Rating Models and Validation - Oesterreichische Nationalbank

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Rating Models and Validation Financial Services Authority (FSA), Report and first consultation on the implementation of the new Basel and EU Capital Adequacy Standards, Consultation Paper 189, July 2003 (Report and first consultation) Fu‹ ser, Karsten, Mittelstandsrating mit Hilfe neuronaler Netzwerke, in: Rating — Chance fu‹r den Mittelstand nach Basel II, Everling, Oliver (ed.), Wiesbaden 2001, 363—386 (Mittelstandsrating 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 and misuses of measures for credit rating accuracy, Universita‹t Regensburg, preprint 2003 (Uses and 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 Bestandfestigkeit 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 Handeln 02, http://www.ruhr-uni-bochum.de/ikf/wissenuþndhłł andeln.htm (Risikofru‹herkennung im Kreditgescha‹ft mit kleinen und mittleren Unternehmen) Keenan/Sobehart, Performance Measures for Credit Risk Models, MoodyÕs Research Report #1-10-10- 99 (Performance Measures) Kempf, Markus, Geldanlage: Dem wahren Aktienkurs auf der Spur, in Financial Times Deutschland, 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-Rating: Das verbundeinheitliche Ratingsystem fu‹r das mittelsta‹ndische Firmenkundengescha‹ft, in: Bankinformation 2001, No. 2, 67—71 (BVR-II-Rating) 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., Angewandte Statistik, 9th ed., Springer 1999 (Angewandte Statistik) Schierenbeck, H., Ertragsorientiertes Bankmanagement, Vol. 1: Grundlagen, Marktzinsmethode und Rentabilita‹ts-Controlling, 6th ed., Wiesbaden 1999 (Ertragsorientiertes Bankmanagement Vol. 1) Sobehart/Keenan/Stein, Validation methodologies for default risk models, MoodyÕs, preprint 05/2000 (Validation Methodologies) 168 Guidelines on Credit Risk Management
Stuhlinger, Matthias, Rolle von Ratings in der Firmenkundenbeziehung von Kreditgenossenschaften, in: Rating — Chance fu‹r den Mittelstand nach Basel II, Everling, Oliver (ed.), Wiesbaden 2001, 63—78 (Rolle von Ratings 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) Rating Models and Validation 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
Page 117 and 118: The lower the Brier Score is, the b
Page 119 and 120: Chart 70 shows the reliability diag
Page 121 and 122: Chart 71: Identification of Signifi
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Page 127 and 128: tency of the cumulative and conditi
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Page 131 and 132: Changes in correlations One of the
Page 133 and 134: 6.4.3 Developing Stress Tests This
Page 135 and 136: Counterparty-based and credit facil
Page 137 and 138: tify decisive factors influencing i
Page 139 and 140: III ESTIMATING AND VALIDATING LGD/E
Page 141 and 142: Chart 81: Loss Components in LGD to
Page 143 and 144: assets, as the danger exists that m
Page 145 and 146: — Collateral: Collateral value, c
Page 147 and 148: Chart 87: Overview of Customer Type
Page 149 and 150: transaction, however, it is also ne
Page 151 and 152: Implementing an in-house LGD estima
Page 153 and 154: nents; this is analogous to the use
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Page 157 and 158: during the realization period. The
Page 159 and 160: Chart 91: Example of Segmentation f
Page 161 and 162: ity of the realization market and t
Page 163 and 164: The level of utilization for off-ba
Page 165 and 166: 8.3 EAD Estimation Methods As in th
Page 167: IV REFERENCES Backhaus, Klaus/Erich
Page 171 and 172: Pytlik, Martin, Diskriminanzanalyse
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