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Fitch believes early adopters of big data will be able to reduce fraud, price more accurately and control distribution better, thereby gaining a vital competitive edge. Those that are slow to adapt may lose earnings or market position.
The term "big data" describes extremely large data sets that may be analysed computationally to reveal patterns, trends and associations, particularly relating to human behaviour and interactions.
Tackling fraud is currently one of the main uses of big data by insurers. False or exaggerated motor injury claims, e.g. whiplash, account for as much as half of fraud in some insurance markets. Big data analytics enables the rapid identification of claims characteristics that flag potential fraud, which would previously have been much harder to uncover.
Big data analytics is already widely used in motor insurance. For example, telematics devices that track drivers' mileage and braking habits enable insurers to adjust each policyholder's premium rate month by month to reflect the updated information on these risk factors. In Europe, insurers sold 4.6m telematics policies in 2014 according to Ptolemus Consulting Group, an increase of 240% from 2012.
Big data is starting to feature in health insurance. Insurers can provide policyholders with products such as wristbands that monitor physical activity, providing data for pricing that more accurately reflects each customer's individual risk profile.
Some insurers use big data to assess their intermediaries by analysing, for example, the volume, value and persistency of the business they source. This enables them to optimise their distribution channels to maximise profitability, which may vary significantly by channel or individual intermediary. Using real-time tracking, insurers can immediately identify sales spikes by product or intermediary that may indicate under-priced or mis-sold business, allowing fast remedial action.