The paper targets the nexus between corruption and money laundering. Scholars and practitioners recently observed how offshore financial centers and financial infrastructures have become central in facilitating corruption and other criminal activities. 

Offshore vehicles often serve to conceal the connections between business people and politically exposed persons. Secrecy jurisdictions and service providers have emerged as key actors in these illicit schemes. 

The paper explores the following questions: 

The paper investigates the role of criminal networks in fostering illegal wildlife trade (IWT), and how these relational structures interact with transnational organized crime. The paper frames these topics within the debate around the opportunistic or organized nature of IWT. The aim is to understand how chaotic behaviors can transform into an ordered and organized strategy.

What does the web of connections look like that underlies grand corruption and money laundering schemes and the abuse of offshore financial centres? Who are the people involved, how do they interact and what do they do?

And what insights can we draw by looking at complex corruption and money laundering schemes from the perspective of social networks, rather than solely individuals?

These questions are at the heart of a new analysis of the so-called Lava Jato or Odebrecht scandal that has engulfed Latin America.

This working paper is based on an empirical investigation of corruption and illicit exchange related to the so-called “Lava Jato” or “Odebrecht” scandal. Focusing on former Peruvian President Alejandro Toledo and his laundering of bribes obtained from the construction giant Odebrecht, the analysis aims to test the usefulness of applying a network lens to better understand the mechanisms underlying grand corruption cases.

This report presents the findings of a novel application of social network analysis (SNA) to study a criminal network surrounding an East Africa-based wildlife trafficker. This technique focuses on understanding structural, functional and sociometric characteristics of networks by mapping social interactions between individuals and groups.