This paper proposes a hurdle model of repayment behaviour in loans with fixed instalments. Using information on previous and current contracts, the approach yields a model of customer behaviour, useful, for example, in assessing the impact of determinants of default, a natural concern for credit and behavioural scoring. Under plausible assumptions, a debtor in each period faces a number of missed payments, which depends on his previous repayment decisions; meanwhile, as most debtors are expected to meet financial obligations, the number of missed payments is bound to display excess zeros, with reference to a single-part law. Each sequence of missed payments is modelled by using the binomial thinning, a conceptual tool that allows for dependence between integers by defining the support of consecutive counts. Under suitable assumptions on heterogeneity, the model can be produced under a random effects approach, leading to a two-part panel data model, estimable by quasi-maximum likelihood. The proposed approach is illustrated using a panel data set on personal loans granted by a Portuguese bank.