| LDR | | | 00000cab a22000004u 4500 |
| 001 | | | MAP20260035192 |
| 003 | | | MAP |
| 005 | | | 20260609171216.0 |
| 008 | | | 260609s2026 esp|||| ||| ||eng d |
| 040 | | | $bspa$aMAP$dMAP |
| 084 | | | $a216.1 |
| 100 | 1 | | $0MAPA20260010991$aPandya, Parth |
| 245 | 1 | 0 | $aPredictive analytics in insurance: top benefits, use cases, real world examples$cParth Pandya |
| 520 | | | $aThe document analyses the role of predictive analytics in the insurance sector, highlighting how it transforms risk management, the customer experience and operational efficiency. It explains how predictive models work, their benefits, use cases and applications, including fraud detection, price optimisation, churn prediction and service personalisation. It also addresses the steps involved in implementing predictive analytics, challenges such as data quality, skills shortages and regulatory compliance, and proposes change management strategies. Finally, it presents real-world examples of insurers applying these technologies and future trends such as hyper-personalisation, ethical AI and the integration of embedded insurance
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| 522 | | | $aInternacional |
| 650 | | 4 | $0MAPA20080586294$aMercado de seguros |
| 650 | | 4 | $0MAPA20130017037$aAnálisis predictivos |
| 650 | | 4 | $0MAPA20250003316$aGestión de riesgos |
| 650 | | 4 | $0MAPA20150006509$aExperiencia del cliente |
| 650 | | 4 | $0MAPA20120026414$aEficiencia operacional |
| 650 | | 4 | $0MAPA20080607036$aLucha contra el fraude |
| 650 | | 4 | $0MAPA20250003187$aPersonalización |
| 650 | | 4 | $0MAPA20080611200$aInteligencia artificial |
| 650 | | 4 | $0MAPA20120019492$aTendencias |
| 710 | 2 | | $0MAPA20260011004$aMindInventory |
| 773 | 0 | | $tBlog de MindInventory .$g20 de mayo de 2026 |
| 856 | 4 | | $uhttps://www.mindinventory.com/blog/predictive-analytics-in-insurance |
