Search

Modeling lapse rates using machine learning : a comparison between Survival Forests and Cox Proportional Hazards techniques

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<rdf:Description>
<dc:creator>Andrade, Jorge Luis</dc:creator>
<dc:creator>Valencia, José Luis</dc:creator>
<dc:creator>Instituto de Actuarios Españoles</dc:creator>
<dc:date>2021-12-29</dc:date>
<dc:description xml:lang="es">Sumario: This study undertakes a comparative analysis of the performance of machine learning and traditional survival analysis techniques in the insurance industry. The techniques compared are the traditional Cox Proportional Hazards (CPH), Random Survival Forests (RSF) and Conditional Inference Forests (CIF) machine learning models. These techniques are applied in a case study of insurance portfolio of one of Ecuador's largest insurer. This study demonstrates how machine learning techniques perform better in predicting survival function measured by the C-index and Brier Score. It also demonstrates that the predictive contribution of covariates in the RSF model is consistent with the traditional CPH model</dc:description>
<dc:format xml:lang="en">application/pdf</dc:format>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/178217.do</dc:identifier>
<dc:language>spa</dc:language>
<dc:rights xml:lang="es">https://creativecommons.org/licenses/by/4.0</dc:rights>
<dc:subject xml:lang="es">Análisis actuarial</dc:subject>
<dc:subject xml:lang="es">Machine learning</dc:subject>
<dc:subject xml:lang="es">Modelos de supervivencia</dc:subject>
<dc:subject xml:lang="es">Análisis comparativo</dc:subject>
<dc:subject xml:lang="es">Cartera de seguros</dc:subject>
<dc:subject xml:lang="es">Análisis predictivos</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">Modeling lapse rates using machine learning : a comparison between Survival Forests and Cox Proportional Hazards techniques</dc:title>
<dc:relation xml:lang="es">En: Anales del Instituto de Actuarios Españoles : Colegio Profesional. - Madrid : Instituto de Actuarios Españoles, 1943-. - 29/12/2021 Número 27 -  Epoca 4ª, Año 2021 , p. 161-183</dc:relation>
</rdf:Description>
</rdf:RDF>