Mapping the disaggregated economy in real-time: Using granular payment network data to complement national accounts

Abstract: In an era of rapid change, timely and disaggregated economic insights are crucial for effective policymaking. This study explores the potential of real-time payment data to complement traditional economic measurement. Using anonmysed UK business payments from 2015-2023, we analysed inter-industry financial flows at a granular 5-digit SIC level and compared them systematically with established economic indicators such as GDP and input-output tables (IOTs). Our findings show strong correlations with GDP and qualitative consistency with official IOTs, highlighting the value of the novel high-frequency data for real-time economic monitoring. We also benchmarked network statistics at the 5-digit level, showing how industry-specific payment structures align with stylised facts from the empirical economic network literature. While outlining methodological and interpretative challenges, we discuss the integration of such bottom-up data into national accounts. This work contributes to ongoing efforts to advance economic measurement and offers additional tools for tracking economic dynamics in real time.