Data has always played a central role in the insurance business model, whether to assess risk, set policy prices or to retain loyal customers. Now, new pricing practices are inspiring insurers to take a fresh look at not only their current datasets, but newer ones that are available in the market. By now, we’re all familiar with the predictive power of insurance data analytics, but how much data is accessed and how it is used is just as important when assessing risk. Too much data from varied platforms and suppliers can slow down the time to quote. Too little data and you risk gaps in knowledge that can lead to higher claims costs, not enough coverage and unsatisfied customers. So, how do you avoid the pitfalls of too much or too little data and find the data sweet spot?

The what, why, when, where and who

Narrowing down the major underlying need for data is elemental. As an insurer, you must assess how a new dataset could benefit different functions and areas of your business. For example, if you choose to invest in a new identity verification solution using email intelligence, this could help support fraud prevention across commercial and home insurance lines. Before investing in new datasets, ask yourself:

  • What outcomes are required and what are the predictive qualities of different datasets to match them?
  • Why is data required?
  • When is it needed in the policy cycle? Is its predictive capability just as good for claims as it is for fraud prevention or policy cancellations?
  • Where in the business is it required most and why?
  • Who is the customer? Is it equally effective in motor, home or commercial insurance?

Choosing the right insurance data

Lack of data should never be a problem in today’s insurance market. At LexisNexis Risk Solutions, our robust data sources draw from more than 83 billion records derived from over 10,000 data sources. So, the data is there, but how do you know what data source to access? A good starting place would be to develop a “wish list.” By drilling down to what’s going to bring you the most value, such as policy history and claims data, gained attributes can help you understand the market’s experience of a particular customer – not just your experience.  Leveraging third-party data can be beneficial throughout the customer insurance journey – from quote to claims and everything in between. 

Chosen wisely, new data offers the power to deliver fair and accurate pricing; delivering the right products for the risk and ultimately, a more personalized and streamlined customer experience. Consulting with data specialists – like LexisNexis – to ensure data enrichment strategies address the problems you want to solve may be one of the best investments you can make in your business.