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Statistical Modelling
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Measuring customer quality in retail banking

David J Hand

Department of Mathematics, Imperial College London, London, d.j.hand{at}imperial.ac.uk

Martin J Crowder

Department of Mathematics, Imperial College London, London, m.crowder{at}imperial.ac.uk

The retail banking sector makes heavy use of statistical models to predict various aspects of customer behaviour. These models are built using data from earlier customers, but have several weaknesses. An alternative approach, widely used in social measurement, but apparently not yet applied in the retail banking sector, is to use latent-variable techniques to measure the underlying key aspect of customer behaviour. This paper describes such a model that separates the observed variables for a customer into primary characteristics on the one hand, and indicators of previous behaviour on the other, and links the two via a latent variable that we identify as ‘customer quality’. We describe how to estimate the conditional distribution of customer quality, given the observed values of primary characteristics and past behaviour.

Key Words: credit cards • financial delinquency • latent variables • loan default • prediction • random effects • retail banking • scorecards

Statistical Modelling, Vol. 5, No. 2, 145-158 (2005)
DOI: 10.1191/1471082X05st092oa
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