Lieferung vom Verlag mit leichten Qualitätsmängeln möglich

Autorentext

Kirsten Mitchell-Wallace, PhD is EMEA Regional Head of Catastrophe Management at SCOR, Zürich, Switzerland Matthew Jones, PhD is Director at Cat Risk Intelligence, UK John Hillier, PhD is Senior Lecturer in Physical Geography at Loughborough University, Loughborough, UK Matthew Foote is Group Head of Exposure Management at Argo Group International Holdings, London, UK

Inhalt

List of Contributors and Acknowledgements xiii

Foreword xxv

1 Fundamentals 1
*Matthew Jones, Kirsten Mitchell-Wallace, Matthew Foote, and John Hillier*

1.1 Overview 1

1.1.1 What Is Included 1

1.1.2 What Is Not Included 1

1.1.3 Why Read This Chapter? 1

1.2 Catastrophes, Risk Management and Insurance 2

1.3 What Are Catastrophe Models? 5

1.4 Why Do We Need Catastrophe Models? 6

1.5 History of Catastrophe Models 7

1.6 Who Provides and Uses Catastrophe Models? 10

1.7 What Are Catastrophe Models Used For? 11

1.8 Anatomy of a Catastrophe Model 12

1.8.1 Hazard 13

1.8.2 Vulnerability 14

1.8.3 Exposure 15

1.8.4 Loss and Financial Perspectives 15

1.8.5 Platform 17

1.9 Model Input 19

1.9.1 Exposure 20

1.9.2 Financial Structure 24

1.9.3 Portfolio Hierarchy 25

1.10 Model Output: Metrics and Risk Measures 26

1.10.1 Common Metrics 26

1.10.2 Exceedance probability curve characteristics 27

1.10.3 More Advanced Metrics 29

1.10.4 Event Loss Tables and Year Loss Tables 29

1.10.5 Event Loss Table (ELT) 29

1.10.6 Year Loss Table (YLT) 36

1.11 Statistical Basics for Catastrophe Modelling 38

1.11.1 Discrete Distributions 40

1.11.2 Continuous Distributions 42

1.11.3 Coherent Risk Measures 44

Notes 44

References 45

2 Applications of Catastrophe Modelling 47
*Kirsten Mitchell-Wallace*

2.1 Overview 47

2.1.1 What Is Included 48

2.1.2 What Is Not Included 48

2.1.3 Why Read This Chapter? 48

2.2 Introduction 48

2.3 Risk Transfer, the Structure of the (Re)insurance Industry and Catastrophe Modelling 49

2.4 Insurance and Reinsurance 52

2.4.1 What Is Insurance? 52

2.4.2 What Is Reinsurance? 53

2.5 Catastrophe Risk Management and Catastrophe Modelling 60
Kirsten Mitchell-Wallace and Matthew Foote

2.5.1 What Are Catastrophe Risk Management and Exposure Management? 60

2.5.2 Catastrophe Risk Management Metrics 61

2.5.3 Catastrophe Risk Management Data 62

2.5.4 Exposure Data 63

2.5.5 Common Tools Used in Catastrophe Risk Management 70

2.6 Underwriting and Pricing 70
Kirsten Mitchell-Wallace and Matthew Jones

2.6.1 What Is Underwriting? 70

2.6.2 What Is Pricing? 73

2.6.3 Practicalities of Using Catastrophe Model Output for Pricing 81

2.6.4 Pricing Specifics for Insurance and Reinsurance 83

2.7 Accumulation, Roll-Up and Capacity Monitoring 97
Claire Crerar and Kirsten Mitchell-Wallace

2.7.1 What Is Accumulation? 97

2.7.2 Use in Underwriting and Risk Management 101

2.7.3 Practicalities of Accumulation 104

2.8 Portfolio Management and Optimization 105
Kirsten Mitchell-Wallace and Guillermo Franco

2.8.1 What Is Portfolio Management? 105

2.8.2 What Is Portfolio Optimization? 107

2.8.3 Using Catastrophe Models in Optimization 108

2.8.4 Optimization Methods 109

2.9 Event Response and Integration with Claims Team 111
Kirsten Mitchell-Wallace

2.9.1 Early Estimation of Claims 111

2.9.2 Claims Stresses and Inflation 114

2.9.3 Lessons Learnt Analysis 115

2.10 Capital Modelling, Management and Dynamic Financial Analysis 116
Junaid Seria

2.10.1 Risk Appetite and Risk Tolerance 116

2.10.2 Why Capital Models? 117

2.10.3 What Is a Capital Model? 118

2.10.4 The Structure of Capital Models 118

2.10.5 Capital Models and Catastrophe Models 120

2.10.6 What is Dynamic Financial Analysis (DFA)? 120

2.11 Regulation and Best Practice in Catastrophe Modelling 121
Junaid Seria, Claire Souch, and Paul Nunn

2.11.1 The Evolution of Catastrophe Modelling as a Profession and Best Practice 121

2.11.2 Rating Agencies 125

2.11.3 Regulation and Catastrophe Modelling 126

2.11.4 Case Study: Catastrophe Models and Solvency Regulation, Solvency II 128

2.11.5 Case Study: Regulation of Catastrophe Models for Ratemaking 135

2.12 Case Study: Catastrophe Modelling for Reinsurance and Retrocession Purchase 137
Juan England

2.12.1 Introduction 137

2.12.2 Determining the Total Limit Required 138

2.12.3 Layering of a CAT XL Programme 140

2.12.4 Price 140

2.12.5 Cost Allocation 141

2.12.6 Conclusion 141

2.13 Government Schemes and Insurance 142
Matthew Eagle

2.13.1 Introduction 142

2.13.2 Government Schemes with Standalone Products Managed by a Central Organization 144

2.13.3 Government Schemes Where Catastrophe Cover Is Provided as an Add-on to Fire 144

2.13.4 Government-Backed Reinsurance/Pooling Schemes 144

2.13.5 Private Insurance Company Pools Supported by Government Legislation 144

2.13.6 Case Study: UK Flood Re 152

2.14 Catastrophe Models and Applications in the Public Sector 154
Rashmin Gunasekera

2.14.1 Introduction 154

2.14.2 Public Sector Catastrophe Models 154

2.14.3 Applications of Public Sector Catastrophe Models 155

2.14.4 Case Study: Country Disaster Risk Profiles (CDRP) 156

2.15 Insurance Linked Securities 158
Arnab Chakrabati

2.15.1 What Are Insurance Linked Securities? 158

2.15.2 From Insurance to Reinsurance to ILS 159

2.15.3 Common ILS Instruments 160

2.15.4 Preliminaries of ILS Instrument: Measurement and Layering of Losses 160

2.15.5 Pricing an ILS Contract 162

2.15.6 Pricing Cat Bonds with the Thin Layer Model 163

2.15.7 Growth of the Market for ILS 164

2.15.8 Conclusion 166

2.16 Effective use of Catastrophe Models 167
Ian Cook, Matthew Jones, Adam Podlaha, and Kirsten Mitchell-Wallace

2.16.1 Treatment of Uncertainty in Catastrophe Models 167

2.16.2 Importance of Framework: A Tool, Not an Answer 179

Notes 181

References 181

3 The Perils in Brief 187
*John Hillier*

3.1 Overview 187

3.1.1 What Is Included 187

3.1.2 What Is Not Included 191

3.1.3 Why Read This Chapter? 191

3.X Structure of the Sections 192

3.X.1 What Is the Peril? 192

3.X.2 Damage Caused by the Peril 192

3.X.3 Forecasting Ability and Mitigation 192

3.X.4 Representation in Industry Catastrophe Models 193

3.X.5 Secondary Perils and Non-Modelled Items 193

3.X.6 Key Past Events 193

3.X.7 Open Questions/Current Hot Topics/Questions to Ask Your Vendor 193

3.X.8 Non-Proprietary Data Sources 193

METEOROLOGICAL PERILS (I.E. 'WIND-DRIVEN') 194

3.2 Tropical Cyclones 194
James Done and Brian Owens

3.2.1 What Is the Peril? 194

3.2.2 Damage Caused by the Peril 198

3.2.3 Forecasting Ability and Mitigation 198

3.2.4 Representation in Industry Catastrophe Models 199

3.2.5 Secondary Perils and Non-Modelled Items 200

3.2.6 Key Past Events 200

3.2.7 Open Questions/Current Hot Topics/Questions to Ask Your Vendor 201

3.2.8 Nonproprietary Data Sources 202

Acknowledgements 202

3.3 Extra-Tropical Cyclones 202
Len Shaffrey and Richard Dixon

3.3.1 What Is the Peril? 202

3.3.2 Damage Caused by the Peril 205

3.3.3 Forecasting Ability and Mitigation 206

3.3.4 Representation in Industry Catastrophe Models 206

3.3.5 Secondary Perils and Non-Modelled Items 207

3.3.6 Key Past Events 207

3.3.7 Open Questions/Current Hot Topics/Questions to Ask Your Vendor 208

3.3.8 Nonproprietary Data Sources 209

3.4 Severe Convective Storms 209
Michael Kunz and Peter Geissbuehler

3.4.1 What Is the Peril? 209

3.4.2 Damaged Caused by the Peril 213

3.4.3 Forecasting Ability and Mitigation 214

3.4.4 Representation in Industry Catastrophe Models 215

3.4.5 Secondary Perils and Non-modelled Items 216

3.4.6 Key Past Events 216

3.4.7 Open Questions/Current Hot Topics/Questions to Ask Your Vendor 216

3.4.8 Nonproprietary Data Sources 217

…