Warning lights

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<dc:creator>Chalk, Alan</dc:creator>
<dc:creator>Micklethwait, Tessa</dc:creator>
<dc:date>2026-02-02</dc:date>
<dc:description xml:lang="es">Sumario: The document explains that UK motor insurance is heavily affected by fraudulent claims and outlines actuarial and data-science methods to combat them. It distinguishes opportunistic and organized fraud and highlights tools such as automation, metadata extraction, machine-learning models, and especially graph-based techniques for detecting links between fraudulent entities. It also notes challenges related to data quality and entity resolution, emphasizing the usefulness of these approaches for early fraud detection in motor insurance</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/189649.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 automóviles</dc:subject>
<dc:subject xml:lang="es">Fraude en el seguro</dc:subject>
<dc:subject xml:lang="es">Análisis de datos</dc:subject>
<dc:subject xml:lang="es">Machine learning</dc:subject>
<dc:subject xml:lang="es">Teoría de grafos</dc:subject>
<dc:subject xml:lang="es">Inteligencia artificial</dc:subject>
<dc:subject xml:lang="es">Mercado de seguros</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">Warning lights</dc:title>
<dc:relation xml:lang="es">En: The Actuary : the magazine of the Institute & Faculty of Actuaries. - London :  Redactive Publishing, 2019-. - 02/02/2026 Number 7 - February 2026 , p. 54 - 57</dc:relation>
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