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Big data analytics and the use of predictive modelling are not new in insurance.
For many years, actuaries have analysed large amounts of data to identify trends and anticipate future events (for instance, to assess people’s life expectancies) and to price products (such as life insurance).
However, technological advances mean that the volume of data and computing power are increasing.
These, combined with advanced data mining and analytics tools, enable insurers to cover new risks, to offer products better tailored to consumers’ needs and to provide better loss prevention advice.
Balancing risks and benefits
Nevertheless, some policymakers and consumer groups are concerned that the use of big data analytics could lead to higher prices, which could exclude certain consumers from accessing cover.
Yet, there is currently no evidence that insurance cover might become unaffordable for certain groups of people or that some of them will be unfairly discriminated against.
On the contrary, insurers have every incentive to offer attractive insurance products for everyone and to cover as many people as possible.
And, importantly, existing legal frameworks, such as the newly adopted Insurance Distribution Directive and the General Data Protection Regulation, provide adequate safeguards to protect consumers from discriminatory and unfair practices.
It remains to be seen to what extent insurers will use these new tools and therefore what impact they will have. It will ultimately be consumers — and the products they choose — that dictate how big data analytics changes insurance.