Reducing False Positives in AML Transaction Monitoring: A Risk-Based Framework Applied to a Composite UK Banking Case

Malki Senevirathne

Abstract: Anti-money laundering (AML) transaction monitoring systems in UK financial institutions typically generate false positive rates of 85-95 per cent. Compliance teams spend up to 90 per cent of investigation time on alerts that never result in a Suspicious Activity Report. This paper sets out a risk-based framework for reducing false positives without weakening detection: it combines customer risk segmentation, above-the-line/below-the-line threshold tuning, periodic rule rationalisation, and a hybrid model that pairs automated detection with targeted manual review. Disclosed institutional data was not available, so the framework is applied step by step to an illustrative, composite mid-sized UK retail and commercial bank built entirely from published academic and industry benchmarks, not any real organisation's figures. Applying published threshold-tuning effect sizes to the composite case's modelled baseline of 800 alerts a day suggests that tuning and rationalisation alone could cut alert volume by roughly one-sixth and free up approximately 81 analyst-hours a day for higher-value review, while keeping the great majority of genuine escalations. The paper also sets out the governance evidence and second-line resourcing this approach needs, and identifies empirical validation against real institutional data as the necessary next step to establish whether these modelled gains would hold in practice.

Keywords: Anti-Money Laundering, Transaction Monitoring, False Positives, Risk-Based Approach, Financial Crime Compliance

How to Cite?: Malki Senevirathne, "Reducing False Positives in AML Transaction Monitoring: A Risk-Based Framework Applied to a Composite UK Banking Case", Volume 15 Issue 9, September 2026, International Journal of Science and Research (IJSR), Pages: 1180-1188, https://www.ijsr.net/getabstract.php?paperid=SR26919052446, DOI: https://dx.doi.org/10.21275/SR26919052446

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