Insurers could be marginalized with big data warns Fitch
Published: March 17, 2017
Updated: July 24, 2018
Author: Luke Jones
CATEGORY: Industry News
Fitch Ratings has warned insurance companies must capitalize on “big data” or risk being left behind by rivals, or targets for consolidation.
The credit analysing firm says big data is becoming essential for insurance providers that want to increase profitability and grow market share. Big data is defined as large data sets that show patterns and trends across customers and markets.
“Many elements of the insurance business could be transformed, such as distribution, risk selection, pricing and claims management.”
Many insurance companies have adopted big data to analyse large volume data for price risk assessment and to predict future claims scenarios. However, the industry has been generally slow compared to other sectors in recognizing the benefits of embracing new technology.
“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.”
Fitch adds that the ability to improve risk analytics is the most beneficial aspect of big data. Within the industry, non-life insurance companies have been the quickest to adopt big data, using the technology to optimize claims management and create more dynamic pricing.
Auto insurance companies could greatly benefit from big data acquired from telematics devices. Companies can use data to assess how a driver performs behind the wheel and several vehicle factors to change pricing models.
Acquiring data raises questions about privacy, but Fitch says laws are playing catch-up to technology:
“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,” Fitch said.
“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.”