How Big Data and Artificial Intelligence are Changing the Insurance Market

The study “Big Data Meets Artificial Intelligence” from the BaFin (Federal Financial Supervisory Authority) examines the potential impact of these two technologies on the financial and insurance markets. In a first article on this topic, we summarized the prospects for the banking market, and here we turn to discussing the changes that will affect insurance companies and their customers.

Market analysis of insurance companies

The insurance industry traditionally uses large amounts of structured data for actuarial purposes (e.g. actuarial calculations based on regulatory requirements). However, only a few providers worldwide are applying or testing out BDAI technologies throughout traditional value chains. A number of individual insurance companies have launched their first initiatives in Germany. There is, however, currently still no widespread use of BDAI on the global insurance market.

Two challenges have delayed the market penetration of BDAI: Firstly, there is, to date, little to no experience in dealing with new data sources and self-learning algorithms. Secondly, current data collection is often not geared towards behavioral data, and data silos to some extent restrict the data from being used in the BDAI context.

However, the German insurance industry in particular is now investing large amounts of money in digitization, especially when it comes to the necessary task of harmonizing core systems. One reason for this is that cost pressure has increased as a result of the ongoing low-interest phase, making efficiency gains through digitization increasingly attractive. Another reason is that there are increasing signs that new competitors – many of them with high technological expertise – are keen to enter the insurance market.

The impact of BDAI on the insurance market

There are many possible applications of BDAI in the insurance industry, including the targeting of specific consumers with individual product offers. That fact is just as relevant to conventional insurers as it is to new competitors.

Compared to Insurtechs and Bigtechs, traditional insurance companies generally have more experience with regulatory requirements, a deeper understanding of the industry, and a greater degree of consumer confidence when it comes to handling sensitive data. If they can maintain these competitive advantages while strengthening their BDAI technologies and competencies, they will be well placed to secure their market position, particularly when it comes to the customer interface. In the medium to long term, if traditional vendors withdraw from or are forced out of customer interfaces, they could focus on core functions such as risk bearing and collaborate with Insurtechs and/or Bigtechs.

Bigtechs’ competitive advantage currently lies in their greater expertise in BDAI technologies. They also usually have a broader client reach and a solid customer base that has become accustomed to the simple usability of the services on offer. This enables them to scale up new business models more quickly. However, they still have to acquire and develop their know-how when it comes to regulatory requirements and industry knowledge. One possible strategy could therefore be, at least for the time being, to only enter the insurance market at the customer interface and not to develop insurance products themselves, but instead to sell products from insurance companies. The next step would be to develop and distribute their own BDAI-based insurance products.

Insurtechs are currently particularly active both at the customer interface and as supporters of core processes. As a rule, they specialize in individual insurance functions. Despite their presence, Insurtechs haven’t yet had a significant impact on the market. The authors of the study do not expect that to change in the coming years either, because the majority of Insurtechs lack a broad customer base. Their strategy could therefore be to continue to use their BDAI expertise in cooperation with conventional insurance companies.

In general, efficiency gains generated by BDAI could increase the profitability of insurance companies in the short term. However, competition would cause market prices to adjust to the new cost situation. Through targeted BDAI-supported sales management, however, insurers could skim off the consumer surplus by offering customers offers at a price that corresponds to their individual willingness to pay. The greater individualization of products, which also goes hand in hand with BDAI, also reduces their comparability.

Another possible consequence of BDAI: increased predatory competition. Traditional insurance companies with high investment budgets could achieve market advantages as pioneers in the use of the new technology. Bigtechs and individual Insurtechs with a license to conduct insurance business could proceed in a similar way. Stragglers would have a hard time and could be driven out of the market if they do not find niche markets within which to locate themselves.

Impact on the customer interface

BDAI technologies will change both the targeted distribution of individualized products and the customer experience. In sales, BDAI enables continuous, individualized marketing that offers each customer products that are precisely tailored to his or her particular situation. That also includes temporary situational insurances, for example for car test drives or a skiing holidays.

Digitization has already simplified individual process stages for customers at numerous different insurers – when signing contracts, managing portfolios and settling claims. With BDAI, this can be developed even further. For example, by using bots and digital assistants that can automate even more processes. In this way, BDAI makes customer interaction with insurers easier, faster, and more individual.

The study “Big Data Meets Artificial Intelligence. Challenges and Implications for Supervision and Regulation of Financial Services” is available here.

Author: Editorial team Future. Customer.
Image: ©  Worawut – AdobeStock

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