| Description |
1 online resource |
| Series |
Wiley finance series |
|
Wiley finance series.
|
| Note |
Includes index. |
| Contents |
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 |
|
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 |
|
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 |
|
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 |
| Summary |
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 over a decade's use in significant banks and financial services firms in Europe and the US, the Exposure, Occurrence, Impact (XOI) method of operational risk modelling played an instrumental role in reshaping their oprisk modelling approaches; in this book, the expert team that developed this methodology offers practical, in-depth guidance on XOI use and applications for a variety of major risks. The Basel Committee has dismissed statistical approaches to risk modelling, leaving regulators and practitioners searching for the next generation of oprisk quantification. The XOI method is ideally suited to fulfil this need, as a calculated, coordinated, consistent approach designed to bridge the gap between risk quantification and risk management. This book details the XOI framework and provides essential guidance for practitioners looking to change the oprisk modelling paradigm.-Survey the range of current practices in operational risk analysis and modelling -Track recent regulatory trends including capital modelling, stress testing and more -Understand the XOI oprisk modelling method, and transition away from statistical approaches -Apply XOI to major operational risks, such as disasters, fraud, conduct, legal and cyber risk The financial services industry is in dire need of a new standard - a proven, transformational approach to operational risk that eliminates or mitigates the common issues with traditional approaches. Operational Risk Modeling in Financial Services provides practical, real-world guidance toward a more reliable methodology, shifting the conversation toward the future with a new kind of oprisk modelling. |
| Bibliography |
Includes bibliographical references and index. |
| Subject |
Financial services industry -- Risk management.
|
|
Banks and banking -- Risk management.
|
|
Financial risk management.
|
|
Services financiers -- Gestion du risque. |
|
Finances -- Gestion du risque. |
|
Financial risk management |
| Added Author |
Condamin, Laurent, author.
|
| Other Form: |
Print version: Naïm, Patrick. Operational risk modeling in financial services. Chichester, West Sussex, United Kingdom : John Wiley & Sons, [2019] 9781119508502 (DLC) 2018058857 |
| ISBN |
9781119508540 (electronic book) |
|
1119508541 (electronic book) |
|
9781119508557 (electronic book) |
|
111950855X (electronic book) |
|
9781119508434 (electronic book) |
|
1119508436 (electronic book) |
|
(hardcover) |
|
More Resources