Historically, insurance companies have used SMALL data to make BIG decisions. Today, insurers are using BIG data for SMALL decisions.
What does this mean?
Traditionally, insurance companies have aggregated data to group risks into broad categories based on basic factors, such as gender, age, martial status etc. For example, let’s consider auto insurance. They have assumed that all young, single male drivers are reckless and that middle-aged, married, female drivers are more cautious and priced their products accordingly. While the law of averages might back up this conclusion, we all know that each individual driver is different.
Fortunately things are changing.
With modern technology insurers are able to gauge risk more precisely down to a micro-level. For example, insurance companies are now using telematics data to assess each driver based on driving behavior such as hard braking, acceleration, speed and distance traveled. But the usage of big data is not exclusive to auto insurance. Many life insurers are beginning to use the data from wearable devices as an extra rating variable. While property insurance companies are using data from sensors (Internet of Things) and working with vendors like Nest to recognize potential claims and hopefully prevent losses.
To learn more about how insurance companies are flipping the data equation and moving from experimentation to innovation download the research paper “Big Data in Insurance”.