Chances Are (19 page)

The principle quickly extended throughout the new, dangerous fields opened by fast-expanding trade and industry. Lloyd's began to certify ships, giving the world the by-word “A1” for “best.” Samuel Plimsoll, outraged at the insurance scams of unscrupulous ship-owners, earned the thanks of thousands of sailors through his plimsoll lines, painted on the outside of ships' hulls to prevent overloading (as well as his rubber-soled shoes to prevent slipping on the new steel decks). Buildings, especially after the great Chicago and Boston fires of the 1870s, were built to “insurance code” rather than to the sloppier requirements of local government.

This certification came to mean that the insurers, rather than the State or the trade, increasingly determined the standards to which the physical and legal world should be held. In late-nineteenth-century America, even the validity of land title came to depend on whether it could be insured—insurance became a stamp of approval rather than a stop against ruin.

A practice like this was clearly too attractive to keep within the bounds where it makes most sense. After all, if insurance can offer you sound title to your land, a house worth owning, and the confidence you won't be blown to atoms on the train to work, why can't it bring the same security to the rest of life—to, for instance, your ability to make a living? Loss of livelihood was a pressing issue in a world with no welfare and hideous working conditions. The earliest mutual societies, the medieval guilds, acknowledged the probability of a member's losing the ability to work through sickness or injury and the need to do something. Hatters do go mad, tailors blind—these were predictable risks that club dues could cover, since all the members had a clear if unmathematical sense of the frequency and severity of loss.

The Industrial Revolution changed all that: mass employment not only increased the danger of work but destroyed the mutual principle, removing the onus from fellow workers without putting it on the employers. Miners choked, cotton-spinners coughed—the risk was still concrete and quantifiable, but no one was obliged to take it on.

Not until 1880 did a British government, having dealt with the religious instruction, drinking habits, and drains of the laboring classes, address the question of injury at work with the Employers' Liability Act. The employers, forced at last to acknowledge some responsibility, were quick to pass it on: the first workmen's compensation insurance companies appeared almost immediately.

The ground plan of this business shows slight but significant deviations from simple probability. For one thing, the person insured, the employer, is not really the person who has borne the loss: the mill girl loses her finger, but the mill owner loses only in the sense that the State has assigned the fault and the cost to him. He, in turn, passes on this cost—in the further hope that the insurance company's trained investigators will find ways to adjust the loss and haggle with the State. The finger—the thing of value—is too easily lost again in this complex machinery of transferred responsibility.

This is not to say, however, that everyone in the industry is shifty: Vince Marinelli is a site inspector in Manhattan for a large workmen's compensation insurer. To walk the streets with him is to see a different city. In place of the horizontal torrent of strangers there is a vertical forest of friends, calling and whistling down greetings from scaffolding on every block. Priestly in dress and manner, Vince is a celebrity: although he's an insurance employee, he is known and loved in every trade and on every site from one end of the island to the other—because he saves lives.

“No workmen's comp, no work—so sure, I can shut a job down if I have to. But who wants to do that?” Two weeks before, Vince had dropped in on a West Side job, an office building with an impressive eight-story atrium. “The steel just topped out. New trades were going to be coming on, maybe not so familiar with the site. Now, atriums—I don't like them: you're working on a building, you don't expect a big hole in the floor. So I went to the general contractor and said: ‘Look. For me: rig a net across that, OK?' And thank God he did—three men dropped in that net the first week. If you can do something like that occasionally, guys don't mind so much you hassling them about wearing their hard hats. It's like they know they got someone looking out for them.” In medieval times, Vince would deserve at least beatification and a statue, carrying his attributes of clipboard and cellphone.

The fact that insurance companies have taken, however indirectly, a moral responsibility for preventing misfortune has opened them to the charge of moral (and legal) responsibility whenever it happens. Nowhere has this been clearer than in the American asbestosis story of the past thirty years, where hundreds of thousands of people have claimed compensation for the effects of something that was not even classed as a risk when the relevant insurance contract was written. Nothing about asbestosis relates to the Law of Large Numbers; loss and premium are entirely unconnected.

“Once our grace we have forgot, nothing goes right: we would—and we would not.” By entering, or being drawn into, the arena of workmen's compensation, insurers abandoned their own guiding principles and now find themselves ruled instead by the twin tenets of American personal-injury law: Somebody Is Responsible and Go Where the Money Is. These, you must know, have nothing to do with probability; they are inevitability.

 

“Consider the sequence of independent events a
₁
, a
₂
. . . a
_n
”: as basic a phrase in probability as “Construct triangle
ABC
” is in geometry. As with all the best magic tricks and confidence games, the hook has been cast and swallowed in the first sentence. “
Independent
events”—how difficult they are to imagine, let alone consider! Nothing in real life seems independent: you met your soul mate
because
you went to a Christmas party; your neighbor lost his job because of Mexican wages; your aunt won't travel by plane because of Arab politics. Industries like insurance that work by probability have first to establish what is and isn't independent—like sexing day-old chicks, it's a job that requires both experience and instinct.

The desire to free up capital, balance portfolios, and limit loss prompts insurers to pass on risk to others—just as bookmakers “lay off” liabilities by betting with other bookmakers. Sometimes this can be a disastrous process: During the 1980s, the London market in excess-of-loss reinsurance—the “LMX spiral”—saw the same risks circulating through Lloyd's again and again, with syndicates effectively, unwittingly, paying themselves to insure themselves against ruin. These policies seemed to be independent risks, but were in fact the same great risk—total market insolvency—in different guises; as a result, when one syndicate made a loss that triggered its excess-of-loss policy, the liability would bounce back and forth between syndicates, amplified at each bounce like a pinball trapped between spring-loaded bumpers. It left many Names destitute and nearly destroyed Lloyd's.

The simpler method for an insurance company to lay off risk is to secure it to one of the great cold, serene lakes of capital that lie beneath the Alps: Swiss Re, Munich Re—the reinsurers. Although reinsurers do redistribute some risk back into the market, this is essentially where the music stops. Your house, your car—even your life, is ultimately secured by one or another of these vast companies. For them, sitting in the last of the chairs, there can be no laying off, no pooling and sharing of risk—so what is left? The same technique used by the Chinese merchants on their way down river, five thousand years ago: diversification.

Thomas Hess occupies a large top-floor office in Zurich. “OK, nobody wants to insure against something that won't happen. So of course, we will pay out—a lot—every year. We have to know when these payouts are independent and when they are cumulative. We could assume, for instance, that earthquake insurance in Japan and motor insurance in Germany are independent; but earthquake in Japan and motor in Japan could be cumulative if, say, a highway collapses. See?

“It's also information arbitrage; we know more about risk, so the clients don't have to. They can sleep at night.
We
sleep at night because we can say no if the risk doesn't suit our appetite. I tell you, I feel a lot more secure running an insurance portfolio than I would running an airline. An airline has all its risks bunched together—and if it doesn't take those risks, it's out of business.”

His company has been in business since 1863, two years after a great fire in Glarus revealed to the Swiss, as London's had to the English, how financially insecure the physical world could be. “We've been in business for some time, it's true,” says Mr. Hess, “but even more than a century is not such a long period to compare risks and be sure of probability. Catastrophe losses—hurricanes, earthquakes—are getting bigger; but is that because these phenomena are worse or because there are more people and more of them buy insurance? Think of how much has been built in Florida since 1920: all in the path of hurricanes and all insured. The probability of disaster may not change, but the exposure does.”

The best diversification plan balances risks as they are perceived at the moment—but what if one force is driving all risks in the same direction? “Climate change is reality. There will be effects on living conditions, agriculture, business—it's certain. It's not just catastrophe cover: conditions could change for health insurance or credit insurance—all because temperatures rise,” says Mr. Hess. “Global change is just that—global. These are not independent events; we can't completely diversify between them. That's why we prefer yearly contracts—if you can't quantify risk over the long term, don't insure it over the long term.”

The independence of risks is an
a posteriori
matter, derived from observation—but human action can suddenly combine what had seemed discrete. Life, aviation, and building insurance were considered separate lines of business with low correlation between them. Even in the same country, they counted as diversified risks, helping to balance out the reinsurer's portfolio—until the morning of September 11, 2001, when all three came together with such horrible results. Three thousand lives; $45 billion; the biggest insurance loss in history. The insurance industry's assumptions had been shaped by limited experience. What it defined as the total loss of a skyscraper by fire was simply damage to the interior of ten floors: the worst that could happen before the firefighters put out the flames. Insurance was priced on those assumptions—no one thought total loss could mean . . . total loss.

We may talk of things as simply happening, obeying their own laws—but our own involvement changes the conditions so radically that we would be far more accurate talking about “beliefs” rather than “events,” and “degrees of certainty” rather than “degrees of likelihood.” As the man from Swiss Re says: “Reality is never based solely on the probable; it is often based on the possible and, time and time again, on that which was not even perceived to be conceivable beforehand.” Probability, once applied to the human world, ceases to be the study of occurrence; it becomes the study of ourselves.

6

Figuring

—T. S. Eliot,
The Rock

 

 

 

 

 

 

I
t's a familiar anxiety: sitting on a chair either too small or too hard, we await the expert's assessment, trying to read the results upside down from the clipboard. A medical test, a child's exams, an employment profile: hurdles that, once leapt, allow life to continue. Then come the magic words—“perfectly normal”—bringing with them an inward sigh of relief.

Perfectly
normal? The phrase is a modern cliché but also, when examined closely, a very odd idea. What makes the normal perfect? Do all kinds of normality imply perfection? Would you be as relieved if your health, child, or employment prospects were described as “perfectly mediocre”? And yet the two words, mathematically, are the same.

Normal is safe; normal is central; normal is unexceptional. Yet it also means the pattern from which all others are drawn, the standard against which we measure the healthy specimen. In its simplest statistical form, normality is represented by the mean (often called the “average”) of a group of measurements: if you measure, say, the height of everyone on your street, add up all the heights, and then divide by the number of people, you will have a “normal” height for your street—even if no particular neighbor is exactly that tall. Normality can also be thought of as the highest point on de Moivre's bell curve: we saw how, given enough trials, events like rolling a die “normally” represent their inherent probability. Normality, in modern society, stands for an expectation: the measure of a quality that we would consider typical for a particular group; and, since we naturally seek to belong, we have elevated that expectation to an aspiration. Man is born free but is everywhere on average.

Society recognizes five basic qualitative distinctions: gender, nationality, skin color, employment, and religion (some might add sexual orientation; others insist on class). Almost everything else we measure numerically, basing our sense of what's normal on the
distribution curve
generated from
quantified observations
repeated
over time
or
across a population
—all phrases taken from statistics. This means the normal can drift: without having changed ourselves, we can find we are no longer average (much as the normal Floridian, born Latino, dies Jewish). The United Kingdom Census for 2001, for instance, tells us that 40 percent of children are born to single mothers, a great leap from the qualitative expectations of fifty years ago: working dad, housewife mom, couple of kids—all white. The same census also reveals that 390,000 people state their religion as “Jedi.”