Can Cash Circulation Predict Money Laundering? Evidence from Indonesian Suspicious Transaction Reports (STRs)

Wartiningsih; Nur Insani

doi:10.59593/amlcft.2025.v4i1.278

Authors

Wartiningsih Badan Pusat Statistik
Nur Insani Royal Melbourne Institute of Technology https://orcid.org/0000-0003-1494-8874

DOI:

https://doi.org/10.59593/amlcft.2025.v4i1.278

Keywords:

Cash circulation, Counterfeit money, Money Laundering, Panel Count Models, STRs

Abstract

Understanding and anticipating money laundering risks remains a formidable challenge for financial authorities, primarily because Suspicious Transaction Reports (STRs) function as lagging indicators rather than real-time proxies for illicit activities. This disconnect necessitates the development of early warning indicators (EWIs) capable of signaling latent risks as institutional reporting behaviors unfold. This study investigates whether fluctuations in currency circulation provide predictive signals for STR volumes in subsequent periods. Drawing on cash-based money laundering theory and acknowledging detection lags inherent in compliance processes, this study argued that currency fluctuations encapsulate information regarding latent suspicious activities that manifest only after a temporal delay. Methodologically, the study employs a panel count model utilizing fixed-effects negative binomial regressions alongside extensive robustness checks, including hurdle and zero-inflated specifications, on monthly panel data from 34 Indonesian provinces spanning 2022 to 2024. The empirical analysis reveals that cash inflows and outflows significantly predict STR volumes with a lead time of two to three months. Conversely, the circulation of counterfeit currency shows no significant correlation. These findings suggest that physical currency circulation can serve as a robust EWI for monitoring financial crime risks, specifically to inform supervisory prioritization, compliance resource allocation, and macro-financial oversight in cash-dependent economies.

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