A Survey of personalized treatment models for pricing strategies in insurance
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| Tag | 1 | 2 | Value |
|---|---|---|---|
| LDR | 00000cab a2200000 4500 | ||
| 001 | MAP20140037124 | ||
| 003 | MAP | ||
| 005 | 20141105140033.0 | ||
| 008 | 141015e20140901esp|||p |0|||b|spa d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a6 | ||
| 100 | 1 | $0MAPA20140020843$aGuelman, Leo | |
| 245 | 1 | 2 | $aA Survey of personalized treatment models for pricing strategies in insurance$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 | |
| 700 | 1 | $0MAPA20080244637$aGuillén, Montserrat | |
| 700 | 1 | $0MAPA20080251772$aPérez-Marín, Ana María | |
| 773 | 0 | $wMAP20077100574$tInsurance : mathematics and economics$dOxford : Elsevier, 1990-$x0167-6687$g01/09/2014 Volumen 58 Número 1 - septiembre 2014 , p. 68-76 |