Operational risk modeling in financial services the exposure, occurrence, impact method
Transform your approach to oprisk modelling with a proven, non-statistical methodology Operational Risk Modeling in Financial Services provides risk professionals with a forward-looking approach to risk modelling, based on structured management judgement over obsolete statistical methods. Proven ove...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Chichester, West Sussex, United Kingdom
John Wiley & Sons Ltd
2019
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| Series: | Wiley finance series
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| Subjects: | |
| Online Access: | |
| Collection: | O'Reilly - Collection details see MPG.ReNa |
Table of Contents:
- Includes bibliographical references and index
- 7.2 Measuring Risk or Measuring Risks?7.3 Requirements of a Risk Measurement Method; 7.4 Risk Measurement Practices; Part Three The Practice of Operational Risk Management; Chapter 8 Risk and Control Self-Assessment; 8.1 Introduction; 8.2 Risk and Control Identification; 8.3 Risk and Control Assessment; Chapter 9 Losses Modelling; 9.1 Loss Distribution Approach; 9.2 Loss Regression; Chapter 10 Scenario Analysis; 10.1 Scope of Scenario Analysis; 10.2 Scenario Identification; 10.3 Scenario Assessment; Part Four The Exposure, Occurrence, Impact Method; Chapter 11 An Exposure-Based Model
- 14.2 Quantification14.3 Simulation; Chapter 15 A Scenario in Internal Fraud; 15.1 Introduction; 15.2 XOI Modelling; Chapter 16 A Scenario in Cyber Risk; 16.1 Definition; 16.2 XOI Modelling; Chapter 17 A Scenario in Conduct Risk; 17.1 Definition; 17.2 Types of Misconduct; 17.3 XOI Modelling; Chapter 18 Aggregation of Scenarios; 18.1 Introduction; 18.2 Influence of a Scenario on an Environment Factor; 18.3 Influence of an Environment Factor on a Scenario; 18.4 Combining the Influences; 18.5 Turning the Dependencies into Correlations; Chapter 19 Applications; 19.1 Introduction
- 11.1 A Tsunami Is Not an Unexpectedly Big Wave11.2 Using Available Knowledge to Inform Risk Analysis; 11.3 Structured Scenarios Assessment; 11.4 The XOI Approach: Exposure, Occurrence, and Impact; Chapter 12 Introduction to Bayesian Networks; 12.1 A Bit of History; 12.2 A Bit of Theory; 12.3 Influence Diagrams and Decision Theory; 12.4 Introduction to Inference in Bayesian Networks; 12.5 Introduction to Learning in Bayesian Networks; Chapter 13 Bayesian Networks for Risk Measurement; 13.1 An Example in Car Fleet Management; Chapter 14 The XOI Methodology; 14.1 Structure Design
- Cover; Title Page; Copyright; Contents; List of Figures; List of Tables; Foreword; Preface; Part One Lessons Learned in 10 Years of Practice; Chapter 1 Creation of the Method; 1.1 From Artificial Intelligence to Risk Modelling; 1.2 Model Losses or Risks?; Chapter 2 Introduction to the XOI Method; 2.1 A Risk Modelling Doctrine; 2.2 A Knowledge Management Process; 2.3 The eXposure, Occurrence, Impact (XOI) Approach; 2.4 The Return of AI: Bayesian Networks for Risk Assessment; Chapter 3 Lessons Learned in 10 Years of Practice; 3.1 Risk and Control Self-Assessment; 3.2 Loss Data
- 3.3 Quantitative Models3.4 Scenarios Workshops; 3.5 Correlations; 3.6 Model Validation; Part Two Challenges of Operational Risk Measurement; Chapter 4 Definition and Scope of Operational Risk; 4.1 On Risk Taxonomies; 4.2 Definition of Operational Risk; Chapter 5 The Importance of Operational Risk; 5.1 The Importance of Losses; 5.2 The Importance of Operational Risk Capital; 5.3 Adequacy of Capital to Losses; Chapter 6 The Need for Measurement; 6.1 Regulatory Requirements; 6.2 Nonregulatory Requirements; Chapter 7 The Challenges of Measurement; 7.1 Introduction