Underwritting 2.0 : in an increasingly automated world, what does risk assessment look like?
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| 001 | MAP20200009764 | ||
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| 040 | $aMAP$bspa$dMAP | ||
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| 100 | $0MAPA20200006473$aRushing, Scott | ||
| 245 | 1 | 0 | $aUnderwritting 2.0$b: in an increasingly automated world, what does risk assessment look like?$cScott Rushing |
| 520 | $aUnderwriting 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. | ||
| 650 | 4 | $0MAPA20080608835$aSuscripción de riesgos | |
| 650 | 4 | $0MAPA20080568009$aAutomatización | |
| 650 | 4 | $0MAPA20140022717$aBig data | |
| 650 | 4 | $0MAPA20080586546$aNuevas tecnologías | |
| 650 | 4 | $0MAPA20080601522$aEvaluación de riesgos | |
| 650 | 4 | $0MAPA20080611200$aInteligencia artificial | |
| 650 | 4 | $0MAPA20080576158$aGestión de datos | |
| 773 | 0 | $wMAP20190020794$tContingencies : American Academy of Actuaries$dWashington : American Academy of Actuaries, 2019-2024$g02/03/2020 March-April 2020 , p. 26-31 |