Throughout its history, the insurance industry has always adopted technology. From the board and chalk used to underwrite the first (marine) risks at Lloyd's, to large computers to process data using punched cards, following the creation of databases, the portability of applications between servers thanks to the adoption of standard operating systems, and the emergence of personal computers. All of these have been critical moments for the industry in terms of the benefits of adopting these technologies, mainly aiming to provide greater security and traceability to recorded transactions, along with achieving greater efficiencies.

In 1983, with the adoption of the TCP/IP communications protocol, we were witness to the creation of internet while computing capacity continued to grow, following Moore's Law. With this, insurers were able to more easily integrate with the outside world and outsource parts of their value chain through functionality made available in websites.

While IBM pioneered the development and release of a smartphone called Simon Personal Communicator in 1994, it was not until 2007 that the iPhone was released by Apple, kicking off the smartphone revolution. With the possibility of having different applications in the phone, which would see its critical milestone with the emergence of its App Store, it has continued to grow in computing capacity, storage, and functionalities. Other brands followed the same path, offering smartphones, mobile apps and stores. Mobile, combined with the increasing data communication capacity provided by the Internet and mobile networks themselves, has put in the hands of consumers the technology that was previously only in hands of companies.

Thus, the insurance industry no longer sees technology exclusively as an efficiency generator but as an ally in improving the customer experience, whether it is the policyholder, a prospect or the intermediary. It also leverages all the technology that can be added through the use of internet, such as sensors (Internet of Things), distributed computing across the cloud, and integration with business partners to deliver innovative value propositions.

It is in this last instance of IT evolution that an impressive volume of new companies has appeared, like never before, seeking to improve or even completely change the customer experience with insurance through the use of technology. This phenomenon, due to its unusual growth and impact, is often referred as insurtech; mainly to refer to these new (startup) companies. However, under a broad definition of insurtech that term should not be exclusive to these new companies.

That said, the recent phenomenon has attracted a lot of interest in the industry and it is common to find studies that measure its evolution in terms of investment and the number of players. By the end of 2018, there were more than 1,500 companies operating in this space[1] and in 2020 the investment in them was US$7.1 billion represented by 377 investment transactions[2]. This exceeds 12% of the 2019 investment and by 20% the volume of transactions.

Prior to the start of the pandemic, our research showed that insurers were already making a good use of these new companies and expected to increase its use in the short term. The specialization that these companies offer, in addition to the customer experience they propose, make them in many cases an ideal partner to integrate within a broader ecosystem, either to generate efficiencies or improve experiences.

There are numerous examples of ecosystems in P&C, life, and health. Recently, at Celent, we recognized General de Salud in Mexico as a model insurer for their Amae initiative offering an ecosystem-based value proposition for patients with type 2 diabetes. Celent’s model insurer of the year was also a case of ecosystem play; in this case AXA XL with an ecosystem for the construction industry. Model insurers also shared this year their views on how to execute innovative initiatives with customer centricity in mind. Their aggregated views and insights are shared in this Celent report: Leaders Benchmark Client Centricity.

Carrying out these associations and ecosystems has its challenges. Our research at Celent shows that there are two main areas to consider: the type of innovation to be achieved, and the differences in focus and culture.

Understanding whether incremental or disruptive innovation is being pursued, for example, can lead to different associative models and vehicles chosen to carry out projects. Innovative organizations often split and protect disruptive innovations from the rest of their core business.

At the level of focus and culture, the differences that can lead to misaligned expectations, incorrect assumptions and below-expected outcomes must be recognized. We understand by culture the processes, metrics, symbols and behaviors of a group of people; we commonly describe it as "the way we do business here." The table below shows these cultural and focus differences that we often find between insurers and new technology companies in insurance, both shown as the extremes of doing business.

To make these partnerships work it is suggested to create a common plan and vision, this is especially important when working with emerging technologies and business models. Uncertainty requires a basic consensus on what we desire to achieve.

Then in implementation, political and technological barriers must be removed; find a way for both companies to formally work and to move forward at the required pace. This sometimes requires reviewing existing policies and deciding to work through new business models or separate units that are not constrained by technology and legacy processes.

New technologies certainly bring countless opportunities and working with experts has its benefits. While this is evident, it is far from easy to execute. New associative models and assembling digital ecosystems require new technological and cultural capabilities. It is a path of no return, in which no one can afford to stay in the middle.

[1] According to the Milken Institute

[2] Willis Tower Watson estimations