Estimating the Scale of Illicit Financial Flows: The Abnormality Method
Estimating the Scale of Illicit Financial Flows: The Abnormality Method
| Authors: | Daniel Coll Sol Mario Cuenda García Bathusi Gabanatlhong Miroslav Palanský Tijmen Tuinsma |
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| Published in: | IES Working Papers 8/2026 |
| Keywords: | Illicit Financial Flows, Offshore Financial Centres, Revenue Losses, Machine Learning, Automatic exchange of Information |
| JEL Codes: | H26, F21, F23, C45 |
| Suggested citation: | Coll Sol D., Cuenda García M., Gabanatlhong B., Palanský M., Tuinsma T. (2026): " Estimating the Scale of Illicit Financial Flows: The Abnormality Method " IES Working Papers 8/2026. IES FSV. Charles University. |
| Abstract: | This paper introduces the abnormality method to estimate illicit financial flows (IFFs) using a bilateral gravity model complemented by a machine learning technique to analyse unexplained financial flows to offshore centres. The findings provide robust evidence linking abnormal flows to offshore financial centres with tax avoidance and evasion and offer new estimates of their scale, costs, and geographical distribution. In 2023, abnormal flows to tax havens and secrecy jurisdictions reached US$2.8 trillion, resulting in foregone tax revenues exceeding US$60 billion. These flows originated mainly from Europe, the Americas, and Asia, flowing mostly to European tax havens. Random Forest analysis confirms that tax haven and secrecy jurisdiction status are key determinants of abnormal financial flows. Furthermore, the analysis of the Automatic Exchange of Information (AEOI) regulation indicates an increase in abnormal flows held in secretive jurisdictions. |
| Download: | wp_2026_08_coll sol, cuenda, gabanatlhong, palansky, tuinsma |
