The Palgrave Handbook of Unconventional Risk Transfer (eBook)

Maurizio Pompella is Professor of Financial Intermediaries Economics at the School of Economics and Management at the University of Siena, Italy. He is highly sought for his teaching, and has lectured at Universities in Europe, Latin America, the Middle East, Russian Federation and China. Among his other scholarly pursuits he has been serving as a reviewer for the prestigious Journal of Risk and Insurance, and is the Editor of the forthcoming series Palgrave Studies in Risk and Insurance. Nicos Scordis is a Professor at the School of Risk Management, Insurance and Actuarial Science at St. John’s University in New York, USA. He was honoured with the prestigious Les B. Strickler Innovation in Instruction Award from the American Risk and Insurance Association for his educational contributions to the developing speciality of alternative risk transfer. He publishes both in scholarly journals and in professional publications on the topic of value creation in the risk and insurance industry.

Foreword 6
Contents 8
List of Figures 11
List of Tables 17
1: Introduction 19
Part I: Risk Management Strategies and Perspectives 23
2: A Theoretical Perspective on Risk Management 24
2.1 Introduction 24
2.2 Why Should a Firm Manage Risks? 25
2.2.1 A Point of Departure: Risk Neutral Owner and a Linear Exposure 26
2.2.2 Risk Aversion on the Part of the Owner: A Reason to Lower Risk? 27
2.2.3 Why Variability Might Lower the Value of the Firm 28
2.2.4 Why Variability Could Increase the Value of the Firm 29
2.3 Sources of Changes in Profit—Risk and Uncertainty 32
2.4 Ways to Manage Risk and Uncertainty 35
2.4.1 Hedging Risk Due to s with Derivatives and Insurance Contracts 36
2.4.2 Operational Hedging 38
2.4.3 Flexibility 41
2.4.4 Managing Liquidity and Ensuring Access to New Funds 43
2.5 Concluding Remarks 46
Notes 47
References 47
3: A Practical Perspective on Corporate Risk Management 51
3.1 Introduction 51
3.2 Risk and Uncertainty 52
3.2.1 Decisions Under Conditions of Risk 52
3.2.2 Decisions Under Conditions of Uncertainty 54
3.3 Challenges in Pricing Corporate Risk 57
3.3.1 Different Consumption Preferences 57
3.3.2 Choosing the Right Metric 59
3.3.3 In Need of Prudence 61
3.4 Why Corporations Manage Risk 64
3.4.1 The View from the Academy 64
3.4.2 Towards a Risk Strategy 66
References 68
Part II: Conventional vs Unconventional Transfer 71
4: Reinsurance, Insurability and the New Paradigms of Unconventional Risk Transfer 72
4.1 Traditional Reinsurance 72
4.2 How Conventional Transfer Works 74
4.3 Unconventional Transfer and ILSs 75
4.4 The Innovation in the “Life Insurance” Sector 78
4.5 Insurability of Risks 80
4.6 Securitisation 83
4.7 ART Attractiveness 86
4.8 Asymmetries and Parametric Triggering 88
4.9 New Markets for Life Insurance Policies 90
4.10 From Viatical to Life Settlement 91
4.11 Premium Financing and STOLI Policies 95
4.12 More on the Enterprises Perspective 96
4.12.1 A Taxonomy of Risks and Actors 96
4.12.2 Pure Risk Management and CAT Risks 99
4.12.3 Pure Business Risk Financing and Control 100
4.12.4 The Risk Management Process, Prevention, Protection, and Resilience 101
4.12.5 Cost of Risk for Enterprises 104
4.13 More on the Insurers’ Perspective 107
4.13.1 Subscribed and Subscription Risk 107
4.13.2 Exposure Limits 108
4.14 The New Paradigms of Unconventional Transfer 111
4.14.1 Structured Finance and Insurers 111
4.14.2 A Brief Outline of Market Products and the New Way 112
4.14.3 Risk Warehousing and Intermediation: The Actuarial Versus the Financial View 115
Notes 116
References 118
Arrow, K.J. 1970. Insurance, Risk and Resource Allocation. In Essays in the Theory of Risk Bearing, ed. K.J. Arrow. Amsterdam: North Holland. 118
Suggested Further Readings 119
5: Enterprise Risk Management and the Risk Management Process 123
5.1 Introduction 123
5.2 Preliminary Definitions and Concepts 124
5.2.1 What Is Risk? 124
5.2.2 What Is Enterprise Risk Management? 128
5.2.3 The Risk Management Process 129
5.3 Objectives of Risk Management 130
5.3.1 How Does Risk Affect Value? 131
5.3.1.1 The Valuation Model 131
5.3.1.2 How Does the First Notion of Risk (Expected Losses) Affect the Valuation Model? 133
5.3.1.3 How Does the Second Notion of Risk (Variability) Affect the Valuation Model? 134
5.3.1.4 Indirect Effects of Risk (Uncertainty) Reduction on Expected Cash Flows5 136
5.3.1.5 Financial Distress Costs 138
5.3.1.6 Costs of Raising External Capital 138
5.3.1.7 Taxes 139
5.3.2 Justification for Enterprise Risk Management 140
5.4 Risk Identification 140
5.5 Risk Assessment 141
5.6 Evaluate Alternative Risk Management Treatments 142
5.7 Monitor and Adjust 143
5.8 Examples of ERM Processes 143
5.8.1 United Grain Growers9 143
5.8.2 Hydro One 145
5.8.3 American Electric Power10 146
5.8.4 Nationwide11 147
5.9 Decision-Making Mistakes 147
5.9.1 Behavioural Biases 148
5.9.1.1 Saliency Bias 148
5.9.1.2 Availability Bias 148
5.9.1.3 Anchoring Bias 148
5.9.1.4 Confirmation Bias 149
5.9.1.5 Optimistic Bias 149
5.9.1.6 Failure to Ignore Sunk Cost 149
5.9.1.7 Other Risk Management Mistakes 149
5.9.1.8 Agency Problems 150
5.10 Risk Appetite 151
5.11 Summary 153
Notes 154
Appendix 1: Risk Management Processes Proposed by Various Risk Management Organizations 155
Casualty Actuary Society 155
The Committee of Sponsoring Organizations of the Treadway Commission (COSO) 155
References 155
6: Credit Risk Transfer with Single-Name Credit Default Swaps 157
6.1 Introduction 158
6.2 The Composition of the Single-Name CDS Market 160
6.2.1 Aggregate CDS Market Activity 160
6.2.2 Single-Name CDSs by Type of Underlying 162
6.3 Single-Name CDSs 165
6.3.1 Reference Entity 166
6.3.1.1 Type of Reference Entity 166
6.3.1.2 Credit Risk of Reference Entity 169
6.3.2 Maturity/Tenor 171
6.3.3 Cost for the Protection Purchaser 173
6.3.4 Credit Events 175
6.3.4.1 The 1999 and 2003 Definitions 175
6.3.4.2 The 2009 “Big Bang Protocol” and Supplement to the 2003 Definitions 177
6.3.4.3 Example of the Determinations Process: The Hellenic Republic Credit Event 179
6.3.4.4 The 2014 Definitions 184
6.3.5 Settlement Methods 185
6.3.5.1 Physical Settlement 186
6.3.5.2 Auction Settlement 188
6.3.5.3 Cash Settlement 191
6.3.6 Deliverable Obligations 192
6.4 Conclusion 193
Notes 194
References 197
Part III: Risks by Class 200
7: Natural Hazards 201
7.1 Introduction 201
7.2 Earthquakes 201
7.3 Volcanoes 210
7.4 Landslides 217
7.5 Tropical Cyclones 222
7.6 Tornadoes 229
7.7 Tsunami 232
7.8 Flood 236
7.9 Extraterrestrial Impactors 239
7.10 Space Weather 243
References 245
8: Anthropic Perils and Man-Made Risks 252
8.1 Introduction 252
8.2 Human Error 253
8.2.1 Defence-in-Depth: The Swiss Cheese Model 255
8.3 Industrial Accidents 256
8.3.1 Industrial Pollution 257
8.3.2 Maritime Accidents 258
8.3.3 Oil Pollution Risk 261
8.3.4 Aviation Accidents 263
8.3.5 Accidents in Space 265
8.4 Terrorism 266
8.4.1 Terrorism in the Name of Religion 268
8.4.2 Terrorism and the Media 269
8.4.3 Implications for Terrorism Insurance Loss 270
8.5 Cyber Attacks 272
8.5.1 Cyber Loss Footprints 273
8.5.2 Hacker Groups 274
8.5.3 Physical Damage from Cyber Attacks 275
8.5.4 Cyber Warfare 276
References 277
9: Mortality and Longevity Risk 279
9.1 Introduction 279
9.1.1 Mortality Risk 280
9.1.2 Longevity Risk 280
9.1.3 Risk Management Tools 282
9.2 Biometric Risks in the Solvency II Framework 283
9.3 Quantitative Assessment 286
9.3.1 Risk Components 286
9.3.2 Early Developments 287
9.3.3 The Lee–Carter Model 287
9.3.4 Criticism and Extensions of the Lee–Carter Model 290
9.3.5 Recent Alternative Mortality Forecasting Techniques 293
9.4 Traditional Risk Management Approaches12 294
9.5 Mortality-Linked Securities 297
Notes 301
References 302
10: Country Risk: Case Study on Crises Examples and Lessons Learnt 308
10.1 Introduction 308
10.2 Country Risk Definition 309
10.3 Approaches to Country Risk Assessment 312
10.4 FDI and Country Risk Level 315
10.5 Country Risk Case Study 316
10.5.1 Asian Crisis of 1997–1998 316
10.5.2 Russian Financial Crisis of 1998, Its Prerequisites 318
10.5.3 Argentine Financial Crisis of 1999–2001 and Its Prerequisites 322
10.5.4 Russian Financial Crisis of 2008 and 2014 325
10.5.5 Great Britain—Brexit19 328
10.6 Conclusion 330
Notes 332
References 332
Part IV: Vulnerability, Market Solutions and Societal Implications 335
11: Disaster Vulnerability 336
11.1 Introduction 336
11.2 Fundamentals: Vulnerability and Disaster Vulnerability 337
11.3 The Sendai Framework 340
11.4 Definitions and Concepts of Vulnerability 341
11.4.1 Vulnerability 341
11.4.2 Response Capacities 342
11.4.3 Resilience 343
11.5 Conceptual Frameworks of Vulnerability 344
11.5.1 The Double Structure of Vulnerability—Development Discourse 344
11.5.2 The Pressure and Release Model (PAR Model) 345
11.5.3 Vulnerability as One Component of Disaster Risk 347
11.5.4 The MOVE Framework 348
11.5.5 Vulnerability Within the Climate Change Adaptation Research 351
11.6 Application Area: Vulnerability and Urbanisation 353
11.7 Conclusions 357
References 358
12: Insurance-Linked Securities: Structured and Market Solutions 364
12.1 Introduction 364
12.2 Insurance-Linked Securities (ILS)—Carriers and Instruments by Class 365
12.3 Catastrophe Bonds (CAT Bonds) and Derivatives 366
12.3.1 CAT Bonds 366
12.3.2 Catastrophe Options and Derivatives 369
12.4 Finite Risk Reinsurance (Finite Re) 370
12.5 Contingent Capital 373
12.6 Weather Derivatives 374
12.7 Other ART Techniques 376
12.8 Summary 378
Notes 378
References 378
13: Longevity Risk Transfer 381
13.1 Introduction 381
13.1.1 The Bittersweet Challenge 382
13.2 Sources of Longevity Risk 383
13.2.1 The Individual Perspective 383
13.2.2 Governments 384
13.2.3 Insurers 386
13.2.4 Corporate Group Pension Schemes 387
13.2.5 Life Settlement Funds 387
13.2.6 Lifetime Mortgages (Also Known as Equity Release Mortgages) 388
13.3 Properties of Longevity and Longevity Risk 389
13.3.1 Characteristics 389
13.3.1.1 Long Duration 389
13.3.1.2 Opposite to Mortality Risk 390
13.3.1.3 Measurement Is Part Objective, Part Subjective 390
13.3.1.4 Longevity Is Largely the Outcome of a Lagged Process 391
13.3.1.5 Pricing Is Marked-to-Model Rather than Marked-to-Market 392
13.3.2 Longevity Risk Components 392
13.3.3 Historical Projections of Life Expectancy 395
13.3.4 Sources of Uncertainty in Longevity Trends 397
13.3.5 Longevity Trend Models 401
13.3.6 The Socio-economic Dimension 403
13.4 Why Organisations Wish to Cede Longevity Risk 405
13.4.1 A Growing Market 405
13.4.2 Reasons for Growth 407
13.4.3 Pension Schemes and Accessing the Longevity-­Mortality Diversification Benefit 408
13.4.4 Ceding Longevity Risk or Holding a Matching Asset? 408
13.5 Why Organisations Wish to Acquire Longevity Risk 410
13.5.1 The Mortality-Longevity Diversification Benefit 411
13.5.2 Optimization Strategies 414
13.5.3 Capital Markets 415
13.6 How Longevity Risk Is Currently Transferred 416
13.6.1 Indemnity Swaps 416
13.6.2 Index-Based Swaps 418
13.6.3 Longevity Swaptions 420
13.7 The Lessons Learned from the Journey to Date 421
13.7.1 Key Milestones in the Journey Thus Far 421
13.7.2 EIB/BNP Paribas, 2004 421
13.7.3 Kortis Bond, 2010 424
13.7.4 International Regulator Co-ordination 425
13.7.5 A Framework for Basis Risk, 2014 425
13.7.6 The First Index-Based Transactions 426
13.7.7 Improving Price Transparency 428
13.8 The Future for Longevity Risk Transfer 429
13.8.1 Increasing Supply from Pension Funds 429
13.8.2 Will Governments Issue Longevity-Linked Bonds? 429
13.8.3 Requirements for an Index-Based Capital Market for Longevity 432
13.8.4 Future Waves of Innovation 432
13.8.5 The Benefits of Socio-economic Segmentation 434
13.8.6 Insurance-Linked Securities 434
Notes 436
References 437
Part V: Risk Modelling and Stress Testing 441
14: Quantitative Man-Made Risks’ Modelling 442
14.1 Man-Made Risks 442
14.1.1 Principles of Terrorism Risk Modelling 444
14.1.2 Target Substitution 446
14.1.3 Terrorist Weaponry 447
14.1.4 Severity of Weapon Attack Modes 447
14.1.5 Frequency of Terrorist Attacks 449
14.1.6 Dependence on Human Behaviour 452
14.2 Terrorism Risk Bonds 453
14.2.1 Golden Goal Finance Ltd. 455
14.2.2 Future Terrorism Catastrophe Bonds 456
14.2.3 Terrorism Parametric Trigger Bonds 458
14.3 Pandemic Risk 459
14.3.1 Linkage with Political Risk 460
14.3.2 Bio-Terrorism 461
14.4 Political Conflict Triggers 462
14.4.1 Political Conflict Risk Forecasting 463
14.5 Cyber Risk 464
14.5.1 Modes of Cyber Attack 465
References 466
15: Pandemic Risk Modelling 468
15.1 Introduction 468
15.2 History of Pandemics 472
15.2.1 Origins and Properties of Infectious Diseases with Pandemic Potential 477
15.3 Infectious Disease Models 478
15.3.1 Modelling Infectious Disease Spread 478
15.3.2 Compartmental Models 479
15.3.3 Agent-Based Models 483
15.4 Inferring Key Epidemiological Model Parameters During a Pandemic 484
15.5 Medical Interventions and Public Health Countermeasures 487
15.6 Probabilistic Models 489
15.6.1 Frequency and Origin 491
15.6.2 Transmissibility and Virulence 492
15.6.2.1 Infectious Disease Modelling in Comparison to Catastrophe Modelling 493
15.7 Applications 494
15.8 Conclusion 495
Notes 495
References 496
16: Assembling Individual ILS into an Optimal Portfolio 501
16.1 Introduction: Beating Your Benchmark 501
16.2 The Setting 502
16.2.1 The Available Portfolio: Deals, Sizes and Prices 502
16.2.2 The Risk Environment: 10,000 Catastrophe Scenarios (Collapsing to 20) 507
16.2.3 Risk Preferences: The Risk Constraints 509
16.3 The Model 513
16.3.1 Outline Model 513
16.3.2 Optimum with Just Risk Constraints: Two Deals Are Optimal 513
16.3.3 Market Share Constraints 516
16.4 The Optimum Portfolio 517
16.4.1 The Solution and Its Characteristics 517
16.4.2 Peril Distribution: Asia 520
16.4.3 Marginal Values and Price Sensitivity 521
16.4.4 Comments on Leverage 529
16.4.4.1 Insurance Leverage: Choosing the “Shorts” and Deploying the Cash 529
16.5 Conclusions 530
16.5.1 The Utility of Optimization 530
16.5.2 Extensions 531
16.5.3 Other Insights 532
Notes 533
Appendix 1: The Price Indication Sheets 535
Appendix 2: A (Incomplete) List of Model Assumptions 537
Appendix 3: Selected Related Publications (Reverse Chronological Order) 538
17: Stress Testing with Bayesian Nets and Related Techniques: Meeting the Engineering Challenges 540
17.1 Stress Testing and Its Engineering Challenges 540
17.2 Current Approaches to Stress Testing 544
17.2.1 The Extreme-Tail Approach 544
17.2.2 The Vulnerability-Driven Approach 545
17.2.3 The Coherent-Stress-Testing Approach 547
17.3 What Bayesian Nets Offer: A Faustian Parable 548
17.4 Bayesian Nets in a Nutshell 553
17.5 The Outstanding Engineering Problems 559
17.6 A Digression: How to Deform a ‘Yield Curve’ 560
17.6.1 The Algorithm 560
17.6.2 An Example 563
17.6.3 Why Minimizing S ? 564
17.7 Applying the ‘View’ Solution to Stress Testing 565
17.8 Obtaining a ‘Normal-Times-Consistent’ Correlation Matrix for the Main Drivers 567
17.9 Extending the Range of the Correlation Matrix 570
17.10 Summary of the Strategy 572
17.11 Conclusions 573
Notes 574
References 577
Index 579