Búsqueda

Cybersecurity insurance : modeling and pricing

<?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">MAP20190021128</controlfield>
    <controlfield tag="003">MAP</controlfield>
    <controlfield tag="005">20190715150855.0</controlfield>
    <controlfield tag="008">190708e20190603usa|||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=" " ind2=" ">
      <subfield code="0">MAPA20120013339</subfield>
      <subfield code="a">Xu, Maochao</subfield>
    </datafield>
    <datafield tag="245" ind1="0" ind2="0">
      <subfield code="a">Cybersecurity insurance</subfield>
      <subfield code="b">: modeling and pricing</subfield>
      <subfield code="c">Maochao Xu, Lei Hua</subfield>
    </datafield>
    <datafield tag="300" ind1=" " ind2=" ">
      <subfield code="a">31 p. </subfield>
    </datafield>
    <datafield tag="520" ind1=" " ind2=" ">
      <subfield code="a">Cybersecurity risk has attracted considerable attention in recent decades. However, the modeling of cybersecurity risk is still in its infancy, mainly because of its unique characteristics. In this study, we develop a framework for modeling and pricing cybersecurity risk. The proposed model consists of three components: the epidemic model, loss function, and premium strategy. We study the dynamic upper bounds for the infection probabilities based on both Markov and non-Markov models. A simulation approach is proposed to compute the premium for cybersecurity risk for practical use. The effects of different infection distributions and dependence among infection processes on the losses are also studied.</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20140022700</subfield>
      <subfield code="a">Ciberseguridad</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">MAPA20080604394</subfield>
      <subfield code="a">Valoración de riesgos</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20120003040</subfield>
      <subfield code="a">Teoría precios</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20100017982</subfield>
      <subfield code="a">Riesgos emergentes</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080564322</subfield>
      <subfield code="a">Tarificación</subfield>
    </datafield>
    <datafield tag="700" ind1=" " ind2=" ">
      <subfield code="0">MAPA20080649616</subfield>
      <subfield code="a">Hua, Lei</subfield>
    </datafield>
    <datafield tag="773" ind1="0" ind2=" ">
      <subfield code="w">MAP20077000239</subfield>
      <subfield code="t">North American actuarial journal</subfield>
      <subfield code="d">Schaumburg : Society of Actuaries, 1997-</subfield>
      <subfield code="x">1092-0277</subfield>
      <subfield code="g">03/06/2019 Tomo 23 Número 2 - 2019 , p. 220-249</subfield>
    </datafield>
  </record>
</collection>