Analytical Techniques in the Assessment of Credit Risk: An Overview of Methodologies and Applications PDF
Preview Analytical Techniques in the Assessment of Credit Risk: An Overview of Methodologies and Applications
EURO Advanced Tutorials on Operational Research Series Editors: M. Grazia Speranza · José Fernando Oliveira Michalis Doumpos · Christos Lemonakis Dimitrios Niklis · Constantin Zopounidis Analytical Techniques in the Assessment of Credit Risk An Overview of Methodologies and Applications EURO Advanced Tutorials on Operational Research SeriesEditors M.GraziaSperanza,Brescia,Italy JoséFernandoOliveira,Porto,Portugal Moreinformationaboutthisseriesathttp://www.springer.com/series/13840 (cid:129) (cid:129) Michalis Doumpos Christos Lemonakis (cid:129) Dimitrios Niklis Constantin Zopounidis Analytical Techniques in the Assessment of Credit Risk An Overview of Methodologies and Applications MichalisDoumpos ChristosLemonakis SchoolofProductionEngineering DepartmentofBusinessManagement andManagement UniversityofAppliedSciencesCrete TechnicalUniversityofCrete Crete,Greece Chania,Greece DimitriosNiklis ConstantinZopounidis DepartmentofAccountingandFinance SchoolofProductionEngineering WesternMacedoniaUniversity andManagement ofAppliedSciences TechnicalUniversityofCrete Kozani,Greece Chania,Greece AudenciaBusinessSchool InstituteofFinance Nantes,France ISSN2364-687X ISSN2364-6888 (electronic) EUROAdvancedTutorialsonOperationalResearch ISBN978-3-319-99410-9 ISBN978-3-319-99411-6 (eBook) https://doi.org/10.1007/978-3-319-99411-6 LibraryofCongressControlNumber:2018953645 ©SpringerNatureSwitzerlandAG2019 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpart of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation,broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionor informationstorageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilar methodologynowknownorhereafterdeveloped. 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ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland Preface Overthepastfewdecades,thefinancialsectorhasbeenundercontinuouschangesin all areas of designing, implementing, and managing the services and products provided to consumers, firms, and investors. One of the most notable changes involves the extensive use of analytical modeling techniques for financial decision making and risk management. Financial models not only provide the basis for describing financial phenomena in a normative context, but they further provide prescriptivesupportindesigningactionstospecificdecisioninstances. Among the many areas of financial decision making, credit risk modeling has attractedalotofinterestamongacademicsandpractitioners.Theexpansionofcredit over the years for consumers and corporations creates a lot of challenges for measuring and managing the risks that the rising debt burden poses. Naturally, financial institutions providing credit are the ones most interested in analytical toolsforcreditriskmanagement.Thesamealsoappliestothenon-financialsector, giventhatalmostalltypesofcorporationsrelyonprovidingcredittocustomersand obtaining credit by creditors. The rising debt burden for households further high- lights theimportanceofcredit risk forindividualconsumers. Moreover,regulatory authorities and supervisors are heavily interested in assessing and monitoring the creditriskexposuresforfinancialinstitutions,corporations,andthewholeeconomy. The measurement and management of credit risk has attracted a lot of interest over the years, not only in terms of regulatory procedures, but also as far as it concernstheuseofsophisticatedanalyticalmodelsandnewtechnologies.Thisbook focuses onmodels and systems for creditrisk scoring and rating. Such approaches arefundamentalingredientsofcreditriskmanagementsystems,providingestimates abouttherisklevelandcreditworthinessofconsumerandcorporateborrowers.The aim of the book is to provide an overview of this field, the main techniques and modeling approaches for constructing credit risk analysis systems, the validation procedures,aswellastheirimplementationinactualinstances.Moreover,thebook also discusses the framework underlying the design and development of credit scoring/rating and risk assessment models. The approaches presented in this book cover both traditional financial models as well as data-driven empirical systems v vi Preface basedonanalyticalmethodologiesfromoperationsresearch,decisionanalysis,and artificialintelligence. Thepresentationismadeinawaythatisaccessibletoreaderswhomaynothave strongfinancialoranalyticalbackground.Thus,thebookintroducesthereadertothe main ideas and techniques in an accessible manner, while also covering the recent state-of-the-artadvancesintheliterature. The book is organized into five chapters. Chapter 1 covers the fundamentals of creditriskmodeling,thestatusofthisarea,theregulatorycontext,aswellassome keyfinancialmodelsforcreditriskassessment.Chapter2providesanintroductionto credit scoring and rating systems, including issues such as modeling aspects, data requirements, and the framework for developing and testing such models and systems.Chapter3presentsanoverviewofdifferentanalyticalmodelingtechniques from various fields, such as statistical models, machine learning, and multicriteria decisionaid.Performancemeasurementissuesarealsodiscussed.Chapter4presents applications of analytical models tocorporate and consumer creditrisk assessment and illustrates comparative results and the insights that such models provide. The book closes with Chap. 5, which focuses on a discussion of some important open issuesforfutureresearchinthisarea. Chania,Greece MichalisDoumpos June2018 ChristosLemonakis DimitriosNiklis ConstantinZopounidis Contents 1 IntroductiontoCreditRiskModelingandAssessment. . . . . . . . . . . 1 1.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 CreditRiskManagementforFinancialInstitutions. . . . . . . . . . . . 4 1.3 UncertaintiesandRiskFactors. . . . . . . .. . . . . . . . . . . . . . . . .. . 5 1.4 ElementsofCreditRiskModeling. . . . . . . . . . . . . . . . . . . . . . . . 7 1.5 TheRegulatoryFrameworkforFinancialInstitutions. . . . . . . . . . 8 1.6 TypesofCreditRiskAssessmentApproaches. . . . . . . . . . . . . . . 10 1.6.1 JudgmentalApproaches. . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.6.2 Data-DrivenEmpiricalModels. . . . . . . . . . . . . . . . . . . . . 12 1.6.3 FinancialModels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 1.7 MeasuringtheFinancialPerformanceofLoans. . . . . . . . . . . . . . . 18 1.8 NotesandReferences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 2 CreditScoringandRating. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.2 TheContextsofCreditScoringandRatingSystems. . . . . . . . . . . 25 2.2.1 ThroughtheCycleandPointinTimeAssessments. . . . . . 25 2.2.2 IssuerRatingsandIssue-SpecificRatings. . . . . . . . . . . . . 25 2.2.3 BehavioralandProfitScoring. . . . . . . . . . . . . . . . . . . . . . 26 2.2.4 SocialLending. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.3 ModelingRequirements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.4 DevelopmentProcess. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 2.4.1 DataCollectionandPre-processing. . . . . . . . . . . . . . . . . . 29 2.4.2 ModelFitting. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 2.4.3 ModelValidation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 2.4.4 DefinitionandValidationofRatings. . . . . . . . . . . . . . . . . 36 2.4.5 Implementation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 2.5 CreditRatingAgencies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 2.6 NotesandReferences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 vii viii Contents 3 DataAnalyticsforDevelopingandValidatingCreditModels. . . . . . 43 3.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 3.2 ModelingApproaches. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.2.1 StatisticalModels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.2.2 MachineLearning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.2.3 OptimizationApproaches. . . . . . . . . . . . . . . . . . . . . . . . . 58 3.2.4 MulticriteriaDecisionAiding. . . . . . . . . . . . . . . . . . . . . . 62 3.3 PerformanceMeasures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 3.3.1 MisclassificationCosts. . . . . . . . . . . . . . . . . . . . . . . . . . . 68 3.3.2 ClassificationAccuracies. . . . . . . . . . . . . . . . . . . . . . . . . 69 3.3.3 ReceiverOperatingCharacteristicCurve. . . . . . . . . . . . . . 71 3.3.4 Kolmogorov-SmirnovDistance. . . . . . . . . . . . . . . . . . . . . 73 3.4 NotesandReferences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 4 ApplicationstoCorporateDefaultPredictionandConsumerCredit. . . 77 4.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 4.2 PredictionofCorporateDefaults. . . . . . . . . . . . . . . . . . . . . . . . . 77 4.2.1 DataDescription. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 4.2.2 SelectionofVariables. . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.2.3 AnalyticalApproachesforPredictiveModeling. . . . . . . . . 84 4.2.4 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 4.3 RetailBanking. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 4.3.1 ClusteringTechniques. . . . . . . . . . . . . . . . . . . . . . . . . . . 90 4.3.2 ApplyingClusterAnalysistoCreditRiskAssessment. . . . 92 4.3.3 DataandVariables. . .. . . . .. . . .. . . .. . . .. . . . .. . . .. 93 4.3.4 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 4.3.5 Perspectives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 4.4 NotesandReferences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 5 ConclusionsandFutureResearch. . . . . . . . . . . . . . . . . . . . . . . . . . . 99 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Index. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Chapter 1 Introduction to Credit Risk Modeling and Assessment 1.1 Introduction Creditisafundamentaltoolforfinancialtransactionsintheprivateandpublicsector, involvingbothcorporationsandconsumers.Creditprovidestheliquidityneededto developall forms ofeconomicactivity, aswell asfundingsourcesfor dailyopera- tions and long-term investments. While credit has a long history that dates to the earlydatesofcivilization,overthepastdecadesithasundergonemajorchanges,not onlyintermsofitsvolume,butalsoasfarasitconcernsthechannelsthroughwhich credit is provided, the types of credit that are available, as well as the regulatory frameworkthatdefineshowcreditisprovided. Inthisnewcontext,theriskthatisassociatedwithprovidingcredithasbecomea majorpointofconcernforallorganizationsthatareinvolvedwithcredittransactions and their supervision. In simple terms, credit risk refers to the likelihood that a borrower(obligor)willnotmeetfuturedebtobligationsinaccordancewiththeterms agreedwhencreditwasprovidedbyalender. Typically,creditriskisconsideredinthecontextoffinancialinstitutions,suchas banks,thatprovidecredittotheircustomersintheformofcorporateandconsumer loans.However,creditriskisalsorelevantforthenon-financialsector.Forexample, in their daily operation, firms in industry and commerce, receive credit from their suppliersandprovidecredittotheircustomers.Firmscollaboratingwithpartnersof low creditworthiness may face severe financial and operating difficulties, in case theirsuppliersorcustomersfacefinancialdistressandfailure. Table1.1providessomeillustrativedataderivedfromtheBankofInternational Settlements, on the expansion of credit to the private non-financial sector (non-financial corporations and households-HHs) in the Eurozone area and USA, betweenthebeginningof2000andtheendof2016.IntheEurozone,thetotalcredit (inabsoluteterms,i.e.,ineuros)increasedby105.5%,reaching17,481billioneuros. The increasewas even higher in theUSA (123.5%),wherethe total credit in 2016 ©SpringerNatureSwitzerlandAG2019 1 M.Doumposetal.,AnalyticalTechniquesintheAssessmentofCreditRisk,EURO AdvancedTutorialsonOperationalResearch, https://doi.org/10.1007/978-3-319-99411-6_1
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