Photo: iStockPhoto
Photo: iStockPhoto

De-jargoned: Law of large numbers in insurance

Insurance is about covering risks and not certainties

Insurance is about covering risks and not certainties. But even while covering an uncertain event, it is important for the insurer to know the probability of that risk actually becoming a reality, to be able to price the product right. Insurers rely on the law of large numbers to predict the risks.

Large numbers in real life

According to this law, the average of the results obtained from a large number of trials will move closer to the expected result as more and more trials are performed. Let’s explain this through a popular example. When you flip a coin, the chances of it landing head upwards are 50%, as the coin has two sides and it could show either head or tail. By this logic, a person flipping a coin six times should get tails at least three times, but when a coin is flipped just six times, the person may get five tails in a row. But flip that coin 60 times, and the number of tails would be closer to the 50% mark. As you increase the number of trials of an event, the number of occurrences of that event get closer and closer to the average chance of the event taking place.

Why do insurers apply this law?

An insurer can predict the chances of a specific risk taking place more accurately through this law. For example, as the number of people in a group (who want an insurance cover against a common risk such as car theft) increases, the real-life instances of that disaster come close to the expected average of that event occurring. In other words, the deviation of the actual event from the expected average will reduce, as the number of people in the pool increases.

So, larger the sample size, the greater is the predictability for insurance when doing the premium rating. By having a larger pool, the insurer can accurately predict the probability of an event and price the policy accordingly

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