Modelling and predicting enterprise level cyber risks in the context of sparse data availability

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<dc:creator>Zängerle, Daniel</dc:creator>
<dc:date>2023-04-03</dc:date>
<dc:description xml:lang="es">Sumario: Despite growing attention to cyber risks in research and practice, quantitative cyber risk assessments remain limited, mainly due to a lack of reliable data. This analysis leverages sparse historical data to quantify the financial impact of cyber incidents at the enterprise level. The results suggest that the probability of a cyber incident correlates with the subindustry, with the insurance sector being particularly exposed. The predicted financial losses from a cyber incident are less extreme than cited in recent investigations. The study confirms that cyber risks are heavy-tailed, jeopardising business operations and profitability </dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/183241.do</dc:identifier>
<dc:language>spa</dc:language>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Ciberseguridad</dc:subject>
<dc:subject xml:lang="es">Mercado de seguros</dc:subject>
<dc:subject xml:lang="es">Gerencia de riesgos</dc:subject>
<dc:subject xml:lang="es">Impacto económico</dc:subject>
<dc:subject xml:lang="es">Pérdidas</dc:subject>
<dc:subject xml:lang="es">Análisis de la rentabilidad</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">Modelling and predicting enterprise level cyber risks in the context of sparse data availability</dc:title>
<dc:relation xml:lang="es">En: Geneva papers on risk and insurance : issues and practice. - Geneva : The Geneva Association, 1976- = ISSN 1018-5895. - 03/04/2023 Volumen 48 Número 2 - abril 2023 , p. 434-462</dc:relation>
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