Mapping the state of the art: artificial intelligence for decision making in financial crime


This chapter provides an overview of the recent literature on the diverse applications of artificial intelligence-based solutions to financial crime issues. This is the first survey of its kind, with a practitioner-oriented, multidisciplinary approach focusing broadly on financial crime-related solutions, not targeting a specific crime typology. In so doing, we are specifically targeting potential decision makers and relevant stakeholders both from industry and governmental agencies, such as risk or fraud analysts, compliance officers, law enforcement officers, managers in financial institutions, policymakers, and academics with neighboring interests, so that they can appraise the capabilities, drawbacks, and particular techniques favored by researchers when confronting issues specific to the context of financial crime. Following a chronological approach, current techniques, emerging applications, and developing trends are discussed, contextualizing artificial intelligence as a good resource yet to be employed to its full potential. Specific focus is given to the recent role of industry-academia partnerships in shaping future research and helping overcome the applicability gap that has emerged in pre-existing research.

In Taylor & Francis/CRC Press
Theodore Papamarkou
Theodore Papamarkou
Reader in maths of data science

I am interested in speeding up computation.