Mapping the State of the Art: Artificial Intelligence for Decision Making in Financial Crime

Borja Álvarez Martínez, Richard Allmendinger, Hadi Akbarzadeh Khorshidi, Theodore Papamarkou, Andre Freitas, Johanne Trippas, Markos Zachariadis, Nicholas Lord, Katie Benson

Research output: Chapter in Book/Conference proceedingChapterpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationCybersecurity for Decision Makers
EditorsNarasimha Rao Vajjhala, Kenneth David Strang
Place of PublicationBoca Raton
PublisherTaylor & Francis
Chapter12
Pages199-213
Number of pages15
ISBN (Electronic)9781003319887
ISBN (Print)9781032334967
Publication statusPublished - 19 Jul 2023

Keywords

  • Artificial intelligence
  • machine learning
  • financial crime
  • crime detection
  • fraud detection
  • money laundering
  • cryptocurrency
  • risk management
  • decision making
  • neural networks
  • graph analysis
  • social network analysis

Fingerprint

Dive into the research topics of 'Mapping the State of the Art: Artificial Intelligence for Decision Making in Financial Crime'. Together they form a unique fingerprint.

Cite this