Conformal prediction of future insurance claims in the regression problem

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<title>Conformal prediction of future insurance claims in the regression problem</title>
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<abstract displayLabel="Summary">The article presents a prediction method based on conformal prediction to estimate future insurance claims in regression settings. The proposed approach is fully model-free and tuning-parameter-free, ensuring finite-sample validity. It analyzes the limitations of traditional parametric and non-parametric approaches, such as model misspecification and the selection effect. Through simulation studies and a real case involving personal injury insurance claims, the effectiveness of the method is demonstrated, particularly in meeting Solvency II capital requirements. The approach is especially relevant for risk management and regulatory capital estimation in insurance companies</abstract>
<note type="statement of responsibility">Liang Hong</note>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080563790">
<topic>Predicciones</topic>
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<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080592011">
<topic>Modelos actuariales</topic>
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<topic>Solvencia II</topic>
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<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080573935">
<topic>Seguros no vida</topic>
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<topic>Riesgo financiero</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>13/04/2026 Número 16 issue 1 - abril 2026 , 17 p.</text>
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