Explore AML & Sanctions Compliance Resources

An AML (Anti-Money Laundering) Analyst plays a vital role in detecting and preventing financial crime by monitoring transactions, investigating suspicious activity, and ensuring compliance with regulations. They work across banks, fintech firms, and regulatory bodies to identify money laundering and terrorist financing risks. Key skills include attention to detail, analytical thinking, knowledge of financial regulations, and discretion. Most analysts have a background in finance, law, or business, and benefit from certifications like ICA or ACAMS. With career progression into senior compliance or financial crime roles, and growing demand driven by global regulation and digital risks, becoming an AML analyst offers a rewarding and impactful career path.

Bank of America has publicly acknowledged the cease-and-desist order issued by the OCC and affirmed its commitment to improving its anti-money laundering (AML) and sanctions compliance programmes. The bank has been engaging with regulators over the past year to address existing gaps and has stated that it is well-positioned to meet the requirements outlined in the enforcement action. In its October 2024 filing, Bank of America had already indicated that regulatory discussions were underway and signalled the likelihood of future actions. Despite the seriousness of the OCC's findings, the bank does not anticipate any material adverse financial impact resulting from the order.

In today’s data-driven world, the Open Source Intelligence (OSINT) framework has emerged as a powerful approach to extracting actionable insights from publicly accessible information across digital platforms. From cybersecurity and national security to business strategy and humanitarian response, OSINT enables organisations to monitor, analyse, and respond to developments in real-time—cost-effectively and ethically. It leverages diverse sources such as social media, news outlets, public records, and geospatial data, turning unstructured data into strategic intelligence through automated tools and expert analysis. While its advantages include scalability, comprehensive coverage, and legal transparency, OSINT also presents challenges related to data overload, accuracy, and ethical use. As technology advances, the integration of AI, real-time visualisation, and cross-domain intelligence sharing is poised to enhance OSINT’s impact, making it a cornerstone of modern intelligence practices in both public and private sectors.

The OFAC alert regarding Russia's SPFS system highlights the growing challenges financial institutions face in navigating sanctions compliance. With SPFS facilitating potential sanctions evasion, banks must reassess their risk management frameworks, scrutinise correspondent relationships, and leverage specialised data sources to identify exposures. Divergent regulatory approaches between the US and EU further complicate compliance efforts, necessitating robust, adaptable strategies. Proactive measures, including the integration of advanced screening tools and real-time data, are essential for institutions to mitigate risks and uphold the integrity of the global financial system.

The Corporate Transparency Act marks a significant advance in the fight against financial crime by requiring companies to disclose beneficial ownership information to US authorities. Aimed at increasing transparency, closing regulatory gaps, and aligning with international standards, the Act imposes new compliance obligations on many small and medium-sized businesses. While it strengthens accountability and corporate governance, it also presents challenges around privacy, enforcement, and administrative burden, highlighting the need for businesses to establish robust compliance systems and embrace transparency as a core principle of responsible operation.

Anti-Money Laundering (AML) is getting a boost from Artificial Intelligence (AI). This article explores how AI is revolutionizing AML by detecting hidden criminal patterns, but also discusses the challenges of data privacy and ensuring fair AI models.