For many graduates, the months following their final dissertation submission are defined not by relief but by uncertainty. One former philosophy and law student knows that feeling well and found an unexpected answer in the world of anti-money laundering (AML).
Writing for Napier AI, the graduate describes completing a Master of Laws in Law & Technology at Queen’s University Belfast in 2024, having already accumulated an undergraduate degree in English Literature and Philosophy and a Graduate Diploma in Legal Studies.
Despite strong academic credentials, meaningful employment proved elusive. Paralegal roles, legal tech positions, and technical writing jobs all resulted in rejection, including a particularly bruising experience involving six interview rounds for a FinTech paralegal role, only for the company to postpone recruitment altogether.
The turning point came from an unexpected source: a checkbox on a rejection email asking whether the applicant was happy to be contacted for future roles. Months later, Napier AI, a RegTech firm specialising in AML compliance technology, reached out, ultimately offering a role as content automation assistant.
That entry-level position opened the door to a world the graduate had never previously considered. Working at a technology vendor serving financial institutions provided a distinctive vantage point into AML’s mechanics, from Requests for Proposals and third-party risk assessments to due diligence questionnaires. Within months, they had progressed to a client solutions consultant role, contributing to client-facing projects, competitive bids, and industry events.
So why should graduates pay closer attention to AML? According to Napier AI’s AML Index, reducing illicit financial flows could return more than $3.3tn to global economies annually. The work sits at the intersection of regulation, finance, technology, and behavioural psychology, making it particularly well-suited to those from humanities and social science backgrounds who bring analytical rigour, pattern recognition, and the ability to synthesise complex information.
The technology underpinning modern AML is also far more sophisticated than many expect. Automation, artificial intelligence, and data visualisation tools are now central to how financial institutions detect suspicious activity, with professionals building detection scenarios and designing rule logic to identify patterns that human analysts might overlook.
Crucially, AML is not confined to traditional banking. The field spans FinTech, digital assets, asset management, payments, gaming, and real estate, meaning the skills developed transfer broadly.
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