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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24113

Title: A model to improve management of banking customers
Authors: Estrella-Ramon, Antonia
Sanchez-Perez, Manuel
Swinnen, Gilbert
Vanhoof, Koen
Issue Date: 2017
Citation: INDUSTRIAL MANAGEMENT & DATA SYSTEMS, 117(2), p. 250-266
Abstract: Purpose - The purpose of this paper is to provide a customer lifetime value (CLV) model to carefully assess and classify banking customers using individual measures and covering customers' relationships with a portfolio of products of the company. Design/methodology/approach - The proposed model comprises two sub-models: (sub-model 1) modelling and prediction of CLV in a multiproduct context using Hierarchical Bayesian models as input to (sub-model 2) a value-based segmentation specially designed to manage customers and products using the latent class regression. The model is tested using real transaction data of 1,357 customers of a bank. Findings - This research demonstrates which drivers of customer value better predict the contribution margin and product usage for each of the products considered in order to get the CLV measure. Using this measure, the model implements a value-based segmentation, which helps banks to facilitate the process of customer management. Originality/value - Previous CLV models are mostly conceptual, generalisation is one of their main concerns, are usually focussed on single product categories using aggregated customer data, and they are not design with a special emphasis on their application as support for managerial decisions. In response to these drawbacks, the proposed model will enable decision makers to improve the understanding of the value of each customer and their behaviour towards different financial products.
Notes: [Estrella-Ramon, Antonia; Sanchez-Perez, Manuel] Univ Almeria, Dept Econ & Business, Almeria, Spain. [Swinnen, Gilbert] Univ Hasselt, Dept Business Econ, Hasselt, Belgium. [VanHoof, Koen] Univ Hasselt, Dept Business Informat, Hasselt, Belgium.
URI: http://hdl.handle.net/1942/24113
DOI: 10.1108/IMDS-03-2016-0107
ISI #: 000399073200001
ISSN: 0263-5577
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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