In the past, external data came in and carriers supplemented it, evaluated it and moved on. Recently, though, the data landscape in insurance began to change and rapidly so.

The idea of using external data is not new. As Silicon Valley Data Science points out: “As early as the 1930s, insurance companies combined internal and external data to determine the rate for policy applicants. However, it is only more recently that the speed of technological advancements has allowed insurers to dramatically redefine and improve their processes.”

The flow of external data has become a flood. Where is it coming from? There are five main categories of data sources: 1) Traditional; 2) Public; 3) Private; 4) Aggregated; and 5) Sensor. The examples of these sources are endless: Government and third-party databases have gone digital and are now publicly available. Social media platforms feature comments, product reviews and discussions. The Internet of Things brings input from connected devices, such as smart cars and home security systems. A vast array of information is also gathered from company call centers and websites.

Third-party data-set types continue to evolve, creating both opportunities and challenges.

These new external-data gathering methods are reducing the amount of information the broker needs to collect, which in turn reduces the friction between brokers, insurers and customers.

“Customer applications for insurance today are significantly shorter than before, thanks to external data. With basics like name and address, insurers can access accurate data files that will append other necessary information such as occupation, income, demographics, and more. This means expedited underwriting processes and improved customer experiences,” write the Data Science authors mentioned above.

These vast streams of data are also transforming the way insurers evaluate and price risk. There are valuable insights hidden within the sea of information and insurers need to identify and act upon them before competitors with new business models seize the market.

Coming up next, we will look into what insurers can do to get ahead of the data game.

To learn more, register to download “Harnessing the Data Exhaust Stream”.

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