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Forecasting Customer Behaviour in a Multi-Service Financial Organisation: A Profitability Perspective (Audzeyeva A., Summers B., Schenk-Hoppe K. R.)

Bank Products and Diversification Bank Profitability Household Strategies

Abstract This paper proposes a novel approach to the estimation of Customer Lifetime Value (CLV). CLV measures give an indication of the profit-generating potential of customers, and provide a key business tool for the customer management process. Existing approaches show unsatisfactory performance in multi-service financial environments because of the high degree of heterogeneity in customer behaviour. We propose an adaptive segmentation approach which involves the identification of “neighbourhoods” using a similarity measure defined over a predictive variable space. The set of predictive variables is determined during a cross-validation procedure through the optimisation of rank correlations between the observed and predicted revenues. Future revenue is forecast for each customer using a predictive probability distribution based on customers exhibiting similar behavioural characteristics in previous periods. The model is developed and implemented for a UK retail bank; it is shown to perform well in comparison to other benchmark models.
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Libref/ Audzeyeva A., Summers B., Schenk-Hoppe K. R. (2010) "Forecasting Customer Behaviour in a Multi-Service Financial Organisation: A Profitability Perspective", Swiss Finance Institute Research Paper No. 10-46, pp. 1 - 30
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