Networks of monetary flow at native resolution

Abstract

People and companies move money with every financial transaction they make. We aim to understand how such activity gives rise to large-scale patterns of monetary flow. In this work, we trace the movement of e-money through the accounts of a mobile money system using the provider's own transaction records. The resulting transaction sequences---balance-respecting trajectories---are data objects that represent observed monetary flows. Common sequential motifs correspond to known use-cases of mobile money: digital payments, digital transfers, and money storage. We find that each activity creates a distinct network structure within the system, and we uncover coordinated gaming of the mobile money provider's commission schedule. Moreover, we find that e-money passes through the system in anywhere from minutes to months. This pronounced heterogeneity, even within the same use-case, can inform the modeling of turnover in money supply. Our methodology relates economic activity at the transaction level to large-scale patterns of monetary flow, broadening the scope of empirical study about the network and temporal structure of the economy.

References in corpus (9)

• Community detection in graphs
• The scaling laws of human travel
• Do the rich get richer? An empirical analysis of the BitCoin transaction network
• Memory in network flows and its effects on spreading dynamics and community detection
• Random walks and search in time-varying networks
• Betweenness Preference: Quantifying Correlations in the Topological Dynamics of Temporal Networks
• Exploring Temporal Networks with Greedy Walks
• Understanding Complex Systems: From Networks to Optimal Higher-Order Models
• The topology of card transaction money flows