The role of social networks for combating money laundering

Abstract

Money laundering is the disguising of the illegal origin of money by bringing it back into the legal financial circuit. Therefore, in this dissertation I try to establish a theoretical framework to understand the role of social networks, and the link between criminals and legal actors in the money laundering process. I focus on the money laundering method called smurfing; the splitting of large criminal proceeds into small inconspicuous amounts, and since this technique typically requires a network, it requires potential criminals to form links with other people and to construct a money laundering network to launder their money. The research questions are focused on how the networks are formed when criminals strategically form links to launder their money and what the shape of the network is at the macro-level. Moreover, focus is also on optimal policies to fight crime and money laundering, both at the national and the international level. Towards this end, I introduce social network and game theory into the field of money laundering. The study also includes some simulations in order to find the optimal budget for anti-money laundering policy. InChapter 2, I analyze a typical drug-crime scenario by presenting a simple model to study the formation of a money laundering network in this context. I assume that there are three types of actors: criminal bosses, foot soldiers, and dishonest workers. I show that the money laundering network at the macro level has an extended inter-linked star structure in which the talented criminal bosses are fully interconnected. I also show that agents’ willingness to become criminals is endogenously dependent on the wage of workers. In Chapters 3 and 4, I consider only two groups of agents in the network, potential criminals and workers. After characterizing the network I analyze the national and international policy to combat money laundering. The crucial focus of Chapter 3 is the analysis of the optimal mixture of anti-crime and anti-money laundering policies. Which policies should a law enforcement agency focus on to combat either crime or money laundering in order to minimize total criminal activity in a society? In the present model, this is expressed in terms of an optimal budget sharing rule. I also empirically implement the model using real world data and calculate the optimal policy response numerically with a macro-level “sufficient statistics’’ approach. The aim of Chapter 4 is to theoretically assess different options for transnational policy cooperation to fight crime and money laundering. I consider four regimes to combat money laundering: a decentral regime without an international information exchange; a decentral regime with an information exchange; a central regime with an evenly split budget among the two countries; a central regime with a tailor-made budget. I determined the best option from the viewpoint of each country and from the overall viewpoint, considering countries that differ in average income and country sizes. My findings show that the first-best regime is to implement a central authority which allocates tailor-made budgets.