Can AI strengthen transaction monitoring against money laundering in the UK?

Ryder, Nicholas ORCID: https://orcid.org/0009-0008-8712-2946 2025. Can AI strengthen transaction monitoring against money laundering in the UK? Presented at: AI and Banking Webinar Series, Online, 16 September 2025.

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Abstract

Money laundering, the process of disguising the origins of illicit funds to integrate them into the legitimate financial system, poses a substantial threat to the UK’s economic integrity. Estimates suggest that the annual volume of criminal proceeds laundered through UK financial and professional services sectors runs into the hundreds of billions of pounds. The UK’s frontline defence is the Suspicious Activity Report regime, which generates over 850,000 reports each year and maintains a secure database, supplying vital intelligence for law enforcement and regulatory intervention. This paper analyses prominent failures in transaction monitoring through case studies of HSBC Bank plc, Deutsche Bank, Monzo Bank Ltd, National Westminster Bank Plc, and Barclays Bank UK PLC/Barclays Bank PLC, demonstrating how weaknesses in customer due diligence, transaction oversight, and governance enable high-end laundering schemes. In particular, Monzo was fined £21 million for systemic control deficiencies between 2018 and 2020, and Barclays faced penalties exceeding £42 million for lapses in due diligence and failure to act on red flags from 2012 to 2023. The paper then examine the transformative potential of artificial intelligence in transaction monitoring to reduce false positives and uncover complex laundering typologies. Our findings indicate that embedding AI-driven analytics within a robust risk-based framework could enhance detection efficiency.

Item Type:	Conference or Workshop Item (Other)
Status:	Unpublished
Schools:	Schools > Cardiff Law & Politics Research Institutes & Centres > Cardiff Centre for Crime, Law and Justice (CCLJ)
Subjects:	K Law > K Law (General)
Date of First Compliant Deposit:	18 September 2025
Date of Acceptance:	11 September 2025
Last Modified:	22 Sep 2025 15:01
URI:	https://orca.cardiff.ac.uk/id/eprint/181158

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