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2020: After a few years into her career, a woman in her mid-twenties wants to switch to private health insurance. She uses a variety of different channels to search for an appropriate insurance tariff including searching online via the now well-established insurance provider - GoogleHealth. She discovers tariffs in which she needs to disclose data such as number of taken steps per day, sleep cycles, blood values and recorded pulse that were collected by a fitness tracker. She feels this information is too personal however. She remembers her parents’ insurance agent and makes an appointment at his office. But when she askshim about tariffs which do not require sharing health data, he also confirms to her: “I'm sorry young lady, nowadays, anyone who wants access to private health insurance needs to transmit his or her health data. How else should we determine the appropriate tariff for you?”

A frightening scenario or a glimpse of the future? Since their invention, insurance companies have been stuck in a dilemma: only the client knows how risky he or she really is. Insurers now are trying to come a giant step closer to a solution for this problem by using Big Data, the mass collection and analysis of data.

Behavior-based tariff models


An increasing number of health insurers offer health insurance tariffs that require the use of fitness trackers or fitness apps. These devices record sleeping behavior, eating habits, number of steps taken and vital signs, and they also inform the user about his or her performance progress. IT companies are already at work on improvements to the sensors so that more accurate data such as blood values can be collected. Google, for example, has recently developed a contact lens that continuously measures the blood glucose level in tear fluid and sends the measured values to the user´s smartphone.

Indeed, AXA France has already developed a health insurance tariff in which insured persons can voluntarily participate in a fitness competition. Depending on the activity, AXA offers discount coupons, vouchers for medical checks and even fitness trackers for free. At the end of the competition, participants are able to decide whether or not to provide their collected health data to AXA.

In some countries behavior-based tariff models already exist. Elsewhere, demand for behavior-based tariffs is currently increasing, but only gradually. The insurance companies are hoping to influence the lifestyles of their insured persons in a positive way in addition to the collection of data. Improved physical fitness lowers health risks and results in lower expenses for the insurance companies. It is conceivable that in the future the amount of the premium an individual pays will be based on his or her activity level.

In Germany the market penetration of fitness apps is increasing rapidly and many people already share their health information in social networks. According to a survey by the market research company YouGov, every third person is already willing to share personal data with his or her health insurer.

Big Data also finds its way into the service provision. Digitalization and increasing automatic processing have led to new possibilities for fraud, e.g., through digital manipulation of invoices. Special software for fraud detection is necessary in order to counteract this trend. Moreover, the treatment steps necessary for certain diseases can be analyzed with the use of a huge amount of data. If there is a significant deviation, the system sets off an alarm. The case is then examined in more detail and false billings can be rejected.

Are the threats of Big Data to be taken seriously?


With behavior-based tariffs we see the trend towards individualization. But what does it mean for the “community of solidarity” if each individual risk is precisely calculated? In many countries, after all, solidarity was once the original idea behind the business model of insurance.

Insurers currently react even with a sort of “voluntary commitment." Phrases such as “We do not use the data for the selection of new customers, but only for these incentives” or “Data from fitness trackers are good for discounts, but never stable enough for our actuarial services” can be heard today, but will this still hold true in the coming years?

And what does this mean for the customer? The permanent monitoring of an insured person allows insight into his or her everyday life. A personal behavior profile could be created and the existence of the profile may be at odds to the interests of the insured person.

The exchange and sometimes the dependence on data present risks of damages. Data can be hacked or manipulated, and the question remains whether the additional costs for security cancel out the expected business benefits.

A look across borders already shows that the collection of data can be against the interest of the customer. Some insurers in the UK negative weight traffic violations, and in some cases those who have grossly violated traffic rules lose their health insurance coverage.

A fine line

The opportunities related to the use of Big Data couldn’t be bigger for insurance companies, but the concerns raised by data privacy groups are equally as big. These groups criticize the lack of information regarding the use and visibility of data. A similar position is taken by the German Government, as was shown in a survey of members of parliament taken in January 2015 on the issue of data collection, storage and usage in the insurance business. The result was that anyone who wants to collect and process behavior-based data requires a written consent of the user. Solutions which are already in use will be tested regarding compliance with this requirement. A tightening of the legal framework is currently not being considered.
The amount of collected personal and behavioral data can be used to create a description of a person's personality and can be used to analyze interrelationships. Increasing digitalization is, on the other hand, also of benefit to users. The scenario presented at the beginning of this article describes what could happen. So what will happen if regulation does not efficiently solve the requirements which result from digitalization?

If insurers hands are tied in terms of planned new products and business models, it is anticipated that insurers from countries without such regulation or even technology companies like Apple, Google and Samsung will not wait long to close this gap in the market and thus displace insurers affected by regulation. Google has already taken a step in this direction with its investment in the U.S. insurance start-up Oscar health insurance which is strongly focused on behavior-based tariffs.
What happens if new insurance models or even individual risk profiles are sold to insurance companies such as Oscar that are not affected by regulation? Maybe this provocative idea is not absurd after all in light of current technical and analytical possibilities?

Insurers are stuck between the pressure to act due to the data sovereignty of disruptive competition and an increasing fear of regulation through legislation.

What to do

The guidelines for the standardization of user rights as required by data privacy groups are a first step towards data security, with which the door of innovation could be simultaneously closed for affected insurance companies. But a unified transnational privacy agreement does not protect against FinTech companies that pass the supervisory bodies and take over parts of the value chain (as has already happened in the banking sector).

Restrictions on Big Data to prevent the opportunities of digitalization from shifting to countries with less regulation or the entering of disruptive competitors into the regulated insurance market would be fatal to innovation. Instead, the definition of a fine line between digitalization and regulation is required, which creates a balanced relationship between the protection of users and the protection of innovation. Big Data is part of the 21st century and a general regulation of data collection and usage may not be effective.

The focus should be on the creation of transparency to consumers and on the promotion of active participation by users. Concerning transparency, it is important to develop rules relating to explain the company’s plans with regard to the collection, storage and use of data in a shortand understandable and above all uniform manner to all customers. More participation and transparency is a win-win-situation for companies and customers; it must be established with regard to Big Data because companies will continue to develop innovative solutions that ultimately benefit users.