Modelling smurfing patterns in cryptocurrencies with integer partitions

In this paper, we propose the modelling of patterns of financial transactions - with a focus on the domain of cryptocurrencies - as splittings and present a method for generating such splittings utilizing integer partitions. We study current money laundering regulations and directives concerning thresholds for monitoring of financial transactions. We further exemplify that, by having the partitions respect these threshold criteria, the splittings generated from them can be used for modelling illicit transactional behavior such as is shown by smurfing. In addition, we conduct an analysis of the splittings occurring in money laundering efforts that took place in the aftermath of the Upbit hack. Based on the potential weaknesses identified by our research, we finally provide suggestions on how to improve current AML techniques and initiatives towards more effective AML efforts.