A survey of personalized treatment models for pricing strategies in insurance

Leo Guelman, Montserrat Guillen and Ana M. Pérez-Marín

Insurance: Mathematics and Economics, 2014, vol. 58, issue C, 68-76

Abstract: 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.

Keywords: Rate making; Cross-selling in insurance; Predictive models; Causal inference; Nonlife insurance (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:58:y:2014:i:c:p:68-76

DOI: 10.1016/j.insmatheco.2014.06.009

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