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

中文翻译：

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报告索赔的个人索赔保留模型

我们提出一种索赔保留技术，该技术使用索赔特定的功能和过去的付款信息来估算单个报告索赔的索赔准备金。我们设计了一个单一的神经网络，使我们能够估算每个报告的索赔的预期未来现金流量。我们介绍了一种使用辍学层的一致方法，以使神经网络适应过去的个人理赔额的不完整时间序列。通过将此模型应用于合成的以及真实的保险数据集，可以提供概念证明，对于这些数据集，已报告索赔的真实未偿还款项是已知的。