  We construct a network of 1.6 million nodes from banking transactions of
users of Rabobank. We assign two weights on each edge, which are the aggregate
transferred amount and the total number of transactions between the users from
the year 2010 to 2020. We present a detailed analysis of the unweighted and
both weighted networks by examining their degree, strength, and weight
distributions, as well as the topological assortativity and weighted
assortativity, clustering, and weighted clustering, together with correlations
between these quantities. We further study the meso-scale properties of the
networks and compare them to a randomized reference system. We also analyze the
characteristics of nodes and edges using centrality measures to understand
their roles in the money transaction system. This will be the first publicly
shared dataset of intra-bank transactions, and this work highlights the unique
characteristics of banking transaction networks with other scale-free networks.

Social and Information Networks;Physics and Society