A statistical model for the temporal pattern of individual automated teller machine withdrawals

Abstract

Models of consumer behaviour that are based purely on empirical relationships in data can perform well in the short term but often degrade rapidly with changing circumstances. Superior longer-term performance can sometimes be attained by developing models for the deeper processes underlying the consumer behaviour. We develop a random-effects point process model for automated teller machine withdrawals. Estimation, prediction and computational issues are discussed. The model may be used to predict behaviour for an individual and to assess when state changes in individual behaviour have occurred and as a description of behaviour for a portfolio of accounts. © 2008 Royal Statistical Society.