Underwriting excellence for the future : machine intelligence will see higher success rate in a post-COVID 19 era

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<rdf:Description>
<dc:creator>Sharan, Rajeev</dc:creator>
<dc:creator>Swiss Re Institute</dc:creator>
<dc:date>2021-02-23</dc:date>
<dc:description xml:lang="es">Sumario: Accelerated digitalisation and associated large volumes of consumer data in the post COVID-19 era could facilitate greater success of MI projects. To date the adoption rate has been low, with over 95% failure due to lack of high-quality training data. The rise in online purchasing could manifest in MI opportunities for insurers to strengthen underwriting and predictive modelling.</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/174792.do</dc:identifier>
<dc:language>eng</dc:language>
<dc:publisher>Swiss Re Institute</dc:publisher>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Machine learning</dc:subject>
<dc:subject xml:lang="es">Digitalización</dc:subject>
<dc:subject xml:lang="es">COVID-19</dc:subject>
<dc:subject xml:lang="es">Pandemias</dc:subject>
<dc:subject xml:lang="es">Modelos predictivos</dc:subject>
<dc:subject xml:lang="es">Mercado de seguros</dc:subject>
<dc:type xml:lang="es">Libros</dc:type>
<dc:title xml:lang="es">Underwriting excellence for the future : machine intelligence will see higher success rate in a post-COVID 19 era</dc:title>
<dc:format xml:lang="es">2 p.</dc:format>
<dc:relation xml:lang="es">Economic insight</dc:relation>
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