How A.I. can change the Health Insurance industry
With the new wave of deep learning innovations, artificial intelligence has the potential to be as efficient as human mind, which will majorly change the way we used to think of the insurance industry.
Insurance is an industry built around risk. Insurance companies greatly depend on their ability to predict what risk this or that person, company, or organization represents. The more information they have about them and the more accurate this information is, the more likely they are to make a correct prediction, either saving themselves money or earning extra revenue. The emergence of AI means that insurance companies should scramble for the ways of implementing them in their work to get the much-needed edge over the competition. But how exactly do these innovations change the industry? Let’s take a look at some of the most important examples.
Health insurance is anything but a linear process. If we look at the US, health insurance companies consider five factors to calculate premiums. According to the U.S. Centers for Medicare & Medicaid Services, these factors include age, location, tobacco use, enrollee category (individual vs. family) and plan category. With the help of A.I., these factors will become fundamental conditions in the big picture equation.
One of the most obvious examples of insurance industry technology that completely changes the way things are done are wearable sensors collecting information about customers. For example, if such a device is installed in a car, it gathers information on how the customer is driving: how fast he goes on average, how quick he is to accelerate, how she brakes, whether he is likely to go over the speed limit, and so on. All this information allows the company to build a comprehensive image of the client as a driver, indicating how likely he is to become a cause of an accident and thus how risky he is as a customer.
Another example is the enhancement of the customer experience. It becomes even easier to purchase insurance. With less active involvement on the part of the insurer and the customer. With enough information about individual behavior, the AI algorithms will create individual risk profiles, so that the time for completing the purchase of an auto, commercial, or life policy will be reduced to several minutes.
In the insurance industry the HyperAspect A.I. Cloud can be used to extract insights from claims and use that data in order to provide intelligent pricing, plan and cost optimizations and risk evaluations. Data becomes one of the most—if not the most—valuable asset in any organization. The insurance industry is no different: how carriers identify, quantify, place, and manage risks fully depends on the volume and quality of data they acquire during a policy’s life cycle. Thus, carriers must develop a well-structured and actionable strategy with regards to both internal and external data. Internal data will need to be organized in ways that enable and support the agile development of new analytics insights and capabilities. With external data, carriers must focus on securing access to data that enriches and complements their internal data sets. Overall, data strategy will need to include a variety of ways to obtain and secure access to external data, as well as ways to combine this data with internal sources. Carriers should be prepared to have a multifaceted procurement strategy that could include the direct acquisition of data assets and providers, licensing of data sources, use of data APIs, and partnerships with data brokers.
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