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| Tag | 1 | 2 | Valor |
|---|---|---|---|
| LDR | 00000cab a2200000 4500 | ||
| 001 | MAP20260004174 | ||
| 003 | MAP | ||
| 005 | 20260213093613.0 | ||
| 008 | 260212e20260202gbr|||p |0|||b|eng d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a322 | ||
| 100 | $0MAPA20260003030$aChalk, Alan | ||
| 245 | 1 | 0 | $aWarning lights$cAlan Chalk and Tessa Micklethwait |
| 520 | $aThe document explains that UK motor insurance is heavily affected by fraudulent claims and outlines actuarial and data-science methods to combat them. It distinguishes opportunistic and organized fraud and highlights tools such as automation, metadata extraction, machine-learning models, and especially graph-based techniques for detecting links between fraudulent entities. It also notes challenges related to data quality and entity resolution, emphasizing the usefulness of these approaches for early fraud detection in motor insurance | ||
| 650 | 4 | $0MAPA20080603779$aSeguro de automóviles | |
| 650 | 4 | $0MAPA20080591052$aFraude en el seguro | |
| 650 | 4 | $0MAPA20080578848$aAnálisis de datos | |
| 650 | 4 | $0MAPA20170005476$aMachine learning | |
| 650 | 4 | $0MAPA20080578435$aTeoría de grafos | |
| 650 | 4 | $0MAPA20080611200$aInteligencia artificial | |
| 650 | 4 | $0MAPA20080586294$aMercado de seguros | |
| 700 | 1 | $0MAPA20260003047$aMicklethwait, Tessa | |
| 773 | 0 | $wMAP20200013259$g02/02/2026 Number 7 - February 2026 , p. 54 - 57$tThe Actuary : the magazine of the Institute & Faculty of Actuaries$dLondon : Redactive Publishing, 2019- |