This paper explores the application of artificial intelligence (AI) in sanctions screening, focusing on how the technology can address the growing challenges posed by increasingly complex regulatory environments, limitations of the traditional rules-based sanctions screening systems, dynamic changes in sanctions lists and the need for greater operational efficiency and consistency in alert handling. The discussion centres on challenges faced by financial services firms in particular, but also by any organisation subject to sanctions compliance obligations. The paper explores how AI, in particular the current capabilities of generative AI powered by large language models (LLMs), can potentially offer significant enhancements to traditional rule-based sanctions screening systems and provide guidance on how an organisation can prepare for the use of AI in sanctions screening. It also outlines the technical, organisational and regulatory prerequisites for successful AI integration, including robust governance, technological maturity, model explainability, transparency and fairness and workforce upskilling. Early adopters are already demonstrating measurable benefits in efficiency and risk detection, signalling that AI is beginning to shift from experimental to practical use in early-adopter organisations. This paper further offers practical strategies for implementation, from defining success metrics to training operations and compliance teams to interpret and challenge AI decisions. It concludes that realising AI’s potential will depend not only on technological readiness but also on alignment with regulatory expectations, cross-functional expertise and strong governance, all of which are crucial to embedding AI into sanctions compliance programmes. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Piecuchova et al. (Sat,) studied this question.
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