Anti Money Laundering Reporting and Investigation - Sorting the Wheat from the Chaff

Much crime investigation today is carried out by automatic scrutiny of large transaction databases, with considerable value placed on the use of profiles to seek out unusual and potentially suspicious behaviour. However, the power of automated profiling can result in negative outcomes such as over-reporting and increased expenditure on manual compliance checking. This paper examines some of these problems using a semiotic framework that draws attention to the delicate interplay of technical and social factors in the search for both efficiency and effectiveness. The framework involves a six level semiotic model through which each level permits a focus on different elements of concern for how agents identify signs and create meaning within a normative context. Instead of the prevailing assumption about a simple flow of information from financial institution to Financial Intelligence Unit and prosecuting agency, this approach suggests that the identification and communication of suspicion is a more complex and social process whose nature should be better understood.