Internet of Things in the insurance sector – creating the right ecosystem

Gartner predicts there will be over 20 billion connected devices by 2020, the resulting exponential growth in data will have massive potential across a variety of insurance businesses. Increasing prominence of autonomous and driverless cars, home automation technology, consumer wearables and industry internet 4.0 will change the shape of insurance business models, and the processes and methods which insurance companies use to assess and price the risk, manage claims and engage with customers. We see insurance companies increasingly moving from protection based paradigm to prevention and preservation based paradigm where insurance companies will not only protect financial losses of its customers, but also make them aware of emerging risks and partner with them in preventing occurring losses or reducing the impact in the event of a loss.

Telematics, autonomous cars, home automation technology or consumer wearables - one thing these technologies have in common is the ability to create insight based on users’ context. This insight can be used to deliver personalised services. Today’s customers not only want, but are able to demand, products and services that are personalised to their specific needs, wherever and whenever they require them. Customers are no longer segmented in simplistic categories such as age, gender or financial strength. Insurers can now build a picture of their personality, their habits and of course, their potential risks.

Meeting these expectations can be a challenge for insurers though and to take advantage of the opportunity, a change in organisational model must be considered. This re-evaluation of the ecosystem can help to reinvent an insurer and align its offering more closely with the customer’s need. There are three models that insurers can look to adopt, all of which have their advantages – and disadvantages.

A customer ecosystem allows the end-to-end ownership of the customer journey, directly influencing and supporting the needs of the customer. This allows insurers to gain insight into the behavioural tendencies of the policy holder and make real-time recommendations based on analysis. This customised approach adds value and ultimately, improves the customer relationship. In this model, insurance companies will seek to bring in products and services of partners that are complementary to their services, for example, embedding road side assistance or home and care management services, as part of their product and service offering.

Secondly, there is a platform ecosystem. This option could enable storage, exchange and usage of data within a wide variety of companies – insurers being one of them. Examples of such platform based ecosystems are Uber, AirBnB and Amazon. This type of ecosystem provides a mutually beneficial environment for all members of the platform, from home automation providers such as Nest providing data to home insurers, to TFL sharing its data with Google maps. Ultimately, it is about matching the best solution for customers by working with each other to provide a flexible and holistic offering. This will require insurance companies to build flexible products and pricing engines supporting lego-style, on-demand product and services that could reside in many ecosystems.

The final option is to create a co-supplier ecosystem. This is a more traditional model, bringing together different core competencies from established market leaders. BMW working with Allianz or more recently, the partnership between Alibaba, Tencent and Ping An, a trio that already handles billions of policies by combining their respective expertise. This model allows businesses to build a custom ecosystem along with their partners supporting and taking advantage of each other’s loyal customer base.

Internet of Things is as much about setting up the right ecosystem model as it is about sensors and data. While data can add huge amounts of value to businesses and their customers, without other factors in place – such as the right business model, the tools for collecting, analysing and sharing the relevant type of data, and the correct standards and policies – organisations stand to gain nothing. However, once it has been refined, it can be used to provide valuable insights that can help to add value, improve the customer experience and drive revenue.