Legalization of criminal income using DeFi: typical schemes and risk indicators

Objective : to increase the effectiveness of countering the use of typical criminal money laundering schemes by identifying the technological and legal vulnerabilities of the DeFi infrastructure: decentralized exchanges, blockchain bridges, decentralized wallets, and privacy-enhanced currencies. Methods : general scientific (analysis and synthesis, induction and deduction, theoretical modeling, legal interpretation) and special methods of scientific cognition (structural-functional, constructive, situational, innovative, target-oriented, program-target, and risk-oriented). Results : the main trends in the development of money laundering using decentralized finance were outlined; the determinative significance of DeFi technological characteristics in the genesis of money laundering was revealed; the main types of money laundering using decentralized finance were identified; the schemes of committing crimes were studied and the criminogenic potential of DeFi infrastructure (decentralized exchanges, blockchain bridges, mixers, privacy-enhanced tokens, etc.) was assessed. Scientific novelty : it is proposed to consider money laundering using DeFi as a special type of digital financial crime. The article proposes the author’s typology of money laundering, substantiates the idea that the matrix of traditional financial regulation and AML standards cannot be applied to decentralized finance. It is argued that prevention of money laundering using decentralized finance should be carried out in close connection with the identification of risk indicators and the development of effective control measures at the points of entry of criminal incomes to centralized exchanges. Practical significance : the analysis of typical mechanisms of money laundering using DeFi allows a systematic approach to the organization of early crime prevention and can potentially become the basis to develop recommendations for financial intelligence and monitoring services.