The Rise of Predictive Analytics in Insurance

The first auto insurance policy was sold to Dr. Truman Martin of Buffalo, New York, in February 1898 by the Travelers Insurance Company. As someone who appreciates data, what stands out to me is that the first odometer patent for an automobile was issued in 1903, and it wouldn't be until the 1920s before odometers became a standard feature on most automobiles. In the early days of writing auto insurance policies, the industry didn't have access to such a simple piece of data.

Fast-forward to today when the insurance industry is one of the most important consumers of data. Whereas previously, insurance companies didn't even have access to data such as how far a car was driven, now some companies will allow you to install devices or software, which provides them with real-time data about your driving behavior.
To further illustrate how quickly things are changing in the insurance industry, the graph below highlights an increase in the number of Google Scholar articles published on the topic of predictive analytics in insurance over the years.

Unfortunately, it's easy to feel left behind by the new world of data analytics. Even people who work with data on a regular basis can get a little overwhelmed. In describing the success of implementing a new predictive analytics model, insurance provider Lemonade asserts: "it's not something that an old-fashioned company could simply adopt and adapt; these tools and techniques are difficult to graft onto a company that wasn't built with them as a core design principle."
Fortunately, as data management and predictive analytics become more valuable, you don't have to have Lemonade's models to take advantage of the shift in the industry.