From spreading out in a group to hunt dangerous animals to dividing valuable cargo on shipping routes, the idea of dividing risk is an ancient idea. It was Babylonian merchants who devised the first known insurance policies, as some chose to hedge their investments by paying an extra sum to cancel loans, should shipments become lost.
In ancient Greece and Rome, the guild system meant that craftsmen would pay their dues to the guild upon completing their training. The money accrued acted as an insurance fund: in the event of an accident or damage to a master’s practice, the guild would step in and offer financial support.
It wasn’t until the medieval period, however, that tools were developed to assess uncertainty and risk. Geralomo Cardano, an Italian lawyer, physician and friend to Leonardo da Vinci, liked to gamble. In order to try and maximize his winnings, he began to investigate the basics concept of probability when throwing dice.
His work would prove important just over a century later, in the mid-1660s, when Blaise Pascal and Pierre de Fermat defined a method for calculating probabilities that enabled forecasting, with gambling once again the driving force. While in games of chance the outcome of an individual trial cannot be predicted with certainty, the mathematicians said, collective results over a long period of time display a certain regularity.
It is this concept that formed the basis of decision-making in risk management, and the insurance industry in particular. When setting premium rates, insurers look at the collective experiences of a large number of individuals, without knowing what will happen to a particular person.
Interestingly, in the age of big data, this approach is showing signs of beginning to change. With increased access to personal information, insurers are starting to rely less on more general probabilities and instead make more accurate assessments of each individual’s riskiness.
This video is an excerpt. To watch the full video on the history of risk, click here