European life insurers are finding analytics treasures : 2020 life insurance predictive analytics survey

<?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>00000cam a22000004b 4500</leader>
    <controlfield tag="001">MAP20200038368</controlfield>
    <controlfield tag="003">MAP</controlfield>
    <controlfield tag="005">20220911190405.0</controlfield>
    <controlfield tag="008">200310s2020    gbr||||       ||| ||eng d</controlfield>
    <datafield tag="040" ind1=" " ind2=" ">
      <subfield code="a">MAP</subfield>
      <subfield code="b">eng</subfield>
      <subfield code="d">MAP</subfield>
    </datafield>
    <datafield tag="084" ind1=" " ind2=" ">
      <subfield code="a">341</subfield>
    </datafield>
    <datafield tag="245" ind1="1" ind2="2">
      <subfield code="a">European life insurers are finding analytics treasures</subfield>
      <subfield code="b">: 2020 life insurance predictive analytics survey</subfield>
    </datafield>
    <datafield tag="260" ind1=" " ind2=" ">
      <subfield code="a">London</subfield>
      <subfield code="b">Willis Towers Watson</subfield>
      <subfield code="c">2020</subfield>
    </datafield>
    <datafield tag="300" ind1=" " ind2=" ">
      <subfield code="a">12 p.</subfield>
    </datafield>
    <datafield tag="520" ind1=" " ind2=" ">
      <subfield code="a">Recent years have seen more life insurers adopting the predictive analytics and automation that have already become a competitive necessity for property and casualty (P&C) insurers around the world. Predictive analytics involves the use of data (often entiched from external sources) to identify and analyse patterns and trends to better predict what may happen, and to inform business decisions. The analytics can be simple, but insurers increasingly have a toolbox of more advanced techniques, such as machine learning, at their fingertips.</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20130017037</subfield>
      <subfield code="a">Análisis predictivos</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080590567</subfield>
      <subfield code="a">Empresas de seguros</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080570590</subfield>
      <subfield code="a">Seguro de vida</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080586294</subfield>
      <subfield code="a">Mercado de seguros</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080568009</subfield>
      <subfield code="a">Automatización</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080550592</subfield>
      <subfield code="a">Encuestas</subfield>
    </datafield>
    <datafield tag="651" ind1=" " ind2="1">
      <subfield code="0">MAPA20080637743</subfield>
      <subfield code="a">Europa</subfield>
    </datafield>
    <datafield tag="710" ind1="2" ind2=" ">
      <subfield code="0">MAPA20170016144</subfield>
      <subfield code="a">Willis Towers Watson</subfield>
    </datafield>
  </record>
</collection>