How artificial intelligence changes the insurance world

For most people, the topic of insurance is not a pleasurable experience. Once rummaged through the tariff Jungle, you feel in the rare case of damage often let down. Basically, the communication with insurers roughly does not really differ with those of authorities. The customer feels unconscious and not fully informed. By definition, insurance is an assumption of risk by the insurer against payment of a premium, in order to receive compensation for damages in the event of damage from the collective. Specifically, this actually means for both parties, ie policyholders and insurers, to get into a situation that one tries for many reasons to avoid. Actually a paradoxical system.

The digitization of the private banking sector, FinTech for short, has shown that the use of technology makes previously tedious processes in banks customer-friendly – today “user-friendly”. But not only the UX (“user experience”) has improved: Small banks that rely entirely on digital tools, overtake the major players in the coveted retail and lending business. The use of DeepTech creates transparency, fair credit checks and convenience. The cost savings in the operational business of banks is self-explanatory. In the meantime banks are already concerned about who brings the younger direct bank to the market with the ‘hipperen’ brand?

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The paradigm shift is already taking place today

Bit by bit, digitization is now also finding its way into the often opaque insurance industry. Artificial intelligence (AI) and algorithms determine risk assessments “live”, taking into account hundreds of variables and data points. The beginnings of car insurance came in: telematics tariffs.

The monthly insurance policy is based on effective vehicle usage and not just conventional static determinants. In the area of ​​property insurance, however, it gets a bit more complicated. The collective of policyholders consists of people of different “risk classes”, lifestyles and mobility. Whether rowdy or ascetic, everyone pays the same. Is that fair? The entry of DeepTech should help. The foundation stone here is a unique joint venture between Munich Re and GoogleMaps creator Axon Vibe. The principle of telematics tariffs is entering the world of property insurance.

A policyholder’s smartphone is used to anonymously compare and analyze his movement and location data with Munich Re’s metadata about risks. AxonVibe acts as a ‘data investigator’ and sends predefined trigger information to the insurance provider after approval by the policyholder. This in turn switches its AI and its algorithms in between and “learns” from insurance cases. Insurance policies can be calculated and offered context-sensitive in real time.

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Insurance 3.0

Modular short-term insurance policies are in the final phase shortly before market entry for various providers. In the insurance jargon called UBI (Usage-Based Insurance), soon comes the first UBI product for travel, where customers daily their luggage, smartphones or laptops against theft, loss or damage on the basis of the respective destination get insured. Automatic notifications from the app or smartwatch are obvious here. Back at the home airport, the insurance cover is automatically terminated.

Another example is an accident insurance based on UBI: Upon entering a ski resort, the insurance cover automatically activates and deactivates after leaving this zone and, if desired, without any action by the policyholder.

The aforementioned UBI insurances make the use of artificial intelligence comparatively easy with their “pay as you use” principle. For example, one of the principles of the Max Planck Institute is that in order to accept decisions of self-learning machines as “fair”, their decisions must have a clear causal connection to our legal and moral requirements. In the field of property insurance, customers have the same starting conditions. And even more.

Artificial intelligence will make cancellations just because, for example, customers “living under the wrong postal code” will be a thing of the past. The system learns that persons X with lifestyle V can also carry the same risk class in the postal code Z area. However, the resulting advantages are not only in the adequate design of the policy contributions. Insurance companies can identify risks in the near future before they arise. They can step out of their role of clean-up and give their customers preventive protection.

About the guest author

Alexander Huber is co-founder and Chief Marketing Officer of ONE Insurance, Europe’s first fully digital insurer. He loves sales funnel, digital business models, but above all, he is known for his black humor and sarcastic comments towards the established competition.

One Cmo U Co Founder Alexander Huber

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