93,99 €
Mehr erfahren.
- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
This book covers both the practical and theoretical aspects of catastrophe modelling for insurance industry practitioners and public policymakers. Written by authors with both academic and industry experience it also functions as an excellent graduate-level text and overview of the field.
Ours is a time of unprecedented levels of risk from both natural and anthropogenic sources. Fortunately, it is also an era of relatively inexpensive technologies for use in assessing those risks. The demand from both commercial and public interests—including (re)insurers, NGOs, global disaster management agencies, and local authorities—for sophisticated catastrophe risk assessment tools has never been greater, and contemporary catastrophe modelling satisfies that demand.
Combining the latest research with detailed coverage of state-of-the-art catastrophe modelling techniques and technologies, this book delivers the knowledge needed to use, interpret, and build catastrophe models, and provides greater insight into catastrophe modelling’s enormous potential and possible limitations.
- The first book containing the detailed, practical knowledge needed to support practitioners as effective catastrophe risk modellers and managers
- Includes hazard, vulnerability and financial material to provide the only independent, comprehensive overview of the subject, accessible to students and practitioners alike
- Demonstrates the relevance of catastrophe models within a practical, decision-making framework and illustrates their many applications
- Includes contributions from many of the top names in the field, globally, from industry, academia, and government
Natural Catastrophe Risk Management and Modelling: A Practitioner’s Guide is an important working resource for catastrophe modelling analysts and developers, actuaries, underwriters, and those working in compliance or regulatory functions related to catastrophe risk. It is also valuable for scientists and engineers seeking to gain greater insight into catastrophe risk management and its applications.
Sie lesen das E-Book in den Legimi-Apps auf:
Seitenzahl: 1268
Veröffentlichungsjahr: 2017
Ähnliche
Contents
Cover
Title Page
Copyright
Foreword
List of Contributors and Acknowledgements
Main Authors
Contributors
Chapter 1: Fundamentals
1.1 Overview
1.2 Catastrophes, Risk Management and Insurance
1.3 What Are Catastrophe Models?
1.4 Why Do We Need Catastrophe Models?
1.5 History of Catastrophe Models
1.6 Who Provides and Uses Catastrophe Models?
1.7 What Are Catastrophe Models Used For?
1.8 Anatomy of a Catastrophe Model
1.9 Model Input
1.10 Model Output: Metrics and Risk Measures
1.11 Statistical Basics for Catastrophe Modelling
Notes
References
Chapter 2: Applications of Catastrophe Modelling
2.1 Overview
2.2 Introduction
2.3 Risk Transfer, the Structure of the (Re)insurance Industry and Catastrophe Modelling
2.4 Insurance and Reinsurance
2.5 Catastrophe Risk Management and Catastrophe Modelling
2.6 Underwriting and Pricing
2.7 Accumulation, Roll-Up and Capacity Monitoring
2.8 Portfolio Management and Optimization
2.9 Event Response and Integration with Claims Team
2.10 Capital Modelling, Management and Dynamic Financial Analysis
2.11 Regulation and Best Practice in Catastrophe Modelling
2.12 Case Study: Catastrophe Modelling for Reinsurance and Retrocession Purchase
2.13 Government Schemes and Insurance
2.14 Catastrophe Models and Applications in the Public Sector
2.15 Insurance Linked Securities
2.16 Effective use of Catastrophe Models
Notes
References
Chapter 3: The Perils in Brief
3.1 Overview
3.X Structure of the Sections
Meteorological Perils (I.E. ‘Wind-Driven’)
3.2 Tropical Cyclones
3.3 Extra-Tropical Cyclones
3.4 Severe Convective Storms
Hydrological Perils (I.E. ‘Rain-Driven’)
3.5 Inland Flooding
3.6 Shrink-Swell Subsidence
3.7 Earthquakes
3.8 Mass Movement
3.9 Tsunami
3.10 Volcanoes
References
Chapter 4: Building Catastrophe Models
4.1 Overview
4.2 Introduction
4.3 Hazard
4.4 Exposure Models and Databases
4.5 Vulnerability
4.6 Integrating Model Components and the Geographical Framework
4.7 The Financial Model
4.8 Model Validation
4.9 Conclusion
Note
References
Chapter 5: Developing a View of Risk
5.1 Overview
5.2 Introduction
5.3 Governance and Model Change Management
5.4 How to Develop a View of Risk
5.5 Implementing a View of Risk
5.6 Conclusion
Notes
References
Chapter 6: Summary and the Future
6.1 Overview
6.2 Key Themes in the Chapters
6.3 The Future: Progress, Challenges and Issues
References
Glossary
Index
End User License Agreement
List of Tables
Table 1.1
Table 1.2
Table 1.3
Table 1.4
Table 1.5
Table 1.6
Table 1.7
Table 1.8
Table 1.9
Table 2.1
Table 2.2
Table 2.3
Table 2.4
Table 2.5
Table 2.6
Table 2.7
Table 2.8
Table 2.9
Table 2.10
Table 2.11
Table 2.12
Table 2.13
Table 2.14
Table 2.15
Table 2.16
Table 2.17
Table 3.1
Table 3.2
Table 3.3
Table 3.4
Table 3.5
Table 3.6
Table 3.7
Table 4.1
Table 4.2
Table 4.3
Table 4.4
Table 4.5
Table 4.6
Table 4.7
Table 4.8
Table 4.9
Table 4.10
Table 4.11
Table 4.12
Table 4.13
Table 5.1
Table 5.2
Table 5.3
Table 6.1
List of Illustrations
Figure 1.1
Figure 1.2
Figure 1.3
Figure 1.4
Figure 1.5
Figure 1.6
Figure 1.7
Figure 1.8
Figure 1.9
Figure 1.10
Figure 1.11
Figure 2.1
Figure 2.2
Figure 2.3
Figure 2.4
Figure 2.5
Figure 2.6
Figure 2.7
Figure 2.8
Figure 2.9
Figure 2.10
Figure 2.11
Figure 2.12
Figure 2.13
Figure 2.14
Figure 2.15
Figure 2.16
Figure 2.17
Figure 2.18
Figure 2.19
Figure 2.20
Figure 2.21
Figure 2.22
Figure 2.23
Figure 2.24
Figure 2.25
Figure 2.26
Figure 2.27
Figure 2.28
Figure 2.29
Figure 2.30
Figure 2.31
Figure 2.32
Figure 2.33
Figure 2.34
Figure 2.35
Figure 3.1
Figure 3.2
Figure 3.3
Figure 3.4
Figure 3.5
Figure 3.6
Figure 3.7
Figure 3.8
Figure 3.9
Figure 3.10
Figure 3.11
Figure 3.12
Figure 3.13
Figure 3.14
Figure 3.15
Figure 3.16
Figure 3.17
Figure 3.18
Figure 3.19
Figure 3.20
Figure 3.21
Figure 3.22
Figure 3.23
Figure 3.24
Figure 3.25
Figure 3.26
Figure 3.27
Figure 4.1
Figure 4.2
Figure 4.3
Figure 4.4
Figure 4.5
Figure 4.6
Figure 4.7
Figure 4.8
Figure 4.9
Figure 4.10
Figure 4.11
Figure 4.12
Figure 4.13
Figure 4.14
Figure 4.15
Figure 4.16
Figure 4.17
Figure 4.18
Figure 4.19
Figure 4.20
Figure 4.21
Figure 4.22
Figure 4.23
Figure 4.24
Figure 4.25
Figure 4.26
Figure 4.27
Figure 4.28
Figure 4.29
Figure 4.30
Figure 4.31
Figure 4.32
Figure 4.33
Figure 4.34
Figure 4.35
Figure 4.36
Figure 4.37
Figure 4.38
Figure 4.39
Figure 4.40
Figure 5.1
Figure 5.2
Figure 5.3
Figure 5.4
Figure 5.5
Figure 5.6
Figure 5.7
Figure 5.8
Figure 5.9
Figure 5.10
Figure 5.11
Figure 5.12
Figure 5.13
Figure 5.14
Figure 5.15
Figure 5.16
Figure 5.17
Figure 5.18
Figure 5.19
Figure 5.20
Figure 5.21
Figure 5.22
Guide
Cover
Table of Contents
Begin Reading
Chapter 1
Pages
i
ii
iii
iv
xiii
xiv
xv
xvi
xvii
xviii
xix
xx
xxi
xxii
xxiii
xxiv
xxv
xxvi
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
Natural Catastrophe Risk Management and Modelling
A Practitioner's Guide
Kirsten Mitchell-Wallace
SCOR, Zürich, Switzerland
Matthew Jones
Cat Risk Intelligence, UK
John Hillier
Loughborough University, Loughborough, UK
Matthew Foote
Argo Group International Holdings, London, UK
This edition first published 2017© 2017 John Wiley & Sons Ltd
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.
The right of Kirsten Mitchell-Wallace, Matthew Jones, John Hillier and Matthew Foote to be identified as the authors of this work has been asserted in accordance with law.
Registered OfficesJohn Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK
Editorial Office111 River Street, Hoboken, NJ 07030, USA9600 Garsington Road, Oxford, OX4 2DQ, UKThe Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK
For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com.
Wiley also publishes its books in a variety of electronic formats and by print-on-demand. Some content that appears in standard print versions of this book may not be available in other formats.
Limit of Liability/Disclaimer of Warranty
The publisher and the authors make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of fitness for a particular purpose. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for every situation. In view of ongoing research, equipment modifications, changes in governmental regulations, and the constant flow of information relating to the use of experimental reagents, equipment, and devices, the reader is urged to review and evaluate the information provided in the package insert or instructions for each chemical, piece of equipment, reagent, or device for, among other things, any changes in the instructions or indication of usage and for added warnings and precautions. The fact that an organization or website is referred to in this work as a citation and/or potential source of further information does not mean that the author or the publisher endorses the information the organization or website may provide or recommendations it may make. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this works was written and when it is read. No warranty may be created or extended by any promotional statements for this work. Neither the publisher nor the author shall be liable for any damages arising here from.
Library of Congress Cataloging-in-Publication Data
Names: Mitchell-Wallace, Kirsten, 1973- editor.
Title: Natural catastrophe risk management and modelling: a practitioner's guide / edited by Kirsten Mitchell-Wallace, Zurich, SZ, Matthew Jones, Southampton, UK, John Hillier, Loughborough, UK, Matthew Foote, London, UK.
Description: Hoboken, NJ : John Wiley and Sons, Inc., [2017] | Includes bibliographical references and index.
Identifiers: LCCN 2016053404| ISBN 9781118906040 (cloth) | ISBN 9781118906071 (epub) | ISBN 9781118906064 (Adobe PDF)
Subjects: LCSH: Emergency management. | Disasters—Risk assessment.
Classification: LCC HV551.2 .C38 2017 | DDC 363.34/2—dc23 LC record available at https://lccn.loc.gov/2016053404
Cover image: © cosmin4000/GettyimagesCover design by Wiley
Foreword
This is a ground breaking and essential book. For the last quarter of a century, some of us have witnessed the birth and development of a new, profound and integrating professional and scientific discipline called catastrophe risk modelling. It has transformed the quality of insurance protection upon which more than a billion people depend for their security, and reformed an industry from relative ruin in the early 1990s to relative resilience just two decades later, in spite of a sharp increase in natural hazard risk over that time.
And yet, despite this significance, the discipline is barely known outside its own circles. It is difficult to estimate, but perhaps just 25,000 people worldwide are active members of the ‘cat modeling’ community among insurers, reinsurers, regulators, modeling providers, and related communities across academia, engineering and civil protection.
I entered this domain in 2005 and, like everyone, learnt about this field through professional courses, experience, the wisdom of colleagues and reports and articles dealing with specific issues. There was no consolidated text that brought this world together. Meanwhile sensing the wider significance of these methods, there was nowhere to point the curious non-insurer when asked to recommend a comprehensive guide to the field. I am grateful that we now have one, and delighted that many of those who shone a light for me ten years ago have come together with others to share their knowledge and experience for all.
The authors and contributors are to be congratulated, not just for producing the first detailed reference on catastrophe modeling, but also for creating the framing of a new discipline. It is path-breaking and one can only imagine the length of internal debates on so many defining points and fundamental issues. This breakthrough will, I hope, spur many other books and publications to support the expansion and further deepening of the field.
Most of us work in specific areas and this text will be useful to experienced practitioners, to connect with wider aspects of the discipline, as well as essential reading for newer professionals. I am also excited that it will open up the field to many others across industry, science, NGOs and public policy, far beyond insurance, who can build on it, apply it and even criticize it as part of a wider, shared, endeavour to better understand, reduce and manage climate and natural hazard risks and protect the under-protected.
As we consider how to implement the UN Global Goals on climate risk and other natural hazards, catastrophe modelling will guide the changes needed to save millions of lives and livelihoods among exposed populations in the decades ahead. This book, and its future editions, will play a leading role in that journey.
Rowan Douglas CBE
CEO Capital Science & Policy Practice, Willis Towers WatsonMember, Prime Minister's Council for Science & Technology
List of Contributors and Acknowledgements
We, the main authors, wish to expressly thank the other authors and reviewers who have contributed to this book and made it possible. Catastrophe risk management and modelling is a discipline that draws upon a wide range of knowledge and expertise, so we could not have created a credible practitioner's guide without the widespread support that we have received from the catastrophe modelling community.
Each main author had oversight of one of the main chapters (i.e. 2–5), and sculpted it as appropriate; the structure of each topic and nature of the material required different approaches by chapter. This said, we have all re-written, polished and homogenized all the chapters of the book to produce what we hope is a coherent journey through the topic of catastrophe risk management and modelling.
We have chosen to accredit ourselves in reverse alphabetical order, selected with a degree of randomness befitting the subject matter of this guide.
As well as the four main authors, many contributors provided material for chapters, or sub-chapters, of the book; sometimes an author contributed in more than one place. These contributions are summarized in the table below, and, as appropriate, authors are listed at the start of sections that they co-wrote.
The contributions of the many external reviewers drawn from outside the editorial team were also invaluable; in particular, we are indebted to Alan Calder, George Cooper, Jeff Gall, Claire Crerar, Paul Nunn and Claire Souch who reviewed the entire book or a large part of it.
We thank Wiley's editors and team for giving us the opportunity to produce this guide and assisting us along the way.
Main Authors
This guide has four main authors who also acted as editors. Here, we introduce ourselves in reverse alphabetical order.
Kirsten Mitchell-Wallace is the Regional Cat Manager for Europe, Middle East and Africa at SCOR, leading cat teams based in Zurich and Paris in support of property treaty business written from this region, including US Cat. Before this, she was Head of Cat Pricing and Methodology and responsible for coordinating the development of SCOR's own view of risk, as well as managing the Zurich-based cat team. Prior to joining SCOR in 2009, she was a Senior Catastrophe Risk Analyst at Willis, London, for 5 years, working first on European, then Japanese business. She started her career with two years at Risk Management Solutions in London and two years at risk management consultancy, Risk Solutions, from 2001. Kirsten has a PhD in Atmospheric Physics from Imperial College, London, and a Masters in Meteorology from Reading University, as well as a degree in Chemistry from the University of Bristol. She also has an International Diploma in Risk Management from the Institute of Risk Management. Kirsten is passionate about catastrophe modelling.
Acknowledgments: I would first like to thank my husband, Richard, for keeping our family fed and Arthur clothed throughout this project. Without his incredible support, my contribution could never have been possible.
I would then also like to thank the many people outside the editorial team who reviewed my chapter and made valuable suggestions: Sibylle Steimen, Claire Crerar, Alan Calder, Paul Nunn, Claire Souch, Iakovos Barmpadimos, Roger Bordoy, George Cooper, Thomas Premier and Thomas Linford. Thanks to Parvez Chowdury and Tobias Hoffmann for their review of the actuarial matter. Special thanks to Tom for associated discussions and to Paul for his support of this endeavour.
I would like to thank my many co-authors for their contributions and for being, without exception, a pleasure to work with. I have learned a lot! Thank you also to my fellow editors for a real team effort. In loving memory of my father, Derrick G. Mitchell.
Matthew Jones is the founding Director of Cat Risk Intelligence, a UK-based company providing catastrophe risk management consultancy to the (re)insurance industry.
In his previous role as Global Head of Catastrophe Management for Zurich Insurance Group, Matthew led the organizational change required to establish a global catastrophe management team with consistent processes to provide catastrophe knowledge, systems, models and services across Zurich's general insurance lines of business. He worked for Zurich for fourteen years, including various roles in the actuarial pricing and catastrophe risk management fields. Prior to this Matthew was a reinsurance pricing actuary for St Paul Re in London.
Matthew graduated from the University of Nottingham in 1993 with a degree in Physics. He then completed a PhD in Oceanography and Remote Sensing from University College London, while being based at the UK's National Oceanography Centre in Southampton. He is a Fellow of the Institute and Faculty of Actuaries.
Acknowledgments: I would like to thank my wife Zoe, and my children, Adam, Lauren and Becky, for their love, support and patience. I am extremely grateful to Jane Hayes for allowing me a sabbatical from Zurich to help write some of this book. I am also very thankful to Alan Calder, Jeff Gall and Claire Souch for the time they put into reviewing and making improvements to Chapter 5; to Fortunat Kind for his input and improvements (including the ‘Christmas tree’ diagram!); to Gary Hemming for his review of some actuarial pricing aspects; to Federico Waisman for allowing many of his model comparison exhibits to be included; and to Ye Liu for some very helpful statistical discussions.
John Hillier is currently a Senior Lecturer at Loughborough University, with research interests that include various geo-hazards (e.g. earthquake, landslide, flooding, extra-tropical cyclones), multi-hazard risk to property and infrastructure, use of impacts (e.g. loss data) to gain insights into physical processes, and inter-dependencies (i.e. ‘links’ or interactions) between perils.
He received B.A. (M.A. Cantab) and M.Sci. degrees in Natural Sciences specializing in Geology from the University of Cambridge, and a D.Phil degree in Marine Geophysics from the University of Oxford.
After studying he was awarded a research fellowship at St Catharine's College, Cambridge, and then worked for Zurich Insurance as a catastrophe modeller.
Acknowledgments: I am extremely grateful as ever for the love, tolerance and support of my wife, Katie; I do not say this enough, so I would like to say it explicitly here. My love and thanks also to Ben and Charlotte for putting up with Daddy working when you could clearly think of better things I should be doing.
Academically, I appreciate the stoic perseverance and professionalism of all 16 contributors on the perils in Chapter 3 in the face of requests for more detail in fewer words, or for correcting errors I inadvertently introduced when re-writing an initial submission to half its original length. The following reviewers did a great job of making sure we did a robust and thorough job, with numbers in brackets indicating sections: Rebecca Bell (Imperial College) [3.7], Thierry Corti (Swiss Re) [3.6], Mark Dixon (RMS) [3.3], Juergen Grieser (RMS) [3.4], Joanna Faure-Walker (UCL) [3.8], Greg Holland (NCAR) [3.2], Edmund Penning Rowsell [3.5], Tiziana Rossetto [3.9], Robin Spence [3.10]. This said, any remaining errors should be considered mine and mine alone.
Matthew Foote is an exposure management specialist with over twenty years of experience in the (re)insurance industry, including roles with Willis and Guy Carpenter reinsurance brokers, Risk Management Solutions, Mitsui Sumitomo and most recently Argo Group. For seven years Matthew was the Research Director of the Willis Research Network, responsible for the coordination and development of industrial-academic collaborations involving over fifty research organisations and universities.
Matthew began his career as a cartographer and geographic information specialist, working primarily with earth observation (EO) data and other imagery-based data. He has a First Class degree in Geography from Birkbeck, University of London, is a Fellow of the Royal Geographical Society/IBG and a Chartered Geographer.
Acknowledgments: My thanks are short and simple, first, to Paula, my wife, for all she has done, and to my children Ciara and Michael for inspiring me. I would also like to particularly acknowledge the efforts of Barbara Page, Adam Podlaha, Shane Latchman, Rashmin Gunasekera and Claire Souch, and to express my gratitude to Stuart Lane for his advice in the very early stages of developing this book.
Contributors
The following practitioners and academics contributed to this guide. For volunteering your time and expertise, we thank you.
Contributor
*
Section(s)
Biography
Šárka Černá
4.3
Šárka Černá
works in the business development team in Impact Forecasting doing product development and working with clients. She benefits from five years working as a catastrophe model developer, where she mainly focused on the mathematical and statistical aspects of flood models (e.g. Switzerland). She is involved in the development of the ELEMENTS platform, including testing and validation procedures for Solvency II. After joining Aon Benfield in 2010, Šárka was appointed their Chair of Research in 2014. Prior to 2010, she worked at the Institute of Thermomechanics of the Czech Academy of Sciences on statistical ultrasonic signal processing.
Arnab Chakrabarti
2.15
Arnab Chakrabarti
is a Research Engineer at Nephila Advisors LLC, Larkspur, CA, USA. He works on developing methods and tools for catastrophe bond pricing, portfolio construction, and other problems that use a combination of math/stat/programming. He has been with Nephila since 2013. Prior to joining Nephila, Dr Chakrabarti worked in R&D at Qualcomm. He has a Masters in Financial Engineering from the Haas School of Business at UC-Berkeley. Earlier, he did his MS-PhD in Electrical and Computer Engineering from Rice University, and his B.Tech in Electronics and Electrical Communication Engineering from IIT-Kharagpur.
Ian Cook
2.16
Ian Cook
is Chief Actuary and Managing Director at Willis Re, advising clients around the world on risk quantification and risk mitigation. He has represented Willis Re on EIOPA's Catastrophe Risk Subgroup, advising them on natural and man-made catastrophe risk and reinsurance. He has also presented and published papers on a number of actuarial and catastrophe-related topics. Prior to joining Willis Re in 2002, he spent over 10 years in actuarial consultancy helping clients on a wide range of actuarial matters. Ian is a Fellow of the Institute and Faculty of Actuaries, and holds a degree in mathematics from Cambridge University.
Claire Crerar
2.7
Claire Crerar
has over 14 years experience working in catastrophe modelling, having started her career as a catastrophe risk analyst at Willis. After six years modelling for a wide range of global clients, Claire moved to Aspen where she led the London catastrophe modelling team, with responsibility for international treaty modelling and monitoring accumulations of catastrophe risk. After seven years in this role, Claire has recently shifted focus to concentrate on cat-related project work at Aspen. Claire has an MA in geography from Cambridge University and holds an Advanced Diploma in Insurance from the Chartered Insurance Institute.
Tom Dijkstra
3.8
Tom Dijkstra
studied at Utrecht University, the Netherlands, taking Physical Geography with Geomorphology, Quaternary Geology and Soil Science as specializations. In 1989, he moved to the UK after being offered a research position as part of a large EU-funded project and this supported his PhD on landslide mechanisms in Chinese loess. He worked in academia, mainly in Civil Engineering Departments, focusing on geotechnical engineering and since 2012 has been an engineering geologist/geomorphologist at the British Geological Survey specializing in climate change effects on slope instability processes in natural and engineered (transport infrastructure) slopes, geohazards and landslide hazard forecasting.
Richard Dixon
3.3
Richard Dixon
received a first-class honours degree in Meteorology followed by a PhD specializing in extratropical cyclones from University of Reading, UK. Since 2000, he has worked in the insurance industry building and researching catastrophe models at Risk Management Solutions, and for the past 10 years has worked in catastrophe model evaluation at Aon Benfield, Renaissance Reinsurance and Hiscox. He currently works as a consultant to the insurance industry in catastrophe model evaluation at CatInsight as well as carrying out meteorological research to aid in the understanding of catastrophe risk and catastrophe risk model development.
James Done
3.2
James Done
received his BSc and PhD in meteorology from the University of Reading, UK. A post-doctoral position at the National Center for Atmospheric Research (NCAR), in the United States led to his current position of Willis Research Fellow and science lead of NCAR's Capacity Center for Climate and Weather Extremes. He works with stakeholders from the energy, water and insurance sectors to understand future weather and climate impacts. Examples of his recent work include assessing future hurricane impacts on the offshore energy industry and the electric power industry, and quantifying the benefit-cost ratio of hurricane building codes.
Radovan Drinka
4.3
Radovan Drinka
is a catastrophe model developer at Impact Forecasting and a meteorologist involved in the European Windstorm project and atmospheric perils (e.g. hail, summer storm). He is also involved in an engineering approach to structure vulnerability to wind damage. He has two years experience as a catastrophe modeller after joining Aon Benfield in 2008. As a member of the Impact Forecasting team, Radovan has gained a wide knowledge of Impact Forecasting proprietary platform ELEMENTS, and has used it in his daily routine since 2010. Radovan earned a Masters degree in Physics, Meteorology and Climatology at the Comenius University, Bratislava, the Slovak Republic.
Matthew Eagle
2.13
Matthew Eagle
is Managing Director and Head of GC Analytics for International at Guy Carpenter. In this role he is responsible for providing resource leadership across the EMEA and AsiaPac regions, with a specific focus on developing a market-leading catastrophe modelling and analytics proposition. He has over 20 years of experience in the reinsurance sector with a focus on catastrophe analytics. Previously he worked in statistical software and consulting. He has a MSc in Statistics from the University of Minnesota and is a Fellow of the Royal Statistical Society.
Juan England
2.12
Juan England
is Managing Director of the Willis Re Latin America and Caribbean team, based in London. Previously he held various positions in the Analytics division as joint-head of Analytics for Willis Re, Deputy Managing Director of Willis Re's International Catastrophe Management team, and head of catastrophe modelling for Willis Re's Latin America and Caribbean. He joined Willis Re as a catastrophe analyst in 2006. Juan has a PhD in Structural Vulnerability from the University of Bristol, UK, and BSc in Civil Engineering with emphasis in earthquake risk assessment from the University of Los Andes in Bogota, Colombia.
Chris Ewing
4.3
Chris Ewing
is a member of Impact Forecasting's business development team, currently leading on the use of data for primary underwriting, and implementation of third party models on Aon's ELEMENTS loss calculation platform. Chris previously developed earthquake models (e.g. Greece) and worked on the global tsunami research project. Prior to 2011, Chris worked for a consultant engineering firm. Chris has a BSc in Geography from the University of Leeds and an MSc in GIS from Nottingham University. Chris is a Chartered Geographer (GIS), a Fellow of the Royal Geographical Society, and chairs AGI's Insurance and Risk special interest group.
Joanna Faure Walker
3.7
Joanna P. Faure Walker
received BA (MA Cantab) and MSci. degrees in Natural Sciences, specializing in Geology, from the University of Cambridge, and a DPhil degree in Earth Sciences from University College London. Following her PhD, Faure Walker became an analyst for the catastrophe modelling firm, RMS. She is currently a Senior Lecturer at UCL IRDR (Institute for Risk and Disaster Reduction) with research interests that include earthquake geology, rates of fault deformation and interaction, seismic hazard, and the transitional phase of recovery. She lectures on natural hazards, vulnerability, risk and their integration into decision-making.
Guillermo Franco
2.8
Guillermo Franco
is Managing Director and Global Head of Catastrophe Risk Research at Guy Carpenter. Prior to this, Guillermo was a manager and principal engineer at AIR Worldwide, where he participated in earthquake model development and headed the Decision Analytics practice. As a research fellow at Columbia, he studied the socioeconomic impact of natural hazards in developing countries. Guillermo is a structural engineer and holds MSc, MPhil and PhD degrees in civil engineering and engineering mechanics from Columbia University in New York and a BSc from the Technical University of Catalonia in Barcelona, Spain.
Yo Fukutani
3.9
Yo Fukutani
received a BS degree in Physics from Tohoku University and an MSci degree in Natural Sciences, specializing in Meteorology, from the University of Tokyo, Japan. After studying, he worked for Tokio Marine & Nichido Risk Consulting Co., Ltd as a catastrophe modeller and surveyor, and then worked for Tohoku University as a research associate from 2012 to 2015. In 2016, he received a PhD in Civil Engineering from Tohoku University. He is currently a Senior Risk Analyst at Tokio Marine & Nichido Risk Consulting, with research interests that include uncertainty assessment and quantitative risk assessment especially in the coastal engineering field.
Peter Geissbuehler
3.4
Peter Geissbühler
has worked at Tokio Millennium Re AG as the Head of the Actuarial and NatCat Department in Europe since 2011. Before he joined Tokio Millennium, Peter worked at RMS as a Director for European and International Product, mainly responsible for managing the European Winterstorm Model in 2011. Peter started his career at Converium as a cat modeller and pricing actuary where he built models for typhoons in South Korea. In addition, he was senior pricing actuary for cat business for many European countries. Peter holds a PhD in Climatology.
Alexandros Georgiadis
4.3
Alexandros Georgiadis
joined Impact Forecasting (Aon Benfield) in 2009. His focus is the development of a probabilistic windstorm risk model for Europe, addressing the climate research-related aspects of the project in collaboration with the University of Cologne. His background is in climatology, including: atmospheric dynamics and climate modelling, surface-atmosphere interactions, climate change, forest fire risk and remote sensing. Prior to 2009, he was a post-doc in the Space and Atmospheric Physics (SPAT) group at Imperial College London. Alexandros holds a PhD in climatology (Hurricane formation and modification in the south-east Caribbean) from the University of Sheffield, UK.
Rashmin Gunasekera
†
2.14, 3.10, 4.3, 6.2.4
Rashmin Gunasekera
is a disaster risk management specialist at the World Bank, focusing on disaster risk assessment and risk financing within the Latin American & Caribbean region. He has over 15 years experience extending to the public sector, re/insurance industry and academia. Prior to joining the World Bank in 2012, he was a Divisional Director of a global reinsurance intermediary and a coordinator of the Willis Research Network, the world's largest collaboration between public science and the financial sector. He has also been a research scientist for an EU project on volcanic risk, and holds an honorary lectureship at UCL. His PhD is in earthquake seismology.
Marc Hill
4.3
Marc Hill
is a principal modeller in the model development group at Risk Management Solutions Ltd (RMS). He studied for his MSc in Concrete Structures at Imperial College London and received a PhD in Engineering at University College London. He joined RMS in 2009 and has participated in a variety of vulnerability development projects, including the climate peril of wind, as well as post-catastrophe damage surveys.
Michael Kunz
3.4
Michael Kunz
studied Meteorology at the University of Karlsruhe (Dipl. Met.), where he also earned his PhD (Dr. rer. nat.) with his dissertation on orographic rain enhancement. In 2011, he completed his Habilitation at the Karlsruhe Institute of Technology (KIT) on the amplification of atmospheric processes over complex terrain. He is currently Senior Scientist and head of the working group ‘Atmospheric Risks’ at the Institute of Meteorology and Climate Research at KIT. His research focuses on extreme weather events (hail, heavy rainfall, and wind gusts), their probability, long-term variability, and related impacts. His working group has also developed various hazard and risk models in cooperation with insurance companies.
Rob Lamb
3.5
Rob Lamb
studied at the Universities of Cambridge and Lancaster, where his doctoral research was in numerical modelling of river catchment hydrology and uncertainty analysis. He was a research scientist at CEH Wallingford for six years, before moving to JBA Consulting in 2002. Since then, he has worked on academic and applied research in hydrology, river hydraulics, flood risk management, climate change adaptation and systems-based infrastructure risk analysis. Since 2012, he has held dual roles as a Professor in the Lancaster Environment Centre, and Director of the JBA Trust, a charitable research and knowledge exchange foundation sponsored by the JBA Group.
Shane Latchman
4.3, 4.5, 4.7
Shane Latchman
is Assistant Vice President in AIR's London office involved in some of AIR's Touchstone initiatives, such as the integration of third-party data and models, expanding AIR's capabilities in marine and energy, the Next Generation Financial Module, and the development of future multi-modelling/blending capabilities. He is a member of the catastrophe modelling and actuarial industry groups, and is heavily involved with rating agencies and regulators on topics, such as Solvency II. After receiving a National Scholarship from Trinidad and Tobago, Shane studied Actuarial Science at City University and received a BSc with honours. His Masters in Mathematics is from the University of Cambridge, and he is a Certified Catastrophe Modeller.
Sue Loughlin
3.10
Susan Loughlin
is the Head of Volcanology at the British Geological Survey and joint leader of the Global Volcano Model project. Her research interests include volcanic processes, hazards and risk, communication, social and environmental impacts of eruptions and the interaction of scientists and decision-makers. Dr. Loughlin spent several years at Montserrat Volcano Observatory and was Director there for two years. She has been an advisor to governments and communities during volcanic unrest and eruptions (e.g. Montserrat and Iceland/UK) and provided scientific evidence for longer-term planning.
Paul Nunn
2.11
Paul Nunn
is Head of Catastrophe Risk Modelling at SCOR Global P&C, responsible for the management of natural hazard perils globally. A key aspect of the role is the provision of analytics and data for internal and external stakeholders, including SCOR's internal capital model, rating agencies, regulators and retrocessionaires. Before joining SCOR Global P&C, Paul was Head of Exposure Management at Lloyd's and previously worked for the cat modelling specialist firm, AIR Worldwide. He is also a Director of the non-profit Oasis Loss Modelling Framework company.
Brian Owens
3.2
Brian Owens
is a meteorologist and specialist in catastrophe risk management. As a Senior Director at Risk Management Solutions (RMS), he is responsible for their global models and data market and release strategy. He has more than 20 years experience in insurance, catastrophe financing, and catastrophe risk management, and has written numerous scientific articles and blogs. Mr Owens holds a BS in computer science from the National University of Ireland, an MBA from the University of Pennsylvania (Wharton), and an MS in meteorology from the University of Miami.
Barbara Page
4.3-4.6
Barbara Page
is a Senior Director in the model product management group at Risk Management Solutions Ltd (RMS). She obtained an MA in Natural Sciences from Cambridge University and a PhD in volcanology from Edinburgh University. Over the past 20 years, Dr Page has fulfilled a variety of roles at RMS in developing and managing catastrophe risk modelling products for the global private insurance market.
Adam Podlaha
2.16, 4.3
Adam Podlaha
is the Head of Impact Forecasting at Aon Benfield, overseeing a team of 85+ catastrophe model developers responsible for over 100 models spanning 12 perils, plus the ELEMENTS loss calculation platform. In addition to managing the team, Adam collaborates with various governmental and non-governmental institutions to deliver the best quality models, finding ways to effectively quantify and visualise uncertainty and make catastrophe modelling platforms more open. He joined Aon Benfield in Prague as a flood model developer in 2003 and holds a PhD in Physical Geography from Charles University in Prague.
Petr Punčochář
4.3
Petr Punčochář
is responsible for the Impact Forecasting flood model development team in the EMEA and APAC regions, implementing new workflows and methodologies. Additionally, he provides insights on hydrology, hydraulics and geographical information systems. Prior to joining Aon Benfield in 2010, Petr was a research assistant at the Department of Hydraulics and Hydrology at the Czech Technical University. Petr is a member of the International Association of Headwater Control and Czech delegation of FAO committee for Mountain Watershed Management. Petr received his PhD in hydrology and open-channel hydraulics in 2011 from the Czech Technical University.
Gillaume Pousse
3.6
Guillaume Pousse
gained a PhD degree in Earthquake Engineering in 2005 from the French Institute for Nuclear Safety. He is working for Guy Carpenter and is dedicated to delivering analytics value to clients. He previously worked at a reinsurer, pricing/monitoring inward catastrophe business in earthquake-prone or traditionally non-modelled countries. He also contributed to documenting the view of the risk in a continuous and prospective way. Prior to this, he developed probabilistic earthquake loss models in London for insurers and reinsurers.
Junaid Seria
2.10, 2.11
Junaid Seria
works as a Solvency II Nat Cat Actuary at SCOR and is responsible for embedding Solvency II in the business activities of the Nat Cat team. This includes SII training, independent validation of cat model methods and results, and developing governance structures. Previously he worked as an Actuarial Executive at KPMG in London where he specialized in cat risk consulting. This included managing authorization engagements for two UK reinsurer start-ups, managing cat risk validation engagements for UK primaries. He was also the cat risk expert reviewer for internal model submissions to the Bermudian Monetary Authority.
Len Shaffrey
3.3
Len Shaffrey
is a Senior Scientist in the National Centre for Atmospheric Science and a Professor in the Department of Meteorology at the University of Reading, UK. His research interests include understanding how extremes such as European Windstorms and extra-tropical cyclones have varied in the past and how they might respond to climate change.
Milan Simic
4.3, 4.5, 4.7
Milan Simic
is Executive Vice President and Managing Director of International Operations for AIR Worldwide, and is responsible for business development, strategic growth initiatives, and client services. Milan has more than 25 years' experience in risk assessment, engineering consulting, teaching, and research. He is a Chartered Engineer of the UK Institution of Civil Engineers and has authored numerous papers. He is also a member of the OECD's High-Level Advisory Board on Financial Management of Large-Scale Catastrophes. He earned his MSc in Hydraulic Structures from the University of Belgrade and a PhD in Earthquake Engineering from the University of Bristol, UK.
Nilesh Shome
4.3
Nilesh Shome
earned his PhD in Structural Engineering from Stanford University, USA. He is a Vice President of Risk Management Solutions (RMS) Global Earthquake and Terrorism products, leading the research and development works. Dr Shome joined RMS in 2009 and has more than 15 years of professional experience in modelling risk from hurricanes, earthquakes and other natural and man-made hazards, for RMS and other agencies including the World Bank, the Federal Emergency Management Agency (
FEMA
) and the Applied Technical Council (ATC). He authors, reviews and edits publications in international technical journals and refereed conferences.
Radek Solnický
4.3
Radek Solnický
is a catastrophe model developer in the Impact Forecasting flood team. As a statistician, his domains are hydrological data processing, frequency analysis, stochastic event set generation, as well as client data-based vulnerability development. He also provides mathematical support. Apart from taking part in the Poland Flood model and Sweden Cloudburst model and flood model for Brazil, he was responsible for the Netherlands Flood and Storm Surge model and Hungary flood model development. Radek contributes to the implementation of flood models into ELEMENTS, Aon's own loss estimation software platform.
Claire Souch
2.11, 4.8, 6.2.1
Claire Souch
has 15 years experience of catastrophe risk model development and usage across the global re/insurance industry. Claire is currently Head of Development at AgRisk, having held previous positions leading model development and evaluation at SCOR, and SVP of Model Strategy at RMS. She has advised on many aspects of catastrophe model usage and the impact of climate change on catastrophe risk for re/insurance companies across multiple markets. She has served on multiple industry task-forces on catastrophe risk and risk modelling, and is frequently invited to speak on topics such as catastrophe risk, development and the role of catastrophe risk insurance. Claire holds a BSc in Environmental Science and a PhD from Cranfield University, UK.
Anawat Suppasri
3.9
Anawat Suppasri
is currently an Associate Professor at the International Research Institute of Disaster Science, Tohoku University, Japan, with research interests that include various topics on tsunami hazard and risk assessments. He received a BEng degree in Civil Engineering from Chulalongkorn University, an MEng degree in Water Engineering and Management from the Asian Institute of Technology, and a PhD Degree in Civil Engineering from Tohoku University. After studying, he was awarded a research fellowship at the Disaster Control Research Center, Tohoku University.
Rick Thomas
6.2.2
Rick Thomas
. After studying Natural Sciences at Cambridge and doing a PhD and postdoc in modelling volcanic eruptions, Rick started work at CARtograph building catastrophe models in 1995. He moved from CARtograph to PartnerRe in 1997 where he led the creation of PartnerRe's in-house model suite, starting with US Hurricane models, but expanding to Japanese Typhoon, European Windstorm and global quake models. Rick moved from modelling to underwriting in the early 2000s and took over as Head of the international property CAT book at PartnerRe in 2004. Subsequent to Partner Re, Rick worked as an advisor to a fund investing in ILS, and as Head of Model Development and Evaluation at Willis Re, where he was also responsible for the Willis Research Network.
Jane Toothill
3.5
Jane Toothill
has over 20 years' experience in the modelling of natural catastrophes. Jane worked for the modelling company EQECAT and reinsurance broker Guy Carpenter, prior to joining JBA Group in 2008. She became one of the founding directors of JBA Risk Management in 2011, where she heads operations and catastrophe modelling. During her career Jane has also worked for the British Geological Survey and acted as an advisor on Zurich Financial Services' Natural Catastrophe Advisory Council. She holds a degree in Geology from the University of Bristol and a PhD in Environmental Science from Lancaster University.
Goran Trendafiloski
4.3
Goran Trendafiloski
is earthquake expert (e.g. seismic hazard assessment) and catastrophe model developer at Impact Forecasting (Aon Benfield). He develops damage and loss models to estimate the risk of properties and population due to earthquake shaking and tsunamis. He has published more than 100 scientific publications, books, papers and reports. Prior to 2010, he worked at the World Agency for Planetary Monitoring and Earthquake Risk Reduction, and the Institute of Engineering Mechanics, Harbin, China. Goran holds Dr.Tech.Sci. and M.Sc. degrees from the Institute of Earthquake Engineering and Engineering Seismology at the University St. Cyril and Methodius, Skopje, Macedonia, and postgraduate specialty degree from the University of Geneva, Switzerland.
Craig Verdon
3.8
Craig Verdon
is currently the Head of Europe Catastrophe Modelling at Endurance Re in Zurich. He received BSc (Geology & Chemistry) and BSc (Hons) degrees from the University of Natal (Durban) and, after some time in industry, an MSc in Engineering Geology from Imperial College London. He worked in a variety of roles across the mining and engineering sectors before joining the catastrophe modelling industry as a product manager at RMS.
Renato Vitolo
4.3
Renato Vitolo
is Head of Risk Modelling, Operational and Reputational Risk at Banca Monte dei Paschi di Siena, Italy, building on being a quantitative risk analyst there since 2011. Previously, he was a Willis Re Research Fellow based at the University of Exeter, UK, specializing in the clustering of extreme events (windstorms, hurricanes, typhoons, floods) and building event sets for tropical cyclone risk assessment using global climate model output. Renato has a PhD in Meteorology.
Dickie Whitaker
6.3.3
Dickie Whitaker
has 30 years' experience in the (re)insurance business and for the last 20 years has specialized in risk and innovation and linking academia, government and finance. Dickie has written and presented extensively on these subjects and has operated globally, having worked in both London and New York. He co-founded and works for the Lighthill Risk Network, FiNexus Ltd, Oasis Palm Tree Ltd, and is chief executive of Oasis Loss Modelling Framework Ltd.
*
Disclaimer: The findings, interpretations, and conclusions expressed in this work are entirely those of the authors and should not be attributed in any manner to the organizations that they are currently or have been employed by.
†
Disclaimer: The findings, interpretations, and conclusions expressed in this work are entirely those of the authors and should not be attributed in any manner to the World Bank, its Board of Executive Directors, or the governments they represent.
1Fundamentals
Matthew Jones,Kirsten Mitchell-Wallace,Matthew Foote, and John Hillier
1.1 Overview
1.2 Catastrophes, Risk Management and Insurance
1.3 What Are Catastrophe Models?
1.4 Why Do We Need Catastrophe Models?
1.5 History of Catastrophe Models
1.6 Who Provides and Uses Catastrophe Models?
1.7 What Are Catastrophe Models Used For?
1.8 Anatomy of a Catastrophe Model
1.9 Model Input
1.10 Model Output: Metrics and Risk Measures
1.11 Statistical Basics for Catastrophe Modelling
Notes
References
1.1.1 What Is Included
This chapter contains a broad overview of the topic of catastrophe modelling, including what catastrophe models are, why they are used, their overall structure and their output. Metrics used in catastrophe modelling are presented. Basic statistical concepts required for catastrophe modelling are also included for ease of reference.
1.1.2 What Is Not Included
Detailed information on every topic is not included. This is provided in the subsequent chapters.
1.1.3 Why Read This Chapter?
This chapter aims to give the reader an introductory background to catastrophe risk management and catastrophe modelling. It is targeted primarily at those new to the subject, but should also provide a refresher to those more familiar with the discipline. Reading this chapter together with any subsequent chapters should provide depth on the topic covered – be that the main uses of models, a discussion of the major perils, how to build a model, or how to develop a view of risk. Alternatively, this chapter can be read in isolation to provide an introduction to catastrophe risk management and modelling, from the basics of insurance to the elementary statistics required when using these models. The statistical basics are provided for completeness and reference; less mathematically-minded readers can avoid this section without compromising understanding of following chapters.
1.2 Catastrophes, Risk Management and Insurance
In its broadest sense, a catastrophe is something that exceeds the capability of those affected to cope with, or absorb, its effects; in the context of natural hazards the driver is an extreme event causing widespread and, usually sudden, damage or suffering. In the insurance industry, definitions of catastrophe are commonly based on an event exceeding one of a number of thresholds for loss (e.g. total economic losses, insured losses, loss of life – for an example by Swiss Re, see Table 1.1). Organizations may choose to define an event as a catastrophe if that company or the whole industry has large or unexpected losses or if significant media attention is expected. For example, the US Property Claims Service definition of a catastrophe is ‘an event that causes 25 m USD or more in direct insured losses to property and affects a significant number of policyholders and insurers’.
Table 1.1 Criteria used by Swiss Re in 2014 to determine if events were categorized as catastrophes and entered into their Sigma database.
Threshold
Quantity
Insured loss, maritime disasters
US$19.6 m
Insured loss, aviation
US$39.3 m
Insured loss, other losses
US$48.8 m
Total economic loss
US$97.6 m
Casualties, dead or missing
20
Casualties, injured
50
Casualties, homeless
2000
Source:
Swiss Re, 2015.
The terms risk, peril, and hazard are often used interchangeably in conversation. However, in the context of this book, we use the following definitions:
A
peril
is a potential cause of loss or damage such as an earthquake or windstorm.
Risk
is uncertainty leading to potential adverse outcomes. It is also used as shorthand for an insured object.
Hazard
is the danger from the peril.
Catastrophes are a risk to organizations and society. Managing this risk (catastrophe risk management) is the ongoing process of: (1) identifying the risk given the context of the organization or community, (2) quantifying the risk, (3) deciding what to do, given the level of risk and the risk appetite (i.e. how much risk an entity is willing to take) of the organization or community, and (4) monitoring the level of risk.
The concept of enterprise risk management (ERM) (Sweeting, 2011) involves the preceding process, but on a holistic basis (i.e. assessing all risks together, allowing for diversifications and concentrations of risk, including risks that are easy to quantify and those that are not, e.g. reputational damage). The classic responses to risk are to reduce, avoid, transfer or retain (Sweeting, 2011). Insurance is one important mechanism to transfer risk.
Insurance is an arrangement whereby one party (the insurer) promises to pay another party (the policyholder) a sum of money in the case of a loss as a result of a specific cause. This obligation to provide compensation following a loss is called indemnity. A premium is charged to the policyholder to provide this service. Insurance companies provide products for individuals (personal lines (PL) insurance) and for corporations (commercial lines insurance). Insurance companies who provide money contingent on whether someone dies are called life insurers, whereas other insurance companies are called non-life insurers or general insurers. Companies that provide both life and general insurance are called composite insurers. The focus of this book is on general insurance, which can be categorized into different lines of business, depending on the type of assets that are being insured; for example:
Motor
(or
auto
) lines provide insurance for the physical car and sometimes also for the third-party liability.
Property
(or
Direct & Fac
(
D&F
)
) lines provide insurance for properties, their contents and loss resulting from not being able to use the buildings because of an insured peril.
Marine
lines provide insurance for ships (
hull
) and the
cargo
they carry (often including goods not actually on a ship, but in transit and in warehouses; sometimes called
marine static risk
).
Aviation
lines provide insurance for aircraft, including third-party liability coverage.
Construction
(or
engineering
) lines provide insurance for building projects.
Liability
(or
casualty
) lines provide insurance to cover claims from third parties.
The precise origins of insurance are debated, but so long as there has been risk, people have tried to manage their individual exposure to it. The first record of insurance was the Babylonian King Hammarubi's code, an ancient tablet dating back to approximately 1750 BC. Insurance's origins were certainly in trade; Phoenicians and Greeks had similar schemes to minimize the impact of the potentially catastrophic (to any individual) loss of ships and cargo by forming a pool to spread the loss. Arrangements similar to modern marine insurance were in place by the mid-fourteenth century in Genoa. An explosion in trade in the seventeenth century led to a maritime information exchange in Lloyd's coffee shop in 1688, with the first recorded underwriting in 1757. After an insurance proposal was drafted, the participants all signed their names and participation on the risk underneath the proposal leading to the term ‘underwriter’ for those taking on the risk. Underwriting will be discussed together with insurance and reinsurance (the insurance of insurance companies) in Chapter 2.4. Meanwhile, in America, Benjamin Franklin founded the Philadelphia Contributorship in 1751.
The development of the (re)insurance industry, like modelling itself, has been driven by events. Large fires across Europe have been a driver for property insurance, notably the Great Fire of London in 1666. Before municipal fire-fighting facilities, insurance companies had their own services to protect the specifically marked properties of policyholders. The Hamburg Fire in 1842 precipitated the foundation of the first reinsurance company, Cologne Re. The foundation of Swiss Re has likewise been linked to the Glarus Fire of 1861. These severe events demonstrated the need for reinsurance, although many reinsurance companies were in fact founded to prevent the outflow of reinsurance premiums from local economies to foreign companies (Swiss Re, 2013). For details of the more recent evolution of insurance history, including the London Market Spiral in 1990s, see, for example, Thoyts (2010).
A fundamental concept of insurance is that pooling risk reduces the uncertainty in the expected (or average) loss (EL) over a specific time period. Put another way, the cost of losses, in any given year, from a large number of insured properties is much more certain than the loss cost from any individual property. An insurance company can, therefore, estimate the overall loss cost from a portfolio of insured properties with far more certainty than an individual could for one policy. In addition, for some loss scenarios (e.g. a property completely destroyed), the individual may be unable to cover the loss themselves. An insurance contract therefore provides the individual with much more certainty about the amount they will have to pay in any one year (the insurance premium, plus potentially an excess, see Section 1.9.2) as well as protection against an unaffordable loss. A more mathematical description of the rationale for insurance, in particular pooling of risk, is provided in Box 1.1.
