk13OpRiskClassification:InternalRisks

(Source:BritishBankers’Association)InternalRisksPeopleProcessesSystemsEmployeecollusion/fraudEmployeeerrorEmployeemisdeedEmployersliabilityEmploymentlawHealthandsafetyIndustrialactionLackofknowledge/skillsLossofkeypersonnelAccountingerrorCapacityriskContractriskMisselling/suitabilityProductcomplexityProjectriskReportingerrorSettlement/paymenterrorTransactionerrorValuationerrorDataqualityProgrammingerrorsSecuritybreachStrategicrisks(platform/suppliers)SystemcapacitySystemcompatibilitySystemdeliverySystemfailureSystemsuitability14OpRiskClassification:ExternalRisks

(Source:BritishBankers’Association)ExternalRisksExternalPhysicalLegalMoneylaunderingOutsourcingPoliticalRegulatorySupplierriskTaxFireNaturaldisasterPhysicalsecurityTerroristTheft15BusinessLinesandOperationalRisk16CommercialBankingandOperationalRisk

(Source:OWC)(Source:CMRA)17MostSignificantOpRisk-APollbyRiskManagementAssociationin200318BaselIILossEventTypesandExamplesEventTypeExamplesInternalfraudEmployeetheft,intentionalmisreportingofpositions,andinsidertradingonanemployee'sownaccountExternalfraudRobbery,forgery,andcheckkitingEmploymentpracticesandworkplacesafety（就業政策與工作場所安全）Workers'compensationanddiscriminationclaims,violationofemployeehealthandsafetyrules,andgeneralliabilityClients,products,andbusinesspractices（客戶，產品和業務操作）Fiduciarybreaches,misuseofconfidentialcustomerinformation,moneylaundering,andsaleofunauthorizedproductsDamagetophysicalassets（實體資產損壞）Terrorism,vandalism,earthquakes,fires,andfloodsBusinessdisruptionandsystemfailures（業務中斷和系統失敗）Hardwareandsoftwarefailures,telecommunicationproblems,andutilityoutagesExecution,delivery,andprocessmanagement（執行，交割和流程管理）Dataentryerrors,collateralmanagementfailures,incompletelegaldocumentation,andvendordisputes19ProcessRisks-InadequateProcessIntegrity&DurabilityExecution,Delivery&ProcessManagementBusinessDisruptionandSystemsFailureConductRisks-EthicalorLegalMisconductClients,Products&BusinessPracticesEmploymentPracticesandWorkplaceSafetyInternalTheftandFraudExternalRisks-ExternalVulnerabilitiesExternalTheftandFraudDamagetoPhysicalAssetsRe-groupingofOpRisklossevents20OperationalRiskEvents21Top-DownModelsonOpRiskAssessmentTheyattempttomeasureoperationalriskatthebroadestlevel,thatis,

firm-wideorindustry-widedata.Resultsarethenusedtodeterminetheamountof

capitalthatneedstobesetasideasabufferagainstthisrisk.Thiscapitalisallocated

tobusinessunits.22Bottom-upModelsonOpRiskAssessmentTheystartattheindividualbusinessunitorprocesslevel.Theresultsarethenaggregatedtodeterminetheriskprofileoftheinstitution.Themainbenefitofsuchapproachesisthattheyleadtoabetterunderstandingofthecausesofoperationallosses.23AssessingOperationalRiskSummaryTop-DownApproachBottom-UpApproachSophisticationSimpleComplexDatarequirementNon-intensiveIntensiveHFLSVLFHSUndifferentiatedDifferentiatedDiagnosticabilityNoYesPerspectiveBackward-lookingForward-looking24TopDownMethod1.Multi-factormodels2.Income-basedmodels3.Expense-basedmodels4.Operatingleveragemodels5.Scenarioanalysis6.Riskprofilingmodels25Multifactormodels(TD)：Return-basedmodelThisapproachanalyzesthereturntimeseriesandsomemacroeconomictimeseries.Thelateronesreflectthemarketriskorcreditrisk.Forinstance,wehaveY=A+BX+εY:ReturnChangeX:RiskFactorsB:SensitivityFactors(1–R2)*V(y)canindicatethesizeofunsystematicrisk(i.e.operationalrisk)Itiseasytoestimate(publictradedfirms)CannotbeusedasdiagnostictoolUsefulinestimatingfirm’sstockpricereactiontoHFLSOReventsonly.DoesnotperformwellwhenlargescaleeventsbreakthecontinuityofequityreturnsMergerCatastrophic(LFHS)26Multifactormodels(TD)：Return-basedmodelOtherrelatedmodels:Income-basedmodelThesearealsocalledEarningatRisk(EaR)models.Incomeorrevenue(asthedependentvariable)isregressedagainstcreditriskfactor(s)andmarketriskfactor(s).Theresidual,orunexplained,volatilitycomponentisdeemedtobethemeasureofoperationalrisk.Otherrelatedmodels:Expense-basedmodelOperationalriskismeasuredasfluctuationsinhistoricalexpenses.Thisistheeasiestapproachbutignoresoperationalrisksthatareunrelatedtoexpenses;further,arisk-reducinginitiativethathappenedtoincreaseexpenses(becauseitinvolvedacost)wouldbemischaracterized.27ScenarioAnalysisInthiscontext,thisisagenericlabelreferringtoanattemptto“imagine〞variousscenariosthatcontaincatastrophicshocks.Bydefinition,scenarioanalysisattemptstoanticipatelowfrequencyhighseverity(LFHS)riskevents–butdoingthisgenerallyisasubjectiveexercise.28Riskprofilingmodels

(TD)：KeyRiskIndicatorsKRIaresimplemeasuresthatprovideanindicationofwhetherrisksarechangingovertime.Thesecanincludeauditscores,staffturnover,tradevolumes,andsoon.〔總量上，建立聯系〕Theassumptionisthatoperationalriskeventsaremorelikelytooccurwhentheseindicatorsincrease.ThesemeasuresallowtheriskmanagertoforecastlossesthroughtheapplicationofstatisticalmodelsOtherrelatedmodelsOperationalperformanceindicators/KPIOperationalcontrolindicators/KCI29BottomUpMethodTherearethreetypesofbottom-upapproaches:

ProcessApproachTheprocessapproachattemptstoidentifyrootcausesofrisk;becauseitseekstounderstandcauseand-effect,inshouldbeabletohelpdiagnoseandpreventoperationallosses.ActuarialProprietary.30Processapproachesmodels

(BU)：CausalnetworksCausalnetworksexplainlossesintermsofasequenceofrelatedvariables.Eachvariableitselfcanbeduetothecombinationofothervariables.Forinstance,settlementlossescanbeviewedascausedbyacombinationof(1)exposureand(2)timedelay.Causesandeffectsarelinkedthroughconditionalprobabilities.Simulationsarethenrunonthenetwork,generatingadistributionoflosses31Processapproachesmodels

(BU)OtherrelatedmodelsConnectivityModelConnectivitymodelsaresimilartoscorecardsbuttheyfocusoncause-and-effect.Examplesofconnectivitymodelsincludefishboneanalysisandfaulttreeanalysis.ReliabilityModelsReliabilitymodelsemphasizestatisticaltechniquesratherthanrootcauses.Theyfocusonthelikelihoodthatariskeventwilloccur.Thetypicalmetricistheeventfailurerate,whichisthetimebetweenevents.〔關注事件發生的間隔〕32ActuarialModels(BU)：Parametric-basedlossdistribution

Thisapproachestimatestheobjectivedistributionoflossesfromtwokindofdistributions,lossfrequenciesandlossseverities.Thelossfrequencydistributiondescribesthenumberoflosseventsoverafixedintervaloftime.Traditionalparamediclossfrequencydistributionsare:BinomialDistributionNegativeBinomialDistributionPoissonDistributionThelossseveritydistributiondescribesthesizeofthelossonceitoccurs.Traditionalparamediclossseveritydistributionsare:LognormalDistributionWeibullDistributionTANDistribution(mixtureofNormaldistributionandGammadistribution)33ActuarialModels(BU)OtherrelatedmodelsHistorical-basedlossdistributionInternalandexternaldataonoperationallossesareplottedinahistograminordertodrawtheempiricallossdistribution.Basically,itisassumedthatthehistoricaldistributionwillapplygoingforward.Assuch,nospecificationormodelisrequired(i.e.,MonteCarlosimulationcanfillinthegaps).ExtremeValueTheoryThisapproachisnotmutuallyexclusivetotheempiricalandparametricapproaches.EVTconductsadditionalanalysesontheextremetailoftheoperationallossdistribution.ForLFHSevents,acommondistributionistheGeneralizedParetoDistribution(GPD).Extremevaluetheory(EVT)impliestheuseofadistributionthathasfat-tails(leptokurtosisorkurtosis>3)relativetothenormaldistribution.34FrequencyandLossTable35ConvolutionNumberoflossesFirstLossSecondLossTotalLossProbability011122222222201000100001000001000100010001000010000100001000001000001000000000100010000100000100010000100000100010000100000010001000010000020001100010100011000200001100001010001100002000000.60.150.090.060.0250.0150.0100.0150.0090.0060.0100.0060.004Expectation1175036OperationalLossDistributionExpectedLoss=averagelossUnexpectedLoss=WorstCaseLoss–ExpectedLoss37OperationalLossDistribution$100,000withaprobabilityof96.4%.VaRat96.4%=100000-11750=$88,25038ProprietaryOperationalRiskModelsProprietaryOperationalRiskModelsProprietarymodelsinclude,forexample,OpVarofferedbyOpVantage.Aproprietarymodelvendorhastheirowndatabaseofeventlossesthatcanbeusedtohelpfitdistributions.39OperationalRiskManagementEightKeyPrinciplesrelevanttobanksforORMframeworkDefinitionandApprovalInternalauditscrutiny〔詳細審查〕FormulationandimplementationAssessmentandidentificationMonitoringandreportingControlandreviewpoliciesContingencystrategiesPublicdisclosure40OperationalRiskManagementIntegratedtheEightKeyPrinciplesinaFirm-wideframeworkDefiningmanagerialresponsibilitiesIdentifyingdependenciesacrossunitsDevelopingpreventioncontrolsExamininginternallossdataandexternaleventsPeriodicallyreviewingandupdatingtheopriskplan41MethodsforHedgingOperationalRiskInsuranceSelf-InsurancecashreservesReservesofliquidassetsContingentcreditlineRiskpreventionandcontrolOff-shoreinsurancesubsidiary〔CaptiveInsurers〕DerivativesCatoptions—spreadoption(underwritingderivatives,Weatherderivatives)Catbonds(Indemnifiednotes〔減免〕,Indexednotes,Parametricnotes)42InsuranceWhy?(transferORtoInsuranceCompany,especiallyLFHS)ProblemofmoralhazardleadtoDeductibleCo-insurancefeaturesPrimarydisadvantage:thelimitationofpolicycoverage.10-30%ofpossibleOL.Largepotentiallossesmaybeuninsurable.Ambiguityinthedegreeofcoverage—delaysinsettingclaims.Insuranceistypicallyexpensive-beusedjudiciouslytotargetrisktowhichthefirmismostvulnerable.(HigherthanEL)Thenhowaboutself-Insurance?43Self-insuranceWhy?reducethecostofinsurancecoveragetomanageriskinternallyCapitalprovisionheldascushionagainstoperationallosses.Setasideaportfolioofliquidassets,suchasmarketablesecurities.Establishalineofcredit—makesfinancingavailablecontingentontheoccurrenceoflargeoperational.RiskpreventionandcontrolInvestresourcestoconstructriskmitigationtechniquesIntheform(riskidentification,externalvalidation,riskmonitoring,incentivetopromoteactivities,riskreportingrequirements,ControlOR)Captiveinsurerwhollyownedinsurancesubsidiaryallowthefirmtoobtainthepreferentialtaxtreatmentaccordedtoinsurancecompany.44HowtoChoose?ThreeMethodsSub-methodComments/characteristicEmpiricalResults(Lossestohedge)>USD100MUSD51~100MUSD11~50M<USD10MSelfInsurancecashreservesheldascushionagainstoperationallossesAppliedAppliedAppliedReservesofliquidassetsContingentcreditlinecredit—makesexternalfinancingavailableRiskpreventionandcontrolInvestresourcestoconstructriskmitigationtechniquesCaptiveinsurerallowthefirmtoobtainthepreferentialtaxtreatmentAppliedApplied45MethodsforHedgingOperationalRiskThreeMethodsSub-methodComments/characteristicEmpiricalResults(Lossestohedge)>USD100MUSD51~100MUSD11~50M<USD10MInsuranceProblemofmoralhazardleadtoDeductibleandCo-insurancefeaturesAppliedAppliedAppliedDerivativesCatoptionsOfferinsuranceeffect/notwell-developedEmpiricalResultsNotavailable46OutlineOperationalRiskWarmUp:WhyOperationalRisk?DefinitionofOperationalRiskMeasurementofOperationalRiskManagementofOperationalRiskOtherRisksrelatedtoOperationalRiskTechnologyRiskDaylightOverdraftRiskModelRisk47RelationshipBetweenTechnologicalImprovements,OperationalRiskandProfitabilityTechnologycandirectlyimproveprofitabilityInterestincomeincreaseInterestExpensereduceOtherincomeincrease〔新產品〕Noninterestexpensesreduce〔人力資源效率提升〕TechnologyenhancementcanincreaseoperationalriskFuturerevenueswon’tcoverdevelopmentcostsexcesscapacityproblemintegrationproblemcostoverrunproblemscostcontrolproblems48EconomiesofScale規模經濟規模經濟在產業經濟學中又叫規模利益，是指伴隨著企業生產能力的擴大而出現的生產批量擴大，以及由此而帶來單位制成品生產本錢的下降和企業盈利的遞增現象〔Theeconomyofscaleadvantageisadeclineintheaveragecostofproducingaserviceasthefinancialinstitutiongrows.〕Averagecostofproduction：ACiaveragecostofithfinancialinstitution，TCiTotalcostofithfinancialinstitutionSirepresentssizeofthefinancialinstitutionsmeasuredbyassets,depositsandloansThreeshapesofDiseconomiesofScale49EconomiesofScope范圍經濟范圍經濟是指合并生產兩種產品，而不是分別生產，會帶來的協同效應〔synergy〕范圍經濟也是技術創新的一項重要組成局部，因為對資源的合并使用可以節約本錢。FI’sabilitiestogeneratesynergisticcostsavingsthroughjointuseofinputsinproducingmultipleproducts.CaseofeconomiesofScopeEconomicsofscope：Thecostofjointproductionviacostsynergisticislessthantheseparateandindependentproductionoftheseservices.〔IFAC1+2<(TC1+TC2)/(S1+S2),ThenEconomiesofscopeisachievedDiseconomicsofscope:Thecostsactuallyhigherfromjointproductionofservicesthaniftheywereproducedindependently.〔IFAC1+2>(TC1+TC2)/(S1+S2),ThenDiseconomiesofscopeexists〕50TechnologicalRiskSomeempiricalresultsEconomicsofscale(Asset$10-25billion)existforlargeregionalandsuper-regionalbankEconomicsofscopeexistevidenceisweakamongbank.NoevidenceofEconomicsofscale/scopeinnonbankfinancialserviceNostrongevidencethatbiggerisbetter.Economicsofscopeandscaledon’texplaincostdifferencesamongthesamesizefirms.RelativelylowpayofffromtechinnovationlargeFIgainefficiencybygeneratingrevenueratherthanreducingcosts.X無效率？51DaylightoverdraftriskFedwire通過FedWire的資金清算是雙向的，即聯邦儲藏銀行借記寄出方賬戶，并以相同信息貸記接收方賬戶。FedWire允許白天透支。在轉賬時，如果寄出方在聯邦儲藏賬戶中的資金缺乏，無法在其賬戶中對可用資金進行借記，即寄出方不能立即和聯邦儲藏銀行清算其資金余額，此時，FedWire那么向其發出一筆貸款，并仍然貸記接收方儲藏賬戶。因此，不管寄出方能否同聯邦儲藏銀行清算其資金余額，對接收方來說，支付總是最終的。52DaylightoverdraftriskWiretransfersysteminUSCHIPS(ClearingHouseInterbankPaymentSystem):紐約清算所銀行同業支付系統國際貿易資金清算的橋梁歐洲美元供給者進行交易的通道Purenetsettlementsystem，日初頭寸0Allintradaytransfersareconsideredprovisionaluntilsettlementoccursattheendoftheday.層層代理的清算體制:非參加銀行可由參加銀行代理清算，參加銀行又由會員銀行代理清算53DaylightoverdraftriskCHIPS流程中央計算機系統對各參加銀行當日(ValueDate)的每筆交易進行統計，統計出各參加銀行應借或應貸的凈金額。中央計算機系統給各參加銀行傳送當日交易的摘要報告當日下午4：30后，CHIPS關閉，通過FedWire網，將各參加銀行應借或應貸的凈金額通知紐約區聯邦儲藏銀行。紐約區聯邦儲藏銀行利用其會員銀行的存款準備金賬戶完成清算。清算完成后，通知CHIPS，CHIPS那么于下午5：30～6：30，用1小時的時間軋平賬務。54DaylightoverdraftriskWhatisdaylightoverdraft?daylightoverdraft,daylightcredit,daylightexposure,intradaycredit日間透支,日間信用,日間風險,日內信用BKhavenegativeintradaybalancesonFed準備金一個營業日以內的信用；在日終結算的信用轉帳系統中，假定接收了支付指令的機構接收了支付指令并且即使這家機構在營業日結算前不能收到最終資金也按指令的要求行動的話，它就在實事上心照不宣地提供了日間信貸。畫圖55Daylightoverdraftrisk結果：專家認為是銀行系統的最大風險BONY1985—Afailurecouldbedestabilizingtothe金融市場Bony(政府債券的主要交易商)1985/11/20軟件系統崩潰日間風險上升21號晚上修復Fed提供了一天的貸款，相當于其總資產的2/3.56ModelRiskDefinemodelriskandidentifysourcesofmodelrisk.Modelriskistheriskassociatedwithusingfinancialmodelstosimulatecomplexrelationships.Itmayarisefromincorrectmodelapplication,implementationrisk,calibrationerrors,programmingerrors,anddataproblems.57Rebonato’sdefinitionofmodelrisk:Modelriskistheriskofoccurrenceofasignificantdifferencebetweenthemark-to-modelvalueofacomplexand/orilliquidinstrument,andthepriceatwhichthesameinstrumentisrevealedtohavetradedinthemarket.ModelRisk58Thereareseveralpointsworthnoticingaboutthedefinition.Firstofall,fromthedefinitionitfollowsthat,ifreliablepricesforallinstrumentswereobservableatalltimes,modelriskwouldnotexist.Anotherimportantobservationisthattheinstrumentinquestionmay,butneednot,becomplexorheldoff-balancesheet:modelriskhasoftenbeenassociatedwithcomplexderivativesproducts,butadeeplyout-of-themoneycall(theplain-vanillaoptionparexcellence)andanilliquidcorporatebond(aprototypicalon-balance-sheetinstrument)canbothpresentsubstantialmodelrisk.Whatboththeseinstrumentshaveincommonisthat