Loss Distribution Approach in Practice

Antoine Frachot, Olivier Moudoulaud and Thierry Roncalli

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

Intense research has been conducted over the past few years to address issues raised by the practical implementation of the advanced measurement approaches (AMA), in particular the loss distribution approach (LDA), presented in the Basel II proposals. Indeed, we believe that most of these issues are now sufficiently clarified to allow for a survey on operational risk quantitative techniques. This is the aim of this chapter.

The roots of quantitative LDA come from actuarial techniques that have been used by the insurance industry for a number of years. It is, of course, a very natural idea, apart from the fact that actuarial techniques could not be imported directly without due regard for the specific needs of operational risks, most notably the reporting bias and the paucity of data. Quantitative people who have looked closely at empirical data will agree that these two features about OpRisk data have a dramatic impact on capital charge. However, these two facets about data cannot be neglected altogether even though they introduce greater complexities and more sophisticated computations than most practitioners prefer.

This chapter aims to describe how a full loss

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