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Optimizing International Private Medical Insurance using Deep Neural Networks
In this collaboration with BUPA I introduced a holistic perspective on pricing for IPMI using a Bayesian framework and predictive models based on deep neural networks. The model includes price sensitivity to customer acquisition, retention and loss ratio prediction, at several granularity levels. The model uses structured and unstructured data and accommodates uncertainty in a natural way, giving the decision maker a clear tradeoff between profitability and market share that allows optimal decisions regarding pricing of products.