- Page 1 and 2: ≈√ Guidelines on Credit Risk Ma
- Page 3 and 4: The ongoing development of contempo
- Page 5 and 6: 5 Developing a Rating Model 60 5.1
- Page 7 and 8: Rating Models and Validation I INTR
- Page 9 and 10: This segmentation from the business
- Page 11: The best-practice segmentation pres
- Page 15 and 16: 2.2 Financial Service Providers In
- Page 17 and 18: Insurance Companies Due to their di
- Page 19 and 20: Capital Market-Oriented/Internation
- Page 21 and 22: — Market prospects are not assess
- Page 23 and 24: Chart 5: Data Requirements for Corp
- Page 25 and 26: elationships in the project, these
- Page 27 and 28: Before the Project As the repayment
- Page 29 and 30: Chart 6: Data Requirements for Reta
- Page 31 and 32: During the Credit Term Instead of o
- Page 33 and 34: 3.1 Heuristic Models Heuristic mode
- Page 35 and 36: Chart 9: Information Categories for
- Page 37 and 38: Explanatory Component The explanato
- Page 39 and 40: This example defines linguistic ter
- Page 41 and 42: ments as to whether higher or lower
- Page 43 and 44: Chart 16: Indicators in the ÒCrebo
- Page 45 and 46: Logistic regression has a number of
- Page 47 and 48: adapts the network according to any
- Page 49 and 50: The parameters required to calculat
- Page 51 and 52: ture of the borrowerÕs creditworth
- Page 53 and 54: Chart 24: Vertical Linking of Ratin
- Page 55 and 56: e necessary in this case if the def
- Page 57 and 58: 4.1.5 Consistency Heuristic models
- Page 59 and 60: Compared to heuristic models, stati
- Page 61 and 62: 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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The lower the Brier Score is, the b
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Chart 70 shows the reliability diag
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Chart 71: Identification of Signifi
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estimates, which means that it is e
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transition matrix, the data require
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tency of the cumulative and conditi
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to internal back-testing results in
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Changes in correlations One of the
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6.4.3 Developing Stress Tests This
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Counterparty-based and credit facil
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tify decisive factors influencing i
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III ESTIMATING AND VALIDATING LGD/E
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Chart 81: Loss Components in LGD to
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assets, as the danger exists that m
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— Collateral: Collateral value, c
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Chart 87: Overview of Customer Type
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transaction, however, it is also ne
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Implementing an in-house LGD estima
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nents; this is analogous to the use
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those assets which serve as collate
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during the realization period. The
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Chart 91: Example of Segmentation f
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ity of the realization market and t
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The level of utilization for off-ba
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8.3 EAD Estimation Methods As in th
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IV REFERENCES Backhaus, Klaus/Erich
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Stuhlinger, Matthias, Rolle von Rat
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Pytlik, Martin, Diskriminanzanalyse