On the way to visit a customer recently, I heard a feature on the radio that made me stop and think. The feature was about a fitness chain that was about to open the world's largest gym in Germany. The difference was the membership model. Instead of a monthly membership fee, users would pay with data.
As an employee of a data analysis software producer, this raised a lot of questions in my mind: How would it work? What about privacy? How does this change visits to the gym? What are my data worth and what will happen to the data? How does the chain refinance through my data?
The radio feature answered most of my questions. The chain was not planning to resell personal data. Training results and evaluations of health records can already be used commercially, for example through targeted personalized advertising in the gym or at advertising events. These data are of course also of interest to other companies, such as health insurers or employers, for example. They use it to see if a customer or employee is actively doing anything to improve their health.
Some insurance companies already use this kind of data, such as Assicurazioni Generali, the insurance company. It rewards healthy living with discounts on risk insurance or occupational disability insurance using a telematics tariff. This simply means that the customer has to pass data to the insurer through fitness trackers or smartphones.
I asked myself whether I personally would sign up to that kind of membership to be able to visit the gym. I found I was still skeptical, but I was not really sure why. After all, I already know that I give away a great deal of data without much thought to companies like Google, Facebook, and WhatsApp. Was I skeptical because this new contract would put a price on my data in the real world?
Tech companies have managed to gather a lot of knowledge about users through the collection of data, and this has enabled them to implement a variety of offers. Google, for example, has transformed itself from a pure search engine provider into a much-used platform provider. This, in turn, collects even more data and generates more knowledge about its users. Amazon is similar. Originally an online bookshop, we now use Amazon for much more. We regularly buy at the world‘s largest mail order company and, as a matter of course, we store data in the Amazon cloud or use the integrated music and video portal as Prime customers. Some of Amazon‘s own productions have already acquired cult status. Based on its market power, Amazon is even considering an entry into the insurance industry.
Insurance cover given in return for data? Would it work? Insurers are already offering customers more services and tariff options — some even in non-insurance segments — and want to differentiate themselves from the competition, offer customers value and improve their own position. This might be through an app to improve home safety, a discount for prudent driving, the option to manage all private contracts (including outsourcing) on my insurer's portal, or the option to purchase cloud storage via insurance.
In other words, paying for insurance in data may only be extending an existing trend. But would it really be conceivable? What would it be like?
Let's do a thought experiment
At the very least, payment in data rather than Euros would attract the attention of potential new customers. So as not to lose these immediately because of a complicated application process with a lot of questions to enable risk assessment, it would be good to keep the application process short and simple. This would probably mean a uniform price as much as possible. InsurTech start-ups have already shown us what this might look like.
The insurance ecosystem is both excited about the potential of AI in insurance, and concerned about how far the disruption will go. Read this report by SAS insurance experts on the scale of change ahead.
As the contract continues, we will have enough information about our customers through the data they provide. We would probably prefer to form a single large insured collective than a lot of small ones. As a positive side effect, criticism about discrimination would be reduced. To ensure that the data gives enough value to cover future claims and losses, we would need to reduce closing and administrative expenses as much as possible. The product should therefore be a pure online product, which the customer can complete and manage themselves without much support. If any help is necessary, we could use chatbots as a first level response, and employees where necessary.
We would also have to consider what data we would like from customers, and what we would do with the data. Obviously we would want information that would provide us with sustainable, risk-bearing and monetizable knowledge, increase customer loyalty, and perhaps even enable us to create a gamification factor. Possible data sources could be fitness bracelets or other wearables, connected cars, smartphones, smarthomes or any other sensor connected to the IoT, especially if it could supply real-time data. Real-time data streaming is particularly interesting when we want to generate value in real-time, such as offer an additional service or product.
How to monetize data?
Finally, the most important question: How do I make money from the data and the associated additional knowledge? There are no limits to the imagination, but with the appropriate opt-ins and good legal advice about data protection law, most things should be feasible. From additional paid service offerings, through advertising and cross-selling, to cooperation, many options are conceivable. Whether this is in the end actually enough to justify offering insurance cover just for data, I cannot judge.
What do you think? Would you take up that type of insurance? What would you do with the data as an insurer? I look forward to your comments.