People naturally tend to be risk averse. While some individuals live for the adrenalin rush of betting the farm on what seems like a good chance, most people are reluctant to assume even much lesser risks. This is hardly a new story: Insurance evolved roughly 4,000 years ago, when Babylonian lenders and ship owners devised ways to spread the risk of a ship loaded with valuable cargo being lost at sea, and reward those who assumed it.
Modern insurance is based on actuarial science and, increasingly, big data. Insurance companies have vast pools of data on life expectancy and factors that impact it, as well as car accident data such as the percentage of cars that can be expected to get into accidents every day, the damage and injuries those accidents will cause, and costs of recovery and repairs. Insurance companies use all of this data to calculate premiums that allow them to come out ahead, despite the fact that all life insurance policy holders eventually die, and many crash at very predictable rates.
There are, however, scenarios that make life uncomfortably risky even for insurers, despite their risk expertise. Structural changes can render their data inaccurate. Climate…
