What’s the deal with data?

Every January newsfeeds are jammed with endless streams of predicted business trends for the coming year. 2016 was no different. Data, big data, the data revolution, data analytics featured high on most of these lists.

What does this actually mean though?

Data isn’t new, we have always collected information on a large scale, particularly the insurance industry. The rapid rate at which data is generated also isn’t particularly new, we understand that it is valuable and therefore want more of it.

For example, in 1944 Fremont Rider, the librarian at Wesleyan University, estimated that American university libraries were doubling in size every sixteen years and calculated that the Yale Library in 2040 will have “approximately 200,000,000 volumes, which will occupy over 6,000 miles of shelves… [requiring] a cataloguing staff of over 6,000 persons.”[1] The prediction of huge growth in volume was correct.  However, this prediction doesn’t take account of technological developments, which would change the way we process and use this information.

History risks repeating itself here. If the insurance industry recognizes the growth of available data, but we do not yet understand the potential ways this could be used, we do not want to end up making a similar mistake to Fremont.

It is crucial for the insurers to recognize the potential of what lies beneath. The sector has been advanced with its collection and analysis of structured data, but new sources of live, unstructured data are becoming available due to the increasingly digital nature of how claims are handled.

These crucial pieces of information, which due to their unstructured nature are more laborious to utilize effectively, could be the key to a more productive claims management process. With the right tools in place however, these nuggets of intelligence could be fully integrated into your systems, not only improving your processes now, but for the future too.

Predictive analysis is able to spot trends across huge pools of data, identifying better ways to manage a claim or the likelihood that a claim is fraudulent. Text-mining can pick up on phrases in unstructured data fields like doctor’s notes, and identify complex claims that will need to be fully analyzed by the manager before a decision is taken. Auto-adjudication allows simple claims to be fast-tracked through the system, increasing customer satisfaction.

The Claim Lab is actively involved in research in this field, working with a number of insurers to implement these tools, harnessing the full capabilities of their data.  This will enable claim managers to focus on claims that need attention, apply the most effective process to each claim, and will  reduce claim durations.

Don’t those sound like better trends for 2016?

The Claim Lab  – Email us at  info@claimlab.org

[1] G Press(9 May 2013), ‘A Very Short History Of Big Data’ Forbes, available at: http://www.forbes.com/sites/gilpress/2013/05/09/a-very-short-history-of-big-data/.