A comprehensive model for cyber risk based on marked point processes and its application to insurance

<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
  <record>
    <leader>00000cab a2200000   4500</leader>
    <controlfield tag="001">MAP20220019798</controlfield>
    <controlfield tag="003">MAP</controlfield>
    <controlfield tag="005">20220701123627.0</controlfield>
    <controlfield tag="008">220701e20220606che|||p      |0|||b|eng d</controlfield>
    <datafield tag="040" ind1=" " ind2=" ">
      <subfield code="a">MAP</subfield>
      <subfield code="b">spa</subfield>
      <subfield code="d">MAP</subfield>
    </datafield>
    <datafield tag="084" ind1=" " ind2=" ">
      <subfield code="a">6</subfield>
    </datafield>
    <datafield tag="100" ind1="1" ind2=" ">
      <subfield code="0">MAPA20220006620</subfield>
      <subfield code="a">Zeller, Gabriela</subfield>
    </datafield>
    <datafield tag="245" ind1="1" ind2="0">
      <subfield code="a">A comprehensive model for cyber risk based on marked point processes and its application to insurance</subfield>
      <subfield code="c">Gabriela Zeller, Matthias Scherer </subfield>
    </datafield>
    <datafield tag="520" ind1=" " ind2=" ">
      <subfield code="a">After scrutinizing technical, legal, financial, and actuarial aspects of cyber risk, a new approach for modelling cyber risk using marked point processes is proposed. Key covariates, required to model frequency and severity of cyber claims, are identified. The presented framework explicitly takes into account incidents from malicious untargeted and targeted attacks as well as accidents and failures. The resulting model is able to include the dynamic nature of cyber risk, while capturing accumulation risk in a realistic way. The model is studied with respect to its statistical properties and applied to the pricing of cyber insurance and risk measurement. The results are illustrated in a simulation study.

</subfield>
    </datafield>
    <datafield tag="540" ind1=" " ind2=" ">
      <subfield code="a">La copia digital se distribuye bajo licencia "Attribution 4.0 International (CC BY 4.0)"</subfield>
      <subfield code="u">https://creativecommons.org/licenses/by/4.0</subfield>
      <subfield code="9">43</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20160007633</subfield>
      <subfield code="a">Ciberriesgos</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080579258</subfield>
      <subfield code="a">Cálculo actuarial</subfield>
    </datafield>
    <datafield tag="700" ind1="1" ind2=" ">
      <subfield code="0">MAPA20220002158</subfield>
      <subfield code="a">Scherer, Matthias</subfield>
    </datafield>
    <datafield tag="773" ind1="0" ind2=" ">
      <subfield code="w">MAP20220007085</subfield>
      <subfield code="g">06/06/2022 Volúmen 12 - Número 1 - junio 2022 , p. 33-85</subfield>
      <subfield code="t">European Actuarial Journal</subfield>
      <subfield code="d">Cham, Switzerland  : Springer Nature Switzerland AG,  2021-2022</subfield>
    </datafield>
    <datafield tag="856" ind1=" " ind2=" ">
      <subfield code="q">application/pdf</subfield>
      <subfield code="w">1116051</subfield>
      <subfield code="y">Recurso electrónico / Electronic resource</subfield>
    </datafield>
  </record>
</collection>