The insurance industry is facing the possibility to improve the performance capacity of its business by relying on artificial intelligence and big data analytics. In this context, 'client risk-profiling algorithms' and knowledge of client habits/characteristics is going to be designed and implemented adequately, resulting in clients classified and assigned an accurate risk profile, together with the possibility to offer the necessary products at the exact price.

Insurance companies are developing automated tools for various products. This type of bundling (insurance and data-recording machine or security automation mechanism) is being used increasingly for products that have significant impact. Automated and semi-automated data recording tools are rapidly expanding in use in the consumer world, along with artificial intelligence tools that protect people and goods (and therefore reduce the probability and economic relevance of events covered by the relevant insurance policies). New technological developments are able to enhance the accessibility and quality of both data and algorithms. Insurtech aims high.

But there are risks as well.

From a general perspective, a legal review of automated and semi-automated tools used in the insurance business encountered grey areas with respect to fulfilment of the duty of care, data protection and treatment parity. In addition, the review found that insurance companies' internal regulation should control the use of technologies and data, and its adoption should aim to improve the quality of the service provision. Based on this consideration, the regulator must prepare guidance to clarify the fulfilment of the duty of care in Insurtech.

Therefore, Insurtech does not refer to sales of insurance and pension products via the Internet. Even if these activities require the necessary and proportionate supervisory actions to ensure that online distributors comply with a duty of advice, the application of innovation to the insurance business goes far beyond increasing the saturation of potential clients' life (through the manipulation of information and risk perception). This perspective also goes far beyond online comparisons of insurance products.

In any case, the use of big data analytics in unsolicited marketing and other relevant areas (such as pricing, underwriting, claims management, sales and/or risk measurement) requires a safe and sound approach, in order to analyze the benefits of the innovation and potential risks related to any unfair treatment of consumers.

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