In the last few years, Insurtechs have entered the market with smart innovative models. Benchmarking the business design of these start-ups gave us the opportunity to understand how they leverage the power of artificial intelligence within narrow domains (insurance for small business, microinsurance for milleniums...) or for specific processes (claim management, on demand product insurance, policies management ...).
All these AI and data-centric models are within the reach of incumbents if they can drive innovation programs with AI savvy agile teams.
The use of health data in machine learning algorithms is a sensible matter as it relates to highly personal information. Regulations are strong and transparency is required. There is no doubt however that health insurers can find a way to leverage the value of data to enhance the service they offer to their clients while lowering the costs of services.
They can for instance leverage the data that their customers are willing to share to demonstrate that they adopt healthy behaviors. They can also use behavioral data to engage proactively with customers and provide personalized advice.
AI for Travel Insurance
Travel insurance is a real pain for every traveler. Everyone starting a new trip will have to go through a painful process to answer basic questions: Am I covered if my flight is delayed overnight ? What is the rental car insurance coverage associated to my Visa card ? Does my health insurance cover ski accidents abroad ? ...
The consequence is that most of the time, travelers end up buying multiple insurance packages, with a lot of redundant policies but without even being sure that they are totally covered.
Now imagine that you can ask your personal insurance assistant to check your level of protection for your next family ski trip to Whistler. Imagine that he can send you in real-time the best quotation to protect your ski equipment for any damage or delay during your flight to Vancouver. Imagine that your insurance company send you a 20% discount if you accept to connect your ski anti-theft device to its mobile app ? Does it seem unreal ? Not really. First movers that will acquire the capacity to bring that level of service to their client will definitely build strong competitive advantages.
AI for Vehicle and Insurance
Is the old vehicle based model still of value in a new era of mobility where multimodal transportation, car sharing and short term rental are rapidly expanding ? How should insurers react to the fact that owning a car is less and less a priority for new generations ? Shall they start designing new models based on mobility patterns rather than vehicle ownership ?
These are not easy questions to address. However there are now more and more ways to acquire mobility data that will help insurers acquire a better understanding of their customers mobility patterns. Consolidating these data and analysing the flow of events generated by mobility data will help them discover new types of customers profiles and needs. Through both supervised and unsupervised learning thet will acquire the capacity to develop new models (profit analysis, risk analysis) and to design taylored offerings for highly targeted segments.
AI for Home Insurance
There's many areas in which home insurers can benefit from machine learning to enhance their processes. But there is very little doubt that the combination of the Internet of Things and artificial intelligence offers one of the highest potential of innovation and disruption.
The IoT provides new streams of real-time data that can be leverage to anticipate and mitigate risks and to provide meaningful insights and alerts to clients. In-home sensors can not only monitor fire, wind and water damages but they are also a mean to engage with customers in a truly individualized manner.
Obviously IoT data can be combined to design smarter offerings. For instance, the challenge to ageing that many countries are facing could be addressed with smart combinations of home sensors and health devices.