Phases of predictive analytics maturity : Understanding the phases on the way to efficiency
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| Tag | 1 | 2 | Valor |
|---|---|---|---|
| LDR | 00000cam a22000004b 4500 | ||
| 001 | MAP20210008160 | ||
| 003 | MAP | ||
| 005 | 20230321113930.0 | ||
| 008 | 200117e20211006gbr|||| ||| ||spa d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a219 | ||
| 245 | 1 | 0 | $aPhases of predictive analytics maturity$b: Understanding the phases on the way to efficiency |
| 260 | $aLondon$bGuidewire$c2021 | ||
| 300 | $a5 p. | ||
| 520 | $aInsurers have come a long way in their use of predictive analytics to deliver better business outcomes. Guidewire has found that insurers typically progress through several phases on their way to becoming efficient. In this white paper, we introduce a predictive analytics maturity model, discuss the typical issues insurers face in each phase, and recommend best practices for an efficient and agile approach. | ||
| 650 | 4 | $0MAPA20170006503$aTransformación digital | |
| 650 | 4 | $0MAPA20080586294$aMercado de seguros | |
| 650 | 4 | $0MAPA20080590567$aEmpresas de seguros | |
| 650 | 4 | $0MAPA20080605674$aDesarrollo tecnológico | |
| 650 | 4 | $0MAPA20080568641$aDigitalización | |
| 650 | 4 | $0MAPA20130017037$aAnálisis predictivos | |
| 710 | 2 | $0MAPA20200006480$aGuidewire |