Búsqueda

Underwritting 2.0 : in an increasingly automated world, what does risk assessment look like?

<?xml version="1.0" encoding="UTF-8"?><modsCollection xmlns="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-8.xsd">
<mods version="3.8">
<titleInfo>
<title>Underwritting 2.0</title>
<subTitle>: in an increasingly automated world, what does risk assessment look like?</subTitle>
</titleInfo>
<typeOfResource>text</typeOfResource>
<genre authority="marcgt">periodical</genre>
<originInfo>
<place>
<placeTerm type="code" authority="marccountry">usa</placeTerm>
</place>
<dateIssued encoding="marc">2020</dateIssued>
<issuance>serial</issuance>
</originInfo>
<language>
<languageTerm type="code" authority="iso639-2b">eng</languageTerm>
</language>
<physicalDescription>
<form authority="marcform">print</form>
</physicalDescription>
<abstract displayLabel="Summary">Underwriting practices today are a world away from those commonplace 20 years ago, but the biggest evolution is yet to come. Big Data will truly transform underwriting over the next decade. Harnessing new data sources using the latest artificial intelligence (AI), machine learning (ML), and deep learning (DL) techniques will radically change every aspect of the risk assessment process. But AI also brings important threats: Deploying these new technologies without consideration of the commercial, risk, ethical, regulatory, and societal factors could have disastrous consequences. In this article, we look in-depth at how Big Data and its tools are changing underwriting.</abstract>
<note type="statement of responsibility">Scott Rushing</note>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080608835">
<topic>Suscripción de riesgos</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080568009">
<topic>Automatización</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20140022717">
<topic>Big data</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080586546">
<topic>Nuevas tecnologías</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080601522">
<topic>Evaluación de riesgos</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080611200">
<topic>Inteligencia artificial</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080576158">
<topic>Gestión de datos</topic>
</subject>
<classification authority="">7</classification>
<relatedItem type="host">
<titleInfo>
<title>Contingencies : American Academy of Actuaries</title>
</titleInfo>
<originInfo>
<publisher>Washington : American Academy of Actuaries, 2019-</publisher>
</originInfo>
<identifier type="local">MAP20190020794</identifier>
<part>
<text>02/03/2020 March-April 2020 , p. 26-31</text>
</part>
</relatedItem>
<recordInfo>
<recordContentSource authority="marcorg">MAP</recordContentSource>
<recordCreationDate encoding="marc">200325</recordCreationDate>
<recordChangeDate encoding="iso8601">20220911211223.0</recordChangeDate>
<recordIdentifier source="MAP">MAP20200009764</recordIdentifier>
<languageOfCataloging>
<languageTerm type="code" authority="iso639-2b">spa</languageTerm>
</languageOfCataloging>
</recordInfo>
</mods>
</modsCollection>