Blockchain Analytics as an Expert Tool for Detecting the Legalization of Wartime Proceeds

Abstract

This study substantiates blockchain analytics as a specialized expert tool for detecting the legalization of criminal proceeds under wartime conditions. The purpose is to systematize the methodological foundations of distributed ledger forensics and develop a conceptual model for its integration into Ukraine’s financial monitoring system. The implementation involves a comparative analysis of scholarly sources and a review of international regulatory standards in the field of anti-money laundering. Graph neural networks ensure an accuracy of 91 to 96 percent in detecting illicit transactions, and the dominant schemes for laundering wartime proceeds are sanctions arbitrage through stablecoins, fund mixing, and DeFi-based legalization through decentralized protocols. The immutability of records in the distributed ledger creates a unique evidentiary environment that enables retrospective analysis of transaction chains even after laundering operations have been completed. The findings confirm the necessity of fully implementing FATF Recommendation 15 and establishing specialized crypto-forensics units within the structure of domestic law enforcement agencies. The proposed four-level model, encompassing data collection, graph analysis, scheme identification, and evidence formation, defines a practical path toward standardizing crypto-forensics in domestic forensic expert practice and improving the effectiveness of financial investigations.