Taking an intelligence-led approach: How to improve understanding of financial crime threats through intelligence and analysis

Abstract

The financial crime compliance landscape is evolving, driven by a number of complementary factors: the move towards a more intelligence-led allocation of resources and advances in machine learning and artificial intelligence, both combined with the increasing availability of structured and unstructured data. This paper argues that the best way to take advantage of these developments is through the implementation of an intelligence and analysis model. It provides a high-level example of a model that can identify, understand and investigate the highest risk financial crime concerns. It shows the readers how the different levels of this model — strategic, thematic and tactical — interact to allow for the flow of information between them. In addition, it outlines how this model can integrate into the wider financial crime compliance department and how its outputs can drive tangible improvements in this area.