02654nam 2200457 450 991063405260332120230415200015.09783658401801(electronic bk.)9783658401795(MiAaPQ)EBC7153333(Au-PeEL)EBL7153333(CKB)25610250600041(OCoLC)1354207339(EXLCZ)992561025060004120230415d2022 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierApplication of AI in credit scoring modeling /Bohdan PopovychWiesbaden, Germany :Springer Gabler,[2022]©20221 online resource (93 pages)BestMastersPrint version: Popovych, Bohdan Application of AI in Credit Scoring Modeling Wiesbaden : Springer Fachmedien Wiesbaden GmbH,c2023 9783658401795 Includes bibliographical references.Intro -- Foreword -- Abstract -- Contents -- Abbreviations -- List of Figures -- List of Tables -- 1 Introduction -- 2 Theoretical Concepts of Credit Scoring -- 2.1 Literature Background -- 2.2 Theoretical Overview -- 2.2.1 Definition and Application -- 2.2.2 Advantages and Limitations -- 2.2.3 Comparison of Credit Scoring and Credit Rating -- 2.3 Regulatory Requirements -- 3 Credit Scoring Methodologies -- 3.1 Traditional Credit Scoring Techniques -- 3.1.1 Discriminant Analysis -- 3.1.2 Logistic Regression -- 3.1.3 Expert Systems -- 3.2 Artificial Intelligence Classification Methods -- 3.2.1 Overview of AI Classification Techniques -- 3.2.2 Decision Trees -- 3.2.3 Random Forest -- 3.3 Methods of Model Validation -- 4 Empirical Analysis -- 4.1 Data Analysis -- 4.2 Logistic Regression -- 4.2.1 Model Description -- 4.2.2 Model Interpretation -- 4.2.3 Model Performance -- 4.3 Decision Tree -- 4.3.1 Model Description and Interpretation -- 4.3.2 Model Performance -- 4.4 Random Forest -- 4.4.1 Model Description -- 4.4.2 Model Interpretation -- 4.4.3 Model Performance -- 4.5 Models Comparison -- 5 Conclusion -- References.BestMasters.Artificial intelligenceFinancial applicationsCredit scoring systems. Artificial intelligenceFinancial applications.Credit scoring systems. .332.640285Popovych Bohdan1272154MiAaPQMiAaPQMiAaPQ9910634052603321Application of AI in Credit Scoring Modeling2996527UNINA