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A Survey of personalized treatment models for pricing strategies in insurance

Recurso electrónico / electronic resource
Registro MARC
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1001 ‎$0‎MAPA20140020843‎$a‎Guelman, Leo
24512‎$a‎A Survey of personalized treatment models for pricing strategies in insurance‎$c‎Leo Guelman, Montserrat Guillén, Ana M. Pérez-Marín
520  ‎$a‎We consider a model for price calculations based on three components: a fair premium; price loadings reflecting general expenses and solvency requirements; and profit. The first two components are typically evaluated on a yearly basis, while the third is viewed from a longer perspective. When considering the value of customers over a period of several years, and examining policy renewals and cross-selling in relation to price adjustments, many insurers may prefer to reduce their short-term benefits so as to focus on their most profitable customers and the long-term value. We show how models of personalized treatment learning can be used to select the policy holders that should be targeted in a company¿s marketing strategies. An empirical application of the causal conditional inference tree method illustrates how best to implement a personalized cross-sell marketing campaign in this framework.
650 4‎$0‎MAPA20080602437‎$a‎Matemática del seguro
650 4‎$0‎MAPA20080592011‎$a‎Modelos actuariales
650 4‎$0‎MAPA20080579258‎$a‎Cálculo actuarial
650 4‎$0‎MAPA20080592059‎$a‎Modelos predictivos
650 4‎$0‎MAPA20080573935‎$a‎Seguros no vida
7001 ‎$0‎MAPA20080244637‎$a‎Guillén, Montserrat
7001 ‎$0‎MAPA20080251772‎$a‎Pérez-Marín, Ana María
7730 ‎$w‎MAP20077100574‎$t‎Insurance : mathematics and economics‎$d‎Oxford : Elsevier, 1990-‎$x‎0167-6687‎$g‎01/09/2014 Volumen 58 Número 1 - septiembre 2014 , p. 68-76