Underwriting excellence for the future : machine intelligence will see higher success rate in a post-COVID 19 era
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| Tag | 1 | 2 | Value |
|---|---|---|---|
| LDR | 00000cam a22000004b 4500 | ||
| 001 | MAP20210006555 | ||
| 003 | MAP | ||
| 005 | 20220911190149.0 | ||
| 008 | 181221e20210223deu|||| ||| ||eng d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a219 | ||
| 100 | 1 | $0MAPA20150008107$aSharan, Rajeev | |
| 245 | 1 | 0 | $aUnderwriting excellence for the future$b: machine intelligence will see higher success rate in a post-COVID 19 era$cRajeev Sharan |
| 260 | $aZurich$bSwiss Re Institute$c2021 | ||
| 300 | $a2 p. | ||
| 490 | 0 | $aEconomic insights$vIssue 4/2021 | |
| 520 | $aAccelerated digitalisation and associated large volumes of consumer data in the post COVID-19 era could facilitate greater success of MI projects. To date the adoption rate has been low, with over 95% failure due to lack of high-quality training data. The rise in online purchasing could manifest in MI opportunities for insurers to strengthen underwriting and predictive modelling. | ||
| 650 | 4 | $0MAPA20170005476$aMachine learning | |
| 650 | 4 | $0MAPA20080568641$aDigitalización | |
| 650 | 4 | $0MAPA20200005599$aCOVID-19 | |
| 650 | 4 | $0MAPA20080552022$aPandemias | |
| 650 | 4 | $0MAPA20080592059$aModelos predictivos | |
| 650 | 4 | $0MAPA20080586294$aMercado de seguros | |
| 710 | 2 | $0MAPA20170013402$aSwiss Re Institute | |
| 830 | 0 | $0MAPA20160007411$aEconomic insight |