Peter Taylor Catastrophes and insurance

This chapter explores the way financial losses associated with catastrophes can be mitigated by insurance. It covers what insurers mean by catastrophe and risk, and how computer modelling techniques have tamed the problem of quantitative estimation of many hitherto intractable extreme risks. Having assessed where these techniques work well, it explains why they can be expected to fall short in describing emerging global catastrophic risks such as threats from biotechnology. The chapter ends with some pointers to new techniques, which offer some promise in assessing such emerging risks.

8.1 Introduction

Catastrophic risks annually cause tens of thousands of deaths and tens of billions of dollars worth of losses. The figures available from the insurance industry (see, for instance, the Swiss Re [2007] Sigma report) show that mortality has been fairly consistent, whilst the number of recognized catastrophic events, and even more, the size of financial losses, has increased. The excessive rise in financial losses, and with this the number of recognized 'catastrophes', primarily comes from the increase in asset values in areas exposed to natural catastrophe. However, the figures disguise the size of losses affecting those unable to buy insurance and the relative size of losses in developing countries. For instance, Swiss Re estimated that of the estimated $46 billion losses due to catastrophe in 2006, which was a very mild year for catastrophe losses, only some $16 billion was covered by insurance. In 2005, a much heavier year for losses, Swiss Re estimated catastrophe losses at $230 billion, of which $83 billion was insured. Of the $230 billion, Swiss Re estimated that $210 billion was due to natural catastrophes and, of this, some $173 billion was due to the US hurricanes, notably Katrina ($135 billion). The huge damage from the Pakistan earthquake, though, caused relatively low losses in monetary terms (around $5 billion mostly uninsured), reflecting the low asset values in less-developed countries.

In capitalist economies, insurance is the principal method of mitigating potential financial loss from external events in capitalist economies. However, in most cases, insurance does not directly mitigate the underlying causes and risks themselves, unlike, say, a flood prevention scheme. Huge losses in recent years from asbestos, from the collapse of share prices in 2000/2001, the 9/11 terrorist attack, and then the 2004/2005 US hurricanes have tested the global insurance industry to the limit. But disasters cause premiums to rise, and where premiums rise capital follows.

Losses from hurricanes, though, pale besides the potential losses from risks that are now emerging in the world as technological, industrial, and social changes accelerate. Whether the well-publicized risks of global warming, the misunderstood risks of genetic engineering, the largely unrecognized risks of nanotechnology and machine intelligence, or the risks brought about by the fragility to shocks of our connected society, we are voyaging into a new era of risk management. Financial loss will, as ever, be an important consequence of these risks, and we can expect insurance to continue to play a role in mitigating these losses alongside capital markets and governments. Indeed, the responsiveness of the global insurance industry to rapid change in risks may well prove more effective than regulation, international cooperation, or legislation.

Insurance against catastrophes has been available for many years - we need to only think of the San Francisco 1906 earthquake when Cuthbert Heath sent the telegram 'Pay all our policyholders in full irrespective of the terms of their policies' back to Lloyd's of London, an act that created long-standing confidence in the insurance markets as providers of catastrophe cover. For much of this time, assessing the risks from natural hazards such as earthquakes and hurricanes was largely guesswork and based on market shares of historic worst losses rather than any independent assessment of the chance of a catastrophe and its financial consequence. In recent years, though, catastrophe risk management has come of age with major investments in computer-based modelling. Through the use of these models, the insurance industry now understands the effects of many natural catastrophe perils to within an order of magnitude. The recent book by Eric Banks (see Suggestions for further reading) offers a thorough, up-to-date reference on the insurance of property against natural catastrophe. Whatever doubts exist concerning the accuracy of these models - and many in the industry do have concerns as we shall see -there is no questioning that models are now an essential part of the armoury of any carrier of catastrophe risk.

Models notwithstanding, there is still a swathe of risks that commercial insurers will not carry. They fall into two types (1) where the risk is uneconomic, such as houses on a flood plain and (2) where the uncertainty of the outcomes is too great, such as terrorism. In these cases, governments in developed countries may step in to underwrite the risk as we saw with TRIA (TerrorismRisk Insurance Act) in the United States following 9/11. An analysis1 of uninsured risks revealed that in some cases risks remain uninsured for a further reason - that the government will bail them out! There are also cases where underwriters will carry the risk, but policyholders find them too expensive. In these cases, people will go without insurance even if insurance is a legal requirement, as with young male UK drivers.

Another concern is whether the insurance industry is able to cope with the sheer size of the catastrophes. Following the huge losses of 9/11 a major earthquake or windstorm would have caused collapse of many re-insurers and threatened the entire industry. However, this did not occur and some loss-free years built up balance sheets to a respectable level. But then we had the reminders of the multiple Florida hurricanes in 2004, and hurricane Katrina (and others!) in 2005, after which the high prices for hurricane insurance have attracted capital market money to bolster traditional re-insurance funds. So we are already seeing financial markets merging to underwrite these extreme risks - albeit 'at a price'. With the doom-mongering of increased weather volatility due to global warming, we can expect to see inter-governmental action, such as the Ethiopian drought insurance bond, governments taking on the role of insurers of the last resort, as we saw with the UK Pool Re-arrangement, bearing the risk themselves through schemes, such as the US FEMA flood scheme, or indeed stepping in with relief when a disaster occurs.

8.2 Catastrophes

What are catastrophic events? A catastrophe to an individual is not necessarily a catastrophe to a company and thus unlikely to be a catastrophe for society. In insurance, for instance, a nominal threshold of $5 million is used by the Property Claims Service (PCS) in the United States to define a catastrophe. It would be a remarkable for a loss of $5 million to constitute a 'global catastrophe'!

We can map the semantic minefield by characterizing three types of catastrophic risk as treated in insurance (see Table 8.1): physical catastrophes, such as windstorm and earthquake, whether due to natural hazards or man-made accidental or intentional cause; liability catastrophes, whether intentional such as terrorism or accidental such as asbestosis; and systemic underlying causes leading to large-scale losses, such as the dotcom stock market collapse. Although many of these catastrophes are insured today, some are not, notably emerging risks from technology and socio-economic collapse. These types of risk present huge challenges to insurers as they are potentially catastrophic losses and yet lack an evidential loss history.

Catastrophe risks can occur in unrelated combination within a year or in clusters, such as a series of earthquakes and even the series of Florida hurricanes seen in 2004. Multiple catastrophic events in a year would seem to be exceptionally rare until we consider that the more extreme an event the more likely it is to trigger another event. This can happen, for example, in natural catastrophes where an earthquake could trigger a submarine slide, which causes a tsunami or triggers a landslip, which destroys a dam, which in turn floods a city. Such high-end correlations are particularly worrying when they might induce man-made catastrophes such as financial collapse, infrastructure failure, or terrorist attack. We return to this question of high-end correlations later in the chapter.

You might think that events are less predictable the more extreme they become. Bizarre as it is, this is not necessarily the case. It is known from statistics that a wide class of systems show, as we look at the extreme tail, a regular 'extreme value' behaviour. This has, understandably, been particularly important in Holland (de Haan, 1990), where tide level statistics along the Dutch coast since 1880 were used to set the dike height to a 1 in 10,000-year exceedance level. This compares to the general 1 in 30-year exceedance level for most New Orleans dikes prior to Hurricane Katrina (Kabat et al., 2005)!





Physical (property) Earthquake,

Nuclear bomb (war).

Climate change,

windstorm, volcano.

nuclear action

nuclear accident

flood, tsunami.

(terrorism), arson

wildfire, landslip,

(property terrorism)

space storm, asteroid

(e.g., 9/11)

Liability ' Pandemic

War (conventional,

Product liability (e.g.,

nano-, bio-, nuclear),



terrorism (nano, bio-,



pollution (chemical.

bio-, nuclear),



nuclear accident


Social failure (e.g..

Technology failure

war, genocide).

(e.g., computer

economic failure

network failure).

(e.g., energy

financial dislocation

embargo, starvation)

(e.g., 7000 stock

market crash)

Table 8.1 Three Types of Catastrophic Risk as Treated in Insurance

Uninsured Losses, report for the Tsunami Consortium, November 2000.

Table 8.1 Three Types of Catastrophic Risk as Treated in Insurance

Uninsured Losses, report for the Tsunami Consortium, November 2000.

You might also have thought that the more extreme an event is the more obvious must be its cause, but this does not seem to be true in general either. Earthquakes, stock market crashes, and avalanches all exhibit sudden large failures without clear 'exogenous' (external) causes. Indeed, it is characteristic of many complex systems to exhibit 'endogenous' failures following from their intrinsic structure (see, for instance, Somette et al, 2003).

In a wider sense, there is the problem of predictability. Many large insurance losses have come from 'nowhere' - they simply were not recognized in advance as realistic threats. For instance, despite the UK experience with IRA bombing in the 1990s, and sporadic terrorist attacks around the world, no one in the insurance industry foresaw concerted attacks on the World Trade Center and the Pentagon on 11 September 2001.

Then there is the problem of latency. Asbestos was considered for years to be a wonder material2 whose benefits were thought to outweigh any health concerns. Although recognized early on, the 'latent' health hazards of asbestos did not receive serious attention until studies of its long-term consequences emerged in the 1970s. For drugs, we now have clinical trials to protect people from unforeseen consequences, yet material science is largely unregulated. Amongst the many new developments in nanotechnology, could there be latent modern versions of asbestosis?

8.3 What the business world thinks

You would expect the business world to be keen to minimize financial adversity, so it is of interest to know what business sees as the big risks.

A recent survey of perceived risk by Swiss Re (see Swiss Re, 2006, based on interviews in late 2005) of global corporate executives across a wide range of industries identified computer-based risk the highest priority risk in all major countries by level of concern and second in priority as an emerging risk. Also, perhaps surprisingly, terrorism came tenth, and even natural disasters only made seventh. However, the bulk of the recognized risks were well within the traditional zones of business discomfort such as corporate governance, regulatory regimes, and accounting rules.

The World Economic Forum (WEF) solicits expert opinion from business leaders, economists, and academics to maintain a finger on the pulse of risk and trends. For instance, the 2006 WEF Global Risks report (World Economic Forum, 2006) classified risks by likelihood and severity with the most severe risks being those with losses greater than $1 trillion or mortality greater than $1 million or adverse growth impact greater than 2%. They were as follows.

2See, for example, 20O4.html

1. US current account deficit was considered a severe threat to the world economy in both short (1-10% chance) and long term (<1% chance).

2. Oil price shock was considered a short-term severe threat of low likelihood

3. Japan earthquake was rated as a 1-10% likelihood. No other natural hazards were considered sufficiently severe.

4. Pandemics, with avian flu as an example, was rated as a 1-10% chance.

5. Developing world disease: spread of HIV/AIDS and TB epidemics were similarly considered a severe and high likelihood threat (1-20%).

6. Organized crime counterfeiting was considered to offer severe outcomes (long term) due to vulnerability of IT networks, but rated low frequency

7. International terrorism considered potentially severe, through a conventional simultaneous attack (short term estimated at <1%) or a non-conventional attack on a major city in longer term (1-10%).

No technological risks were considered severe, nor was climate change. Most of the risks classified as severe were considered of low likelihood (<1%) and all were based on subjective consensual estimates.

The more recent 2007 WEF Global Risks report (World Economic Forum, 2007) shows a somewhat different complexion with risk potential generally increased, most notably the uncertainty in the global economy from trade protectionism and over-inflated asset values (see Fig. 8.1). The report also takes a stronger line on the need for intergovernmental action and awareness.

It seems that many of the risks coming over the next 5-20 years from advances in biotechnology, nanotechnology, machine intelligence, the resurgence of nuclear, and socioeconomic fragility, all sit beyond the radar of the business world today. Those that are in their sights, such as nanotechnology, are assessed subjectively and largely disregarded.

And that is one of the key problems when looking at global catastrophic risk and business. These risks are too big and too remote to be treated seriously.

8.4 Insurance

Insurance is about one party taking on another's financial risk. Given what we have just seen of our inability to predict losses, and given the potential for dispute over claims, it is remarkable that insurance even exists, yet it does! Through the protection offered by insurance, people can take on the risks of ownership of property and the creation of businesses. The principles of ownership and its financial protection that we have in the capitalist West, though, do not apply to many countries; so, for instance, commercial insuranceCatastrophes and insurance did not exist in Soviet Russia. Groups with a common interest, such as farmers, can share their common risks either implicitly by membership of a collective, as in Soviet Russia, or explicitly by contributing premiums to a mutual fund. Although mutuals were historically of importance as they often initiated insurance companies, insurance is now almost entirely dominated by commercial risk-taking.

The principles of insurance were set down over 300 years ago in London by shipowners at the same time as the theory of probability was being formulated to respond to the financial demands of the Parisian gaming tables. Over these years a legal, accounting, regulatory, and expert infrastructure has built up to make insurance an efficient and effective form of financial risk transfer.

To see how insurance works, let us start with a person or company owning property or having a legal liability in respect of others. They may choose to take their chances of avoiding losses by luck but will generally prefer to protect against the consequences of any financial losses due to a peril such as fire or accident. In some cases, such as employer's liability, governments require by law that insurance be bought. Looking to help out are insurers who promise (backed normally by capital or a pledge of capital) to pay for these losses in return for a payment of money called a 'premium'. The way this deal is formulated is through a contract of insurance that describes what risks are covered. Insurers would only continue to stay in business over a period of years if premiums exceed claims plus expenses. Insurers will nonetheless try and run their businesses with as little capital as they can get away with, so government regulators exist to ensure they have sufficient funds. In recent years, regulators such as the Financial Services Authority in the United Kingdom have put in place stringent quantitative tests on the full range of risk within an insurer, which include underwriting risks, such as the chance of losing a lot of money in one year due to a catastrophe, financial risks such as risk of defaulting creditors, market risks such as failure of the market to provide profitable business, and operational risks from poor systems and controls.

Let us take a simple example: your house. In deciding the premium to insure your house for a year, an underwriter will apply a 'buildings rate' for your type of house and location to the rebuild cost of the house, and then add on an amount for 'contents rate' for your home's location and safety features against fire and burglary multiplied by the value of contents. The rate is the underwriter's estimate of the chance of loss - in simple terms, a rate of 0.2% is equivalent to expecting a total loss once in 500 years. So, for example, the insurer might think you live in a particularly safe area and have good fire and burglary protection, and so charge you, say, 0.1% rate on buildings and 0.5% on contents. Thus, if your house's rebuild cost was estimated at /500,000 and your contents at /100,000, then you would pay /500 for buildings and /500 for contents, a total of/1000 a year.

Most insurance works this way. A set of 'risk factors' such as exposure to fire, subsidence, flood, or burglary are combined - typically by addition - in the construction of the premium. The rate for each of these factors comes primarily from claims experience - this type of property in this type of area has this proportion of losses over the years. That yields an average price. Insurers, though, need to guard against bad years and to do this they will try to underwrite enough of these types of risk, so that a 'law of large numbers' or 'regression to the mean' reduces the volatility of the losses in relation to'the total premium received. Better still, they can diversify their portfolio of risks so that any correlations of losses within a particular class (e.g., a dry winter causes earth shrinkage and subsidence of properties built on clay soils) can be counteracted by uncorrelated classes.

Continue reading here: Global catastrophic risks

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