When the Hollywood bombshell Betty Grable had her famous legs insured for $1m by Lloyds of London in the 1940s, she was not only protecting a valuable asset – she was giving a boost to an industry in its virtual infancy. At the time it was relatively common to insure one’s home, business premises, motor car or shipping line against quantifiable risk, but it was another thing altogether for an insurance business to try to calculate the incalculable – like the risk to a film star’s legs, or more recently, a country singer’s bosom (Dolly Parton’s assets were insured for £6m). Lloyds of London have made a science out of predicting unusual risk. Bruce Carnegie-Brown, current chairman of Lloyds agrees that information and data are key elements in measuring risk, but insists that it’s more important to possess the expertise to use the data properly. Today, if there’s a chance something can go wrong, someone will try to insure against it, so it’s vital to get those calculations right. Lloyds, for instance, are paying out on claims for unprecedented events like the Californian wildfires of 2019, admitting that they underestimated the extent of the disaster, and the degree of damage. Extreme weather events are posing problems across the insurance industry, whose models need to be regularly amended to take account of new climate-related risks. Using data correctly can lead to low insurance costs for low-risk customers, while higher risk clients face much bigger premiums. But the industry is having to navigate stormy waters. Across the world governments are stepping in to prevent insurers from using the abundance of data that exists today on gender, age and race, to calculate risk. In the EU, for instance, insurers are prohibited from using data which could be seen to discriminate on the grounds of gender – which means women drivers, who according to all the statistics, are the safest drivers, can’t be given cheaper car insurance.