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    HomeFraud PreventionAnti-money laundering tech adoption to hit 3.8mn businesses globally by 2030, led...

    Anti-money laundering tech adoption to hit 3.8mn businesses globally by 2030, led by Europe

    New research from global tech strategists Juniper Research finds that the number of businesses deploying Anti-money Laundering (AML) systems will surge to more than 3.8 million worldwide by 2030; driven by tightening regulatory expectations and rapid adoption of AI-enhanced compliance tools. The study identifies Europe as the leading hub of adoptions, underpinned by its strong enforcement culture.

    An extract from the new report, Anti-money Laundering Systems Market 2025-2030, is now available as a free download.

    “Europe’s early momentum stems from coordinated policy initiatives which encourage cross-border data sharing and strengthen beneficial ownership transparency, such as the recent establishment of the Anti-Money Laundering Authority (AMLA),” says Shane O’Sullivan, Research Analyst at Juniper Research.

    Stricter regulations spur AML innovation

    The report highlights that, by 2030, more than 34% of all AML-enabled businesses will be based in Europe, where mandatory digital identity verification, high-frequency reporting requirements, and advanced transaction-monitoring standards have created strong incentives for system uptake.

    Juniper Research also notes that vendors are accelerating innovation to support this expansion of capabilities, such as AI-driven risk scoring and behavioural analytics, Agentic AI-driven investigation assistants and cloud-native AML platforms.

    Tech landscape evolves to support rapid AML adoption

    “We are seeing AML vendors invest millions and shift towards autonomous, agent-driven systems; marking a fundamental redesign of how compliance workflows operate” says O’Sullivan. “While these technologies are still maturing, particularly in areas that require complex reasoning, they are currently strengthened by human oversight at key decision points to maintain accuracy and trust. As capability advances, they will increasingly augment human teams, while enhancing the speed, scale, and consistency of investigation processes.”

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