An Individual claims reserving model for reported claims

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<title>Individual claims reserving model for reported claims</title>
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<abstract displayLabel="Summary">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</abstract>
<note type="statement of responsibility">Andrea Gabrielli</note>
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<topic>Cálculo actuarial</topic>
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<topic>Matemática del seguro</topic>
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<title>European Actuarial Journal</title>
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<publisher>Cham, Switzerland  : Springer Nature Switzerland AG,  2021-2022</publisher>
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<identifier type="local">MAP20220007085</identifier>
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<text>06/12/2021 Número 2 - diciembre 2021 , p. 541-577</text>
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