The big data revolution is in full swing. It’s difficult at the current time to read an industry journal or attend a seminar where it doesn’t get a mention. Insurers have always been at the forefront of data analytics and this data-led revolution offers massive potential to those who are able to harness it.

This article looks at where this revolution may take the insurance industry over the next decade and what insurers and other service providers need to put in place to take advantage of these developments.

We focus on three key questions:

• What exactly is big data and where does it come from?
• In what areas of insurance does big data have the most potential?
• What do insurers and other participants need to do to position themselves to take advantage of this revolution?

We are clearly only at the beginning of this journey, but here we look forward to establish where big data might bear its first fruit for insurance organisations.

Notwithstanding big data’s huge potential, many commentators portray it as being all things to all people – to the extent that it will make traditional data sources and analytical techniques redundant. We need to be careful to not overstate where we are at now and where we are likely to be in a decade’s time. Gartner¹ declared in 2013 that big data had reached the peak of its “hype cycle” – a point in time when the benefits of these new techniques are perhaps oversold.

What is big data and where does it come from?

The term “big data” means different things in different contexts and there is no rigid definition. At a high level, big data refers to any large unstructured data source that can be collected, organised and analysed to produce business intelligence.

One of the great benefits of the exponential growth in computing power over the past two decades is that it has opened up data sources that were previously inaccessible due to their volume, structure and volatility. These new data sources may be rich with information but they also contain lots of “noise”. The big data revolution is largely about distilling one from the other and using the results to inform decisions.

Where does it come from?

Big data can come from a huge number of sources. Most insurers would already store substantial amounts of information about their policyholders and processes that they do not currently harness. Beyond these traditional sources, there is a wealth of external data sources for an insurer to consider – these include consumer behaviour data, credit information, geospatial data and of course, social media.

In a 2012 survey of nearly 800 organisations², IBM asked respondents who had indicated they were using big data to identify which sources of data they were collecting and analysing. The results showed that most respondents were still mainly using internal data sources.

How can an organisation harness the endless streams of information propagated by websites such as Facebook, YouTube and Twitter? What infrastructure will they need to do this? All sorts of businesses are asking themselves how these relatively cheap sources of information can help them to address challenges within their businesses and to unlock competitive advantages.

Where might big data have its biggest impact?

Insurance has always been a data-hungry industry. Some insurance functions lend themselves readily to analytic methods – these include pricing, reserving and risk analysis. While these are the traditional playgrounds for data-driven analytics, new data sources and improvements in modelling techniques are opening up a range of possibilities. Other core insurance functions that can start to use big data include marketing, distribution, claims management, customer insights and fraud detection.

In this section we take a look at what will likely be the initial battlegrounds for the use of big data within an insurance organisation.

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