<strong>Rating</strong> <strong>Models</strong> <strong>and</strong> <strong>Validation</strong> Financial Services Authority (FSA), Report <strong>and</strong> first consultation on the implementation of the new Basel <strong>and</strong> EU Capital Adequacy St<strong>and</strong>ards, Consultation Paper 189, July 2003 (Report <strong>and</strong> first consultation) Fu‹ ser, Karsten, Mittelst<strong>and</strong>srating mit Hilfe neuronaler Netzwerke, in: <strong>Rating</strong> — Chance fu‹r den Mittelst<strong>and</strong> nach Basel II, Everling, Oliver (ed.), Wiesbaden 2001, 363—386 (Mittelst<strong>and</strong>srating mit Hilfe neuronaler Netze) Gerdsmeier, S./Krob, Bernhard, Kundenindividuelle Bepreisung des Ausfallrisikos mit dem Optionspreismodell, Die Bank 1994, No. 8; 469—475 (Bepreisung des Ausfallrisikos mit dem Optionspreismodell) Hamerle/Rauhmeier/Ro‹ sch, Uses <strong>and</strong> misuses of measures for credit rating accuracy, Universita‹t Regensburg, preprint 2003 (Uses <strong>and</strong> misuses of measures for credit rating accuracy) Hartung, Joachim/Elpelt, Ba‹rbel, Multivariate Statistik, 5th ed., Munich 1995 (Multivariate Statistik) Hastie/Tibshirani/Friedman, The elements of statistical learning, Springer 2001 (Elements of statistical learning) Heitmann, Christian, Beurteilung der Best<strong>and</strong>festigkeit von Unternehmen mit Neuro-Fuzzy, Frankfurt am Main 2002 (Neuro-Fuzzy) Jansen, Sven, Ertrags- und volatilita‹tsgestu‹tzte Kreditwu‹rdigkeitspru‹fung im mittelsta‹ndischen Firmenkundengescha‹ft der Banken; Vol. 31 of the ÒSchriftenreihe des Zentrums fu‹r Ertragsorientiertes Bankmanagement in Mu‹nster,Ó Rolfes, B./Schierenbeck, H. (eds.), Frankfurt am Main (Ertrags- und volatilita‹tsgestu‹tzte Kreditwu‹rdigkeitspru‹fung) Jerschensky, Andreas, Messung des Bonita‹tsrisikos von Unternehmen: Krisendiagnose mit Ku‹nstlichen Neuronalen Netzen, Du‹sseldorf 1998 (Messung des Bonita‹tsrisikos von Unternehmen) Kaltofen, Daniel/Mo‹ llenbeck, Markus/Stein, Stefan, Gro§e Inspektion: Risikofru‹herkennung im Kreditgescha‹ft mit kleinen und mittleren Unternehmen, Wissen und H<strong>and</strong>eln 02, http://www.ruhr-uni-bochum.de/ikf/wissenuþndhłł <strong>and</strong>eln.htm (Risikofru‹herkennung im Kreditgescha‹ft mit kleinen und mittleren Unternehmen) Keenan/Sobehart, Performance Measures for Credit Risk <strong>Models</strong>, MoodyÕs Research Report #1-10-10- 99 (Performance Measures) Kempf, Markus, Geldanlage: Dem wahren Aktienkurs auf der Spur, in Financial Times Deutschl<strong>and</strong>, May 9, 2002 (Dem wahren Aktienkurs auf der Spur) Kirm§e, Stefan, Die Bepreisung und Steuerung von Ausfallrisiken im Firmenkundengescha‹ft der Kreditinstitute — Ein optionspreistheoretischer Ansatz, Vol. 10 of the ÒSchriftenreihe des Zentrums fu‹r Ertragsorientiertes Bankmanagement in Mu‹nster,Ó Rolfes, B./Schierenbeck, H. (eds.), Frankfurt am Main 1996 (Optionspreistheoretischer Ansatz zur Bepreisung) Kirm§e, Stefan/Jansen, Sven, BVR-II-<strong>Rating</strong>: Das verbundeinheitliche <strong>Rating</strong>system fu‹r das mittelsta‹ndische Firmenkundengescha‹ft, in: Bankinformation 2001, No. 2, 67—71 (BVR-II-<strong>Rating</strong>) Lee, Wen-Chung, Probabilistic Analysis of Global Performances of Diagnostic Tests: Interpreting the Lorenz Curve-based Summary Measures, Stat. Med. 18 (1999) 455 (Global Performances of Diagnostic Tests) Lee, Wen-Chung/Hsiao, Chuhsing Kate, Alternative Summary Indices for the Receiver Operating Characteristic Curve, Epidemiology 7 (1996) 605 (Alternative Summary Indices) Murphy, A. H., Journal of Applied Meteorology, 11 (1972), 273—282 (Journal of Applied Meteorology) Sachs, L., Angew<strong>and</strong>te Statistik, 9th ed., Springer 1999 (Angew<strong>and</strong>te Statistik) Schierenbeck, H., Ertragsorientiertes Bankmanagement, Vol. 1: Grundlagen, Marktzinsmethode und Rentabilita‹ts-Controlling, 6th ed., Wiesbaden 1999 (Ertragsorientiertes Bankmanagement Vol. 1) Sobehart/Keenan/Stein, <strong>Validation</strong> methodologies for default risk models, MoodyÕs, preprint 05/2000 (<strong>Validation</strong> Methodologies) 168 Guidelines on Credit Risk Management
Stuhlinger, Matthias, Rolle von <strong>Rating</strong>s in der Firmenkundenbeziehung von Kreditgenossenschaften, in: <strong>Rating</strong> — Chance fu‹r den Mittelst<strong>and</strong> nach Basel II, Everling, Oliver (ed.), Wiesbaden 2001, 63—78 (Rolle von <strong>Rating</strong>s in der Firmenkundenbeziehung von Kreditgenossenschaften) Tasche, D., A traffic lights approach to PD validation, Deutsche Bundesbank, preprint (A traffic lights approach to PD validation) Thun, Christian, Entwicklung von Bilanzbonita‹tsklassifikatoren auf der Basis schweizerischer Jahresabschlu‹sse, Hamburg 2000 (Entwicklung von Bilanzbonita‹tsklassifikatoren) Varnholt, B., Modernes Kreditrisikomanagement, Zurich 1997 (Modernes Kreditrisikomanagement) Zhou, C., Default correlation: an analytical result, Federal Reserve Board, preprint 1997 (Default correlation: an analytical result) <strong>Rating</strong> <strong>Models</strong> <strong>and</strong> <strong>Validation</strong> Guidelines on Credit Risk Management 169
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≈√ Guidelines on Credit Risk Ma
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The ongoing development of contempo
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5 Developing a Rating Model 60 5.1
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Rating Models and Validation I INTR
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This segmentation from the business
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The best-practice segmentation pres
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Chart 2: Data Requirements for Gove
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2.2 Financial Service Providers In
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Insurance Companies Due to their di
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Capital Market-Oriented/Internation
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— Market prospects are not assess
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Chart 5: Data Requirements for Corp
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elationships in the project, these
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Before the Project As the repayment
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Chart 6: Data Requirements for Reta
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During the Credit Term Instead of o
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3.1 Heuristic Models Heuristic mode
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Chart 9: Information Categories for
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Explanatory Component The explanato
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This example defines linguistic ter
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ments as to whether higher or lower
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Chart 16: Indicators in the ÒCrebo
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Logistic regression has a number of
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adapts the network according to any
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The parameters required to calculat
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ture of the borrowerÕs creditworth
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Chart 24: Vertical Linking of Ratin
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e necessary in this case if the def
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4.1.5 Consistency Heuristic models
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Compared to heuristic models, stati
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the data set and statistical testin
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data collection procedure. This pro
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full surveys is often too high, esp
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essential structural characteristic
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For each block, interim objectives
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Chart 34: Creating the Analysis Dat
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Chart 35: Creating the Analysis and
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Once a quality-assured data set has
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an indicator should only be used in
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Transformation of Indicators In ord
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the scoring functions developed usi
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Chart 37: Significance of Quantitat
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— For all other statistical and h
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of approximately 10 intervals shoul
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With regard to the time interval be
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around the main diagonal, however,
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tial increase in marginal default r
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Chart 46: Aspects of Rating Model V
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— Model development procedure Mod
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and bad refer to whether a credit d
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numbers of cases per class observed
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Chart 54: Depiction of a and b erro
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Chart 57: Shape of the a—b Error
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Interpretation of the Pietra Index
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The following relation applies to t
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Chart 62: ROC Curve with Simultaneo
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Chart 65: Interpretation of the Bay
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The table below (chart 67) shows a
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- Page 167: IV REFERENCES Backhaus, Klaus/Erich
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