The insurance industry understands that clients may feel like they are just a policy number in an ever-growing field. That’s where some insurance companies are turning to deep learning to create more personalized attention for the insured. Deep learning uses algorithms the same way neurons are used in the brain, creating artificial neural networks based on how users operate. This teaches computers to do what humans do, by anticipating human behavior. Here are a few examples of how this subset of machine learning is making its way into the insurance market.
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Property Analysis
A home insurance company will usually analyze a property before quoting a premium. However, customers can make changes to the property from adding on to the framework of the house to installing a poll. When this happens, providers can proactively modify the existing insurance coverage with the help of deep learning software. This form of artificial intelligence actually helps customers with predictive maintenance and real-time support, updating a homeowners insurance policy to assure peace of mind for a covered loss.
Deep learning techniques combine statistics, finance, and case-based reasoning to better assess potential risks and peril. This automated reasoning, as part of machine learning, has become increasingly prevalent in property & casualty insurance, as well as life insurance. This helps to make effective decisions based on large data sets, with an understanding of a person’s dwelling or their lifestyle to determine the cost of whichever type of coverage they may be purchasing.
Personalized Offers
When homeowners shop for an insurance policy that covers their house and personal belongings, they want to research the coverage out there that provides the best bang for their buck. With home insurance compare tools, home insurance companies rely on different customer touch-points for marketing outreach. Through personalized recommendations, insurers can all but assure customer satisfaction by having providers present recommendations for products based on the research already done by the prospective policyholder.
Deep learning technology takes into account recent events in figuring out offers for any additional coverage. For example, if you are shopping for an auto insurance policy, an insurance company will take into account recent life events. This could include adding a teenage driver onto a policy or expanding existing insurance coverage into a bundle with a home insurance policy. Machine learning also takes into account acts of God, like natural disasters, where homeowners find themselves looking into new lines of liability protection for the future.
Property insurance companies remapped flood zones following Hurricane Sandy in 2012, after certain regions in the Northeast U.S. found themselves inundated with water damage, changing the guidance on flood insurance. This understanding of geography by artificial intelligence directs homeowners to this needed insurance policy.
Handling Claims
Deep learning relies on data optimization for handling insurance claims in every line of coverage. Deep learning models help to create a connected information ecosystem, helping insurance companies get a better understanding of medical bills and additional living expenses when insured parties file in the event of a claim. Software developers develop portals that assure enough coverage and an easy way to file claims in homeowners insurance and other lines of protection.
With structured algorithms through a deep neural network, insurance companies avoid having to use handwritten claims that delay getting results under replacement cost coverage, leaving the insured waiting on a check to make necessary repairs or cover any medical payments in health insurance. Deep learning models leave customers in a good place, knowing that their claim can be monitored in real-time, tracking through a dataset that lets a covered party feel certain their money is coming in the event disaster strikes.
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