An individual claims reserving model for reported claims

Abstract We present a claims reserving technique that uses claim-specific feature and past payment information in order to estimate reserves for individual reported claims. design one single neural network allowing us expected future cash flows every claim. introduce consistent way of using dropout layers fit the incomplete time series payments. A proof concept is provided by applying this model synthetic as well real insurance data sets which true outstanding payments are known.