Model behaviour for insurance risk prediction : destroying the myth

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<rdf:Description>
<dc:date>2019-01-11</dc:date>
<dc:description xml:lang="es">Sumario: In a highly competitive market, it is important that insurers maximise their data models to create more intelligible insights. Only then, argues Alan O'Loughlin, head of analytics and statistical modelling at Lexis Nexis Risk Solutions, will they gain a strategic advantage over competitors</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/166710.do</dc:identifier>
<dc:language>eng</dc:language>
<dc:publisher>Insurance Post</dc:publisher>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Gerencia de riesgos</dc:subject>
<dc:subject xml:lang="es">Predicciones</dc:subject>
<dc:subject xml:lang="es">Modelos predictivos</dc:subject>
<dc:subject xml:lang="es">Empresas de seguros</dc:subject>
<dc:subject xml:lang="es">Comportamiento humano</dc:subject>
<dc:type xml:lang="es">Libros</dc:type>
<dc:title xml:lang="es">Model behaviour for insurance risk prediction : destroying the myth</dc:title>
<dc:relation xml:lang="es">En: Blog. Insurance Post</dc:relation>
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