Harnessing “big data” is proving essential for insurers seeking to maintain and increase market share and profitability, according to Fitch Ratings, who said that those that fail to keep pace risk being marginalised or coming under pressure to consolidate.
“Many elements of the insurance business could be transformed, such as distribution, risk selection, pricing and claims management,” Fitch said.
“The insurance industry’s core functions historically used large volumes of data to assess and price risk and predict future claims experience. But insurers have been slower than companies in other sectors to adapt their business models to rapid technological change.
“Expansion in computer processing capabilities, data storage capacity, the proliferation of internet use and the development of “smart” devices has created new opportunities for insurers to access and process information.
“The gap is starting to close now that insurers have realised the potential of modern big data, but it has helped leave the door ajar for outside technology disruptors, which we believe will play a meaningful role as either direct competitors or technology partners to the major insurers.
“The most obvious potential for big data is in improving risk analysis and pricing. Non-life insurers have made the most progress so far, using data analytics and predictive models for greater price segmentation and optimising claims management.
“Significant opportunities in auto insurance lie with telematics technology that monitors driving behaviour and generate a plethora of data to assess driver safety. Life insurers see similar potential in wearable devices that can help assess a customer’s lifestyle and health, enabling more accurate pricing.
“The expansion of big data analytics creates new challenges. The collection and analysis of sensitive personal data can generate privacy concerns. Data privacy laws and regulations have lagged behind rapid technological advancement and may lead to restrictions on data use and the breadth of data that can be collected as they catch up.
“More accurate pricing can also mean greater differentiation for higher-risk customers, which could be perceived as discriminatory. This could lead to regulatory intervention to limit the use of big data, or the pricing impact of its use in some sensitive product segments.
“But we expect early movers to gain a significant advantage, with the reward on technology investment increased by scale and network benefits. Those who reach critical mass first can pick the best risks and achieve operational cost efficiencies compared to the laggards.
“Smaller insurers that lack the resources to invest are most at risk. Benefits from scale tied to greater technology use and investment will also contribute to further M&A activity in the sector.”