Review Questions 31Word下载.docx
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Review Questions 31Word下载.docx
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3.1.4Listsomeofthecommoncategoriesofinformationusedtobuildacreditscore.
3.1.5Whichiseasiertoestimate,theprobabilityoftype1errorsortype2errors?
3.1.6
FICO(previouslyFairIsaacCorp)isapublicly-tradedcorporationthatcreatedthebest-knownandmostwidelyusedcreditscoremodelintheUnitedStates.
Howisthescoreconstructed,i.e.,whatarethemainconsiderations?
OutlinetherangeofFICOscoresandthekeyboundaryscores.
Whataresomestrategiesforimprovingacreditscoreunderthissystem?
3.1.7PleaseattemptProblemIICreditReportonpage693ofKochandMacdonald.
Creditscoringtechniques
ReviewQuestions3.1.1
Q1.Whatisstatisticalcreditscoring?
Howdoesitdifferfromjudgementalmethods?
A.Creditscoringisamathematically-basedtoolthatrankstheprobabilityofanunknownoutcome,e.g.aloanispaidordefaultedupon;
thisisdonebyallocatingapointssystemtoknownvariables.Thecreditinformationofanapplicantisassessedandgradednumerically
togainatotalscore.Thisscoreisthenassessedagainsttheexpectationsoroutcomesofafinancialinstitutionbasedonitsriskappetite.
Statisticalcreditscoringisbasedontechnologyandinformationaveragesforprobabledefaultoutcomesoverarangeofloans.Judgementaldecision-makingreliesontheinputoftheindividualloanofficerbasedonrelationships,knowledgeoftheclientandtheexperienceoftheindividuallender.
Thescoregiventoacustomerisnormallyproportionaltothenaturallogarithmoftheodds(orlogit)ofthecustomerbecoming‘bad’.Itisnormallya3or4digitnumber;
thehigherthenumber,thehigherthequalityoftheborrower
Q2.Doestheadoptionofcreditscoringaddvaluetoafinancialinstitution?
Whatpotentialexistsforanadverseoutcome?
Implementationofafullcreditscoringsystemacrossafinancialinstitutionwilladdvaluebecauseitwillallowfortheprobabilityofdefaulttobebuiltintothepricingoftheloan.
Thisallowsfordynamicprovisioningofloandefaulttobebuiltintothecashflowsoftheinstitution.Otherbenefitsareoutlinedinquestion3.
Anadverseoutcomecanoccuriftheassumptionsbuiltintothemodelareincorrectorbasedonoutofdateoranecdotalinformation.Thiscouldallowforanincreasedlevelofdefaultnotfactoredintothesystem.
Q3.Creditscoringmethodshavemushroomedinrecentyears.Whatarethreeapplicationsofthedifferingmethods?
Howdotheyaddvaluetothefinancialinstitution?
Applicationsinclude:
☐todeterminewhethercreditshouldbeapproved,
☐inthesettingofcreditlimitsoncreditcards/storecards,
☐behavioralmodelingsuchascollectionsscoring:
(whichinvolvespredictingacustomer'
sresponsetodifferentstrategiesforcollectingowedmoney),
☐inthepre-approvalofadditionalcredittoacustomer.
Theyaddvaluetothefinancialinstitutionbecause:
∙Creditscoringcanincreasereturnsbyidentifyinggoodversusbadpropositions.
∙Accuratecreditscoringreducescreditrisktoastatisticallyaccuratepercentageofoutstandingloans.
∙Creditscoringreducescost,savestimeandallowsforvolumeincreases.
∙Creditscoringincreasesflexibilityandmarketpenetration.Forexample,alowcostexpansionintothesmallbusinesssector.
∙Poorcreditoutcomesallowforcorrectionandre-adjustment(ofthemodel)bytheinstitution.
∙Strongerrelationshipscandevelopusingdifferentrelationshipcriteria.Loansstaffhavemoretimetodeveloprelationshipswithcustomers,andcanbetrainedinthisregard.
Q5.Whataretheadvantagesanddisadvantagesofimplementingcreditscoringwithinafinancialinstitution?
SomeadvantageswerementionedinQ3.Furthertothis:
A.Advantages:
∙Lesslabourcosts
∙Lowerlevelsofinvestmentintrainingoflendingofficers
∙Abilitytogrowtheloanportfolioswithlessresources
∙Loanpricingcanreflectmoreaccuratelytheriskinvolvedinextendingcredit
∙Abilitytoapplystandardisationacrosstheloanportfolio
∙Allowsuseofexperiencedstaffatthecentralisedlevel
∙Lossesaremanagedwithstatisticallyacceptableboundaries
∙Riskandreturncanbequantifiedacrosstheportfolios
∙Ameasurablerejectionmethod
Disadvantages:
∙Thepotentialforinappropriateanalysisanddecision-making–eg.ethnicbias
∙Potentialalienationofthetargetedclientgroupeg.smallbusinesses
∙Potentia
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