Search

The Doctor in the data

<?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>Zabój, Maciej </dc:creator>
<dc:date>2020-04-01</dc:date>
<dc:description xml:lang="es">Sumario: The traditional pricing model works to capture policyholder data during the quotation process. This means that the risk is assessed at that point in time, with a predefined discriminating factor (such as smokers vs non-smokers). This data may be updated following results from health assessments (such as blood tests) to assess whether, say, a non-smoking habit has changed. Preventive life insurance takes a diff erent approach. The information gathered via the traditional approach  self-reported risks and habits  could be extended using data obtained from a personalised monitoring device. Currently, these devices track basic health factors, such as sport activity, pulse, blood pressure, body temperature and oxygen saturation.</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/171572.do</dc:identifier>
<dc:language>eng</dc:language>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Seguro de vida</dc:subject>
<dc:subject xml:lang="es">Análisis de datos</dc:subject>
<dc:subject xml:lang="es">Wearables</dc:subject>
<dc:subject xml:lang="es">Dispositivos móviles</dc:subject>
<dc:subject xml:lang="es">Digitalización</dc:subject>
<dc:subject xml:lang="es">Salud Digital</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">The Doctor in the data</dc:title>
<dc:relation xml:lang="es">En: The Actuary : the magazine of the Institute & Faculty of Actuaries. - London :  Redactive Publishing, 2019-. - 01/04/2020 Número 3 - abril 2020 , p. 40</dc:relation>
</rdf:Description>
</rdf:RDF>