  Border inspection, and the challenge of deciding which of the tens of
millions of consignments that arrive should be inspected, is a perennial
problem for regulatory authorities. The objective of these inspections is to
minimise the risk of contraband entering the country. As an example, for
regulatory authorities in charge of biosecurity material, consignments of goods
are classified before arrival according to their economic tariff number
(Department of Immigration and Border Protection, 2016). This classification,
perhaps along with other information, is used as a screening step to determine
whether further biosecurity intervention, such as inspection, is necessary.
Other information associated with consignments includes details such as the
country of origin, supplier, and importer, for example.
  The choice of which consignments to inspect has typically been informed by
historical records of intercepted material. Fortunately for regulators,
interception is a rare event, however this sparsity undermines the utility of
historical records for deciding which containers to inspect.
  In this paper we report on an analysis that uses more detailed information to
inform inspection. Using quarantine biosecurity as a case study, we create
statistical profiles using generalised linear mixed models and compare
different model specifications with historical information alone, demonstrating
the utility of a statistical modelling approach. We also demonstrate some
graphical model summaries that provide managers with insight into pathway
governance.
