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09/02/2010

Trilovszky is a mathematician and a senior executive at Munich Re. She has worked for the company for 23 years, and has looked after customers in North America and Eastern Europe while constantly climbing the corporate ladder to reach her current position. Her job title is "Senior Executive Manager, Corporate Underwriting," and she is responsible for the insurance policies that are concluded with other insurers.

Hers is a classic career within Munich Re, and Trilovszky is probably a classic representative of the company: intelligent, eloquent, thoughtful and as levelheaded as an accountant. Munich Re expects its employees to be detail-oriented and precise, which also applies to their interactions with one another and how they dress. After all, this is a company that sells certainty and reliability in an unreliable world.

The kinds of gamblers who typically work in stock markets are not to be found at Munich Re, which values reliability and competency and prefers staid over flashy. The hallways are filled with men wearing suits in every shade of gray and dark outfits with gold buttons. At Munich Re, the extroverts wear Joop designer cufflinks and oversized Tag Heuer wristwatches. Women like Trilovszky stick to classic business attire, especially when they meet with clients for negotiations or with journalists to explain how the business works.

Laws of Probability

"Determining the price of an insurance policy isn't all that different from evaluating a game of dice," says Trilovszky. Assume you have six euros, she explains. If you want to keep these six euros, no more and no less, how much do you have to bet on each roll of the dice? The answer is one euro, because the probability of rolling a specific number is one in six.

The actual ratio will likely be different once you start rolling the dice. But the more often one rolls the dice, the closer does the appearance of each number approximate a ratio of one to six. Munich Re's business is based on this law of probability. The more frequently a specific event occurs, the more accurately can the probability of its occurrence be calculated. Take, for example, an individual German's risk of dying within the next 365 days, which is 1 in 88. This means that one in 89 Germans will no longer be alive on Sept. 1, 2011.

Of course, rolling one die isn't enough to make a statement like this. A large number of dice has to be rolled an extremely large number of times to determine the probability of every possible cause of death. It gets even more complicated when the goal is not to make a statement about a large group like all Germans, but about individuals within this group, and about the probability that these individuals will die of a specific cause. In that case, one is no longer rolling a large number of dice on one table, but a large number of dice on as many tables as there are individuals -- around 80 million tables, in the case of the population of Germany.

And when the goal is not only to calculate the probability of one person dying of a specific cause, but also to determine the age at which this is likely to occur, things become indescribably complex. Nevertheless, it's still possible to make this and many other calculations. For example, the probability that a 40-year-old man will die of cancer in the next 10 years is 0.7 percent. It jumps to 2.5 percent if the man is 50, and to 3.7 percent if the person in question is a woman and she is 60.

What is the probability that Cologne's historic Old Town will be flooded a second time within the next year? Ten percent. Or that San Francisco will be hit by an earthquake this year? One percent. And what about the football World Cup in South Africa -- how likely was it that it would be cancelled because of a terrorist attack? That probability, according to the estimates by Munich Re's risk analysts, was also 1 percent.

Putting Theory into Practice

Those analysts are the people who put theory into practice at the global risk headquarters. Their job is to adapt the mathematicians' models to individual cases, to keep themselves informed about things like security strategies, the strength of fire walls, the performance of sprinkler systems and, if necessary, the stability of national governments. They view the world as a collection of risks and are constantly trying to quantify these risks.

If McDonald's wants to insure all of its restaurants worldwide, or Walmart all of its stores and warehouses, it is up to the analysts at Munich Re to examine the potential risks that confront every restaurant, every Walmart store and every warehouse.

Using geographical coordinates, they determine, for each building, the probability of earthquakes, major storms and floods. The entire world is stored in the databases at Munich Re in many different forms. Some data sets specify the probability of an earthquake occurring at any given point on Earth, while others contain detailed, site-specific data on the likelihood of floods and storms.

Other data can be used to draw conclusions on how storm-proof a given roof is, be it a flat roof, a pitched roof, a half-hip roof, a lean-to roof or a barrel roof. Every roof and every building is classified, and factors like mode of construction, materials, shape, height and width are entered into programs, evaluated and considered in relation to other factors, such as the type and quality of fire protection measures, the kind of product being stored, the manner of storage, the labeling of emergency escape routes and, finally, the human factor. Do the employees seem motivated? Is there trash lying around? Are tools put away at the end of the workday? How often is the building burglarized?

The answers are entered into databases. Deviations from the norm are calculated and taken into account. In the end, after everything has been weighted -- from fire protection to labor organization to the crime rate -- the premium appears. One premium. One premium for all of McDonald's restaurants or for Walmart's global empire.

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• Part 1: Inside Munich Re, the World's Risk Center
• Part 2: Like A Game of Dice
• Part 3: An Authority on Fate
• Part 4: Possible and Impossible Risks