Centro de Documentación de Fundación MAPFRE - A Survey of personalized treatment models for pricing strategies in insurance

Notes: Sumario: We 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.Related records: En: Insurance : mathematics and economics. - Oxford : Elsevier, 1990- = ISSN 0167-6687. - 01/09/2014 Volumen 58 Número 1 - septiembre 2014 , p. 68-76Materia / lugar / evento: Matemática del seguro Modelos actuariales Cálculo actuarial Modelos predictivos Seguros no vida Otros autores: Guillén, Montserrat
Pérez-Marín, Ana María
Other categories: 6

Rights: In Copyright (InC)

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