Social network analysis tools in the fight against fiscal fraud and money laundering

Abstract

Wealth concealment always involves covering up relationships between a taxpayer and his or her wealth or between a taxpayer and other taxpayers. We regard the fight against fraud as the discovery of hidden relationships, and we use social network analysis (SNA) to address the risk analysis of wealth concealment. Relationships can be concealed through the interposition of front men and networks of interposed companies possibly located in tax havens. Their discovery is one of the main challenges in the fight against corruption and money laundering. Traditional risk analysis systems are insufficient to combat this, since fraudsters do not advertise their wealth. Risk detection and selection must combine multivariate statistics techniques with social network analysis and machine learning techniques and should not only detect criminals but also recognize and detect fraud patterns. We report the data of research carried out to combat these forms of financial crime using for the first time the totality of tax authority (AEAT) data.