The client company is one of the leaders in the health insurance industry and wants to cement its place by offering accurate insurance costs to its customers based on their lifestyles. Their technology-driven solution aims to gain user trust and make optimum use of the gathered user data.
Our client is a Fortune 500 healthcare insurance company that required a model to calculate the insurance charges based on the lifestyle habits of its customers. We created a state-of-the-art model to optimize the price of health insurance by taking into account the information of the users. The model was made using accelerated machine learning for hypothesis testing and visualization to help the company make informed business decisions. It also overcomes the challenges this industry faces regarding the accuracy of the price and analyzing complex data sets. The model had a positive impact on the business by saving around 41% of evidence costs and reducing manual labor by 70%
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