Imagine a world in which your digital footprint gets recorded in real time into an immutable, highly encrypted distributed digital ledger (for example, a blockchain) that is connected to your watch, phone, car, smart house, private virtual assistant and wearable health tracking devices that track your sugar and cholesterol levels, brain activity and molecular decay.
This data can provide insights into your driving and sleeping behaviour, moods and stress, recently acquired taste for expensive wines, the extent of your social network or the fact that your running shoes have lost their grip.
Data ownership
You own that data and have the private encryption key that allows you or others to decrypt it. Your private virtual assistant — an AI that has learned to defend your interests — communicates and negotiates with other AIs on how to use that data to, for example, get access to better and more personalised insurance products. Once granted access, the underwriters’ AI accesses unstructured data lakes containing the immutable record of your past behaviour.
Based on the information, AI-enabled blockchain smart contracts self-issue a personalised insurance policy, designed only for you, with clauses, prices and coverage that self-adapt in real time to your needs by learning from your past behaviour and assessing your riskiness in real time.
This AI may be able to infer that despite the fact that you consistently drive at a speed that is 10 per cent higher than speed limits, what actually constitutes a higher accident risk factor is that you have slept less than four hours. Indeed, before you even leave your home, your private AI assistant has shared this information with your connected car and that this may affect your driving.
Your car may suggest driving itself that morning or, if you refuse, since you are in a hurry and think you will be able to get to work more quickly than your driverless car, it will start communicating with the AIs of neighbouring cars to make sure everyone gets to work safely. This will all be followed closely by your smart insurance policy, which may decide to charge you more or may decide to help you reduce your stress and incentivise you to change your habits.
Wearable devices
The wearable device tracking your brain activity will have the intelligence to let you know many hours in advance that you will be having a migraine or to give you tailored games to play on your smartphone to avoid certain parts of your brain losing its memory or certain types of synapses disappearing. It will let your smart disability insurance policy know about the changing odds of developing Alzheimer’s disease.
Even more, AIs could not only assess riskiness of individuals, but also automatically pool them to mutualise against those risks in large, decentralised, autonomous peer-to-peer insurance networks and find investors whose risk appetite is adequate to insure/reinsure them.
Key points
In a hypothetical world, AI-enabled blockchain smart contracts self-issue a personalised insurance policy
AI could not only assess riskiness of individuals, but also automatically pool them
The future of insurance is very likely to be one in which the nature of risk, and the relationship between underwriters and customers is radically changed
Incredibly, every piece of technology needed for a world like that described in such an extreme (arguably dystopian) view of the future already exists. And some of them are likely to appear in some consumer segments and in some markets.
While there may be some debate about just how deeply advanced technologies and methods have already penetrated the insurance industry, the reality is that insurers as a whole are increasingly investing in technology, in analytics capability and in data.
Aside from what can be imagined for technology and analytics, there are, of course, a whole host of factors that will determine how the future will actually unfold that need to be built into thinking.
Regulators will keenly watch the use of personal data and the role of insurance in a world that increasingly facilitates risk assessment that considers a “segment of one.” Consumers will be particularly concerned about cyber risks, which will be exponentially larger in a fully digitally enabled world.
Furthermore, insurers’ access to the levels and types of data suggested in our imagined scenario above would appall many consumers, who might not engage with any insurer that hinted at such a prospect.
Analytics innovation
Regardless of the speed at which insurtech and data analytics innovation occurs, the future of insurance is very likely to be one in which the nature of risk, the value of data and the relationship between underwriters and customers is radically changed. The impact will be felt on products and distribution channels, customer and risk models, regulatory frameworks, and the transition into cognitive big data and next-generation predictive analytics.
Like any other transformation, this requires strategy and direction, crucially underpinned by company views of the future state — despite the many uncertainties and out-and-out unknowns. Just as important is where the company fits into those future states, the associated implications for data and analytics, risk appetite, talent retention and attraction, customer relationships, market positioning, cost efficiency, and the required levels of innovation and change.
Opinions abound on the speed and extent of disruption, but there is general agreement that companies best able to ride the disruptive wave of insurtech are highly agile, geared to execute managed risk-taking activities/investments, quick to make major decisions, and are capable of forming strategic/exclusive partnerships when advantageous.
A well-articulated vision of possible scenarios, backed by sound data and analytics foundations, and a streamlined strategy for bold execution will foster such qualities.
Magdalena Ramada is senior economist, and Andrew Harley is global leader of the Advanced Analytics practice at Willis Towers Watson
