Virtual replica technology, which thus far has been used in Industry 4.0 to prevent failures and predict behaviour, opens up an unlimited potential for insurers that has not yet been unlocked. The interpretation, in terms of risk, of the big data that people generate will represent a new paradigm in the creation and provision of products and services.
Rather like the dummies in car safety tests, stunt doubles for actors in action films, or in the olden days, food tasters for royalty, doubles in the physical world have played a role in the mitigation of risk in some very specific areas. In the digital world, however, the possibilities and applications are endless, and their use by companies to improve their financial performance could be boundless.
Now, doubles have made the leap to the digital world – these are digital twins, the technology that uses artificial intelligence to take full advantage of the big data extracted from the Internet of Things (IoT). With the masses of data generated by each and every object and person connected to the network, you can create a virtual replica with which the companies that own these data can make predictions and decisions.
In Industry 4.0, these digital twins of parts, engines, devices and systems operate as predictors of failures that allow businesses to maximise their profits. They also act as doubles in experimentation: what would happen if I subject double X to conditions Y and Z?
These virtual replicas are constantly updating and analysing data from their real counterparts and from the physical environment that surrounds them in their world. Users can ask questions of the digital twin and it will run simulations by analysing historical data, current data and forecasts. It will then predict what might happen in each case and the associated risk, and propose an action for the user to review and make a decision about. Even the virtual twin itself could act, when ordered to do so in advance, on the technology of the real twin, given that the two are linked.
The potential for insurers
Now that the digital twins model has been consolidated in Industry 4.0, other key areas of our economy are preparing to take advantage of this technology, especially the finance sector and the insurance industry, whose raison d’être is risk management.
The first to flick the switch will have a competitive advantage over others for quite some time. Everyone is aware of the power that they could have by connecting the predictions of a virtual model with commercial applications. In the words of Thomas Kaiser, vice president of IoT at the software giant SAP, digital twins are “an imperative in business”, and “companies that do not react will be left behind”.
If the idea is to insure vehicles or houses, their increasing hyper-connection will contribute to the development of digital twins that will be key for insurers to make predictive models and offer personalised services. However, if the subject of the business is not things but people, that brings a degree of complexity to the issue that has not yet been resolved and that, when the time comes, will result in a paradigm shift in the creation and provision of products and services in these sectors. Trying to predict the human factor will always involve a considerable margin of error, and herein lies the challenge for insurers who want to develop digital twins.
And yet we are generating increasing amounts of personal data through smartphones, fitbits or other devices in our homes, for example. But despite the availability of more and more data, the question is how to make them coherent and give them value, and how to translate them into probable behaviour (and its associated risk, of course).
There are those who point to the key role that a more direct and personalised relationship with the client could play. But above all – beware entrepreneurs – they point to the critical role of a new intermediary between data providers and insurers, specialising in interpreting the big data of insurance customers and in making it possible to create their digital twins.