Identifying illegal cartel activities from open sources

Abstract

In a truly free marketplace, business entities compete with each other to appeal and to satisfy the purchasing needs of their customers. This elegant and efficient process can only succeed when competitors set their prices independently. When collusion occurs among competitors, prices rise, quality is often compromised and the public at large loses. In all developed countries around the world, price fixing, bid rigging and other forms of collusion are illegal and prosecuted through judicial systems. The relevance of OSINT for this form of activity is two-fold: as covertly conducted activity between parties, market manipulation and price fixing is particularly difficult to detect and prove while, at the same time, it is particularly susceptible to automated information discovery which can be vital for law enforcement agencies. However, finding even weak threads of evidentiary material requires extensive human and financial resources. This chapter proposes an automated methodology for text and data analysis, which aims to save both professional time and cost by equipping investigators with the means to detect questionable behavioural patterns thus triggering a more intimate review. This is followed by working examples of how OSINT characteristics and techniques come together for law enforcement purposes.