Bayesian Statistics and Marketing
Marketing Science
Identifying Innovators for the Cross-Selling of New Products
Management Science
How to Compute Optimal Catalog Mailing Decisions
Marketing Science
Cross-Selling in a Call Center with a Heterogeneous Customer Population
Operations Research
Intelligent profitable customers segmentation system based on business intelligence tools
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Time-varying effects in the analysis of customer loyalty: A case study in insurance
Expert Systems with Applications: An International Journal
Selecting prospects for cross-selling financial products using multivariate credibility
Expert Systems with Applications: An International Journal
Bootstrap control charts in monitoring value at risk in insurance
Expert Systems with Applications: An International Journal
A causal inference approach to measure price elasticity in Automobile Insurance
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
A new methodology, for optimal customer selection in cross-selling of financial services products, such as mortgage loans and non life insurance contracts, is presented. The optimal cross-sales selection of prospects is such that the expected profit is maximized, while at the same time the risk of suffering future losses is minimized. Expected profit maximization and mean-variance optimization are considered as alternative optimality criteria. In order to solve these optimality problems a stochastic model of the profit, expected to emerge from a single cross-sales prospect and from a selection of prospects, is developed. The related probability distributions of the profit are derived, both for small and large portfolio sizes and in the latter case, asymptotic normality is established. The proposed, profit optimization methodology is thoroughly tested, based on a real data set from a large Swedish insurance company and is shown to achieve considerable profit gains, compared to traditional cross-selling methods, which use only the estimated sales probabilities.