  Fraud in public funding can have deleterious consequences for the economic,
social, and political well-being of societies. Fraudulent activity associated
with public procurement contracts accounts for losses of billions of euros
every year. Thus, it is of utmost relevance to explore analytical frameworks
that can help public authorities identify agents that are more susceptible to
incur in irregular activities. Here, we use standard network science methods to
study the co-biding relationships between firms that participate in public
tenders issued by the $184$ municipalities of the State of Cear\'a (Brazil)
between 2015 and 2019. We identify $22$ groups/communities of firms with
similar patterns of procurement activity, defined by their geographic and
activity scopes. The profiling of the communities allows us to highlight groups
that are more susceptible to market manipulation and irregular activities. Our
work reinforces the potential application of network analysis in policy to
unfold the complex nature of relationships between market agents in a scenario
of scarce data.
