With the continued rise of multinational corporations straddling the world, the increase in global compliance requirements, and the continued backdrop of multi-jurisdictional oversight, it is no surprise that there have been a number of high profile cross-border investigations hitting the headlines, including the Wirecard, Tuna Bond and Alstom matters. This article will look at some of the largest and most complex global matters and discuss whether some of the most difficult barriers preventing a successful outcome centre around the demands involved with accessing, preserving and transmitting the evidential data across borders. The article examines some of the issues and suggests how they are best addressed and managed.

Bij beschikking van 17 juli 2024 verklaarde het Hof van Justitie van de Europese Unie (HvJ of het Hof) de penitentiaire kamer van het Gerechtshof Arnhem-Leeuwarden (hierna: het Gerechtshof A-L) niet-ontvankelijk in zijn verzoek om een prejudiciële beslissing.3 Het verzoek betrof de uitleg van verscheidene Unierechtelijke bepalingen in de sfeer van de tenuitvoerlegging van buitenlandse strafvonnissen in Nederland – bepalingen die middels de Wet wederzijdse erkenning en tenuitvoerlegging vrijheidsbenemende en voorwaardelijke sancties (WETS) in de Nederlandse rechtsorde zijn geïmplementeerd.

Over the coming years, new tools based on large language models (LLMs) and other artificial intelligence-based software are set to play an increasing role in many modern administrations, including in the anti-fraud domain. One might even argue that the prevention, detection, and investigation of fraud and associated illegal activities, which today involve processing and analysing an ever-growing volume of data of different types, are uniquely suited to the strengths of such tools. The authors of this article share some reflections on two particular challenges that authorities, which seek to harvest the potential of artificial intelligence for anti-fraud purposes, have to come to terms with: first, how to leverage the strength of artificial intelligence tools by identifying suitable use cases for the specific anti-fraud domain? Second, how to navigate the emerging regulatory framework considering in particular that the European Union’s Artificial Intelligence Act has entered into force on 1 August 2024?