A one-stop guide for the theories, applications, and
statistical methodologies essential to operational risk
Providing a complete overview of operational risk modeling and
relevant insurance analytics, Fundamental Aspects of Operational
Risk and Insurance Analytics: A Handbook of Operational Risk
offers a systematic approach that covers the wide range of topics
in this area. Written by a team of leading experts in the field,
the handbook presents detailed coverage of the theories,
applications, and models inherent in any discussion of the
fundamentals of operational risk, with a primary focus on Basel
II/III regulation, modeling dependence, estimation of risk models,
and modeling the data elements.
Fundamental Aspects of Operational Risk and Insurance Analytics:
A Handbook of Operational Risk begins with coverage on the four
data elements used in operational risk framework as well as
processing risk taxonomy. The book then goes further in-depth into
the key topics in operational risk measurement and insurance, for
example diverse methods to estimate frequency and severity models.
Finally, the book ends with sections on specific topics, such as
scenario analysis; multifactor modeling; and dependence modeling. A
unique companion with Advances in Heavy Tailed Risk Modeling: A
Handbook of Operational Risk, the handbook also features:
* Discussions on internal loss data and key risk indicators,
which are both fundamental for developing a risk-sensitive
framework
* Guidelines for how operational risk can be inserted into a
firm's strategic decisions
* A model for stress tests of operational risk under the United
States Comprehensive Capital Analysis and Review (CCAR)
program
A valuable reference for financial engineers, quantitative
analysts, risk managers, and large-scale consultancy groups
advising banks on their internal systems, the handbook is also
useful for academics teaching postgraduate courses on the
methodology of operational risk.
Autorentext
Marcelo G. Cruz, PhD, is Adjunct Professor at New York University and a world-renowned consultant on operational risk modeling and measurement. He has written and edited several books in operational risk, and is Founder and Editor-in-Chief of The Journal of Operational Risk.
Gareth W. Peters, PhD, is Assistant Professor in the Department of Statistical Science, Principle Investigator in Computational Statistics and Machine Learning, and Academic Member of the UK PhD Centre of Financial Computing at University College London. He is also Adjunct Scientist in the Commonwealth Scientific and Industrial Research Organisation, Australia; Associate Member Oxford-Man Institute at th Oxford University; and Associate Member in the Systemic Risk Centre at the London School of Economics.
Pavel V. Shevchenko, PhD, is Senior Principal Research Scientist in the Commonwealth Scientific and Industrial Research Organisation, Australia, as well as Adjunct Professor at the University of New South Wales and the University of Technology, Sydney. He is also Associate Editor of The Journal of Operationa Risk. He works on research and consulting projects in the area of financial risk and the development of relevant numerical methods and software, has published extensively in academic journals, consults for major financial institutions, and frequently presents at industry and academic conferences.
Zusammenfassung
A one-stop guide for the theories, applications, and statistical methodologies essential to operational risk
Providing a complete overview of operational risk modeling and relevant insurance analytics, Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk offers a systematic approach that covers the wide range of topics in this area. Written by a team of leading experts in the field, the handbook presents detailed coverage of the theories, applications, and models inherent in any discussion of the fundamentals of operational risk, with a primary focus on Basel II/III regulation, modeling dependence, estimation of risk models, and modeling the data elements.
Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk begins with coverage on the four data elements used in operational risk framework as well as processing risk taxonomy. The book then goes further in-depth into the key topics in operational risk measurement and insurance, for example diverse methods to estimate frequency and severity models. Finally, the book ends with sections on specific topics, such as scenario analysis; multifactor modeling; and dependence modeling. A unique companion with Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk, the handbook also features:
- Discussions on internal loss data and key risk indicators, which are both fundamental for developing a risk-sensitive framework
- Guidelines for how operational risk can be inserted into a firm's strategic decisions
- A model for stress tests of operational risk under the United States Comprehensive Capital Analysis and Review (CCAR) program
A valuable reference for financial engineers, quantitative analysts, risk managers, and large-scale consultancy groups advising banks on their internal systems, the handbook is also useful for academics teaching postgraduate courses on the methodology of operational risk.
Inhalt
Preface xvii
Acronyms xix
List of Distributions xxi
1 OpRisk in Perspective 1
1.1 Brief History 1
1.2 Risk-Based Capital Ratios for Banks 5
1.3 The Basic Indicator and Standardized Approaches for OpRisk 9
1.4 The Advanced Measurement Approach 10
1.4.1 Internal Measurement Approach 11
1.4.2 Score Card Approach 11
1.4.3 Loss Distribution Approach 12
1.4.4 Requirements for AMA 13
1.5 General Remarks and Book Structure 16
2 OpRisk Data and Governance 17
2.1 Introduction 17
2.2 OpRisk Taxonomy 17
2.2.1 Execution, Delivery, and Process Management 19
2.2.2 Clients, Products, and Business Practices 21
2.2.3 Business Disruption and System Failures 22
2.2.4 External Frauds 23
2.2.5 Internal Fraud 23
2.2.6 Employment Practices and Workplace Safety 24
2.2.7 Damage to Physical Assets 25
2.3 The Elements of the OpRisk Framework 25
2.3.1 Internal Loss Data 26
2.3.2 Setting a Collection Threshold and Possible Impacts 26
2.3.3 Completeness of Database (Under-reporting Events) 27
2.3.4 Recoveries and Near Misses 27
2.3.5 Time Period for Resolution of Operational Losses 28
2.3.6 Adding Costs to Losses 28
2.3.7 Provisioning Treatment of Expected Operational Losses 28
2.4 Business Environment and Internal Control Environment Factors (BEICFs) 29
2.4.1 Risk Control Self-Assessment (RCSA) 29
2.4.2 Key Risk Indicators 31
2.5 External Databases 33
2.6 Scenario Analysis 34
2.7 OpRisk Profile in Different Financial Sectors 37
2.7.1 Trading and Sales 37
2.7.2 Corporate Finance 38
2.7.3 Retail Banking 38
2.7.4 Insurance 39
2.7.5 Asset Management 40
2.7.6 Retail Brokerage 42
2.8 Risk Organization and Governance 43
2.8.1 Organization of Risk Departments 44
2.8.2 Structuring a Firm Wide Policy: Example of an OpRisk Policy 46
2.8.3 Governance 47
3 Using OpRisk Data for Business Analysis 48
3.1 Cost Reduction Programs in Financial Firms 49
3.2 Using OpRisk Data to Perform Business Analysis 53
3.2.1 The Risk of …