Predictive analytics global survey results - Still room to grow for life & health insurers
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| Tag | 1 | 2 | Valor |
|---|---|---|---|
| LDR | 00000cam a22000004b 4500 | ||
| 001 | MAP20180019050 | ||
| 003 | MAP | ||
| 005 | 20220911211609.0 | ||
| 008 | 180625s2018 esp|||| ||| ||eng d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a34 | ||
| 100 | 1 | $0MAPA20180008863$aHu, Guizhou | |
| 245 | 1 | 0 | $aPredictive analytics global survey results - Still room to grow for life & health insurers $cGuizhou Hu |
| 260 | $aCologne$bGen Re$c2018 | ||
| 300 | $a3 p. | ||
| 520 | $aHow big is big data for life and health insurers? What are insurers worldwide focused on when it comes to predictive analytics? How are they adopting it and what are their expectations for the future? We set out to find answers to these questions through our global predictive analytics survey just released to participants this month | ||
| 650 | 4 | $0MAPA20080550592$aEncuestas | |
| 650 | 4 | $0MAPA20130017037$aAnálisis predictivos | |
| 650 | 4 | $0MAPA20080590567$aEmpresas de seguros | |
| 650 | 4 | $0MAPA20080570590$aSeguro de vida | |
| 650 | 4 | $0MAPA20080573867$aSeguro de salud | |
| 650 | 4 | $0MAPA20140022717$aBig data | |
| 650 | 4 | $0MAPA20080611880$aPerspectivas del seguro | |
| 650 | 4 | $0MAPA20080592059$aModelos predictivos | |
| 710 | 2 | $0MAPA20080660857$aGen Re |