Implementation of an IRB-Compliant Rating System

Sebastian Fritz, Michael Luxenburger and Thomas Miehe

Contents
1.

Development and Validation of Key Estimates for Capital Models

2.

Explaining the Correlation in Basel II: Derivation and Evaluation

3.

Explaining the Credit Risk Elements in Basel II

4.

Loss Given Default and Recovery Risk: From Basel II Standards to Effective Risk Management Tools

5.

Assessing the Validity of Basel II Models in Measuring Risk of Credit Portfolios

6.

Measuring Counterparty Credit Risk for Trading Products under Basel II

7.

Implementation of an IRB-Compliant Rating System

8.

Stress Tests of Banks’ Regulatory Capital Adequacy: Application to Tier 1 Capital and to Pillar 2 Stress Tests

9.

Advanced Credit Model Performance Testing to Meet Basel Requirements: How Things Have Changed!

10.

Designing and Implementing a Basel II Compliant PIT–TTC Ratings Framework

11.

Basel II in the Light of Moody’s KMV Evidence

12.

Basel II Capital Adequacy Rules for Retail Exposures

13.

IRB-Compliant Models in Retail Banking

14.

Basel II Capital Adequacy Rules for Securitisations

15.

Regulatory Priorities and Expectations in the Implementation of the IRB Approach

16.

Market Discipline and Appropriate Disclosure in Basel II

17.

Validation of Banks’ Internal Rating Systems – A Supervisory Perspective

18.

Rebalancing the Three Pillars of Basel II

19.

Implementing a Basel II Scenario-Based AMA for Operational Risk

20.

Loss Distribution Approach in Practice

21.

An Operational Risk Rating Model Approach to Better Measurement and Management of Operational Risk

22.

Constructing an Operational Event Database

23.

Insurance and Operational Risk

INTRODUCTION

Numerous publications exist regarding Basel II and the related issue on credit rating, but they concentrate on very specific topics. Our objective in this chapter is to compile all aspects that are relevant to the implementation of a rating system, which is compliant with Basel II. We start with general considerations on the assessment horizon, data quality and default definition, describe several measures for the separation power, and the assignment of probabilities of default (PD).11The separation power (also called discriminative power) describes how well a rating model discriminates between defaulting and non-defaulting customers.

We then elaborate how to derive rating methodologies based on econometric approaches, expert systems and hybrid systems. Using these techniques, we then explain how to derive ratings for retail, corporate, bank, (sub-) sovereign exposure and specialised lending.22The asset-class sub-sovereign includes federal states, regions and municipalities.

A separate section describes the additional risk components such as exposure at default (EAD) and loss given default (LGD) and how to come up with a calibration and validation for the advanced

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