AML Optimisation
BAE Systems has launched a new too l- AML Optimisation - to empower financial institutions with greater insight, understanding, and control over their existing anti-money laundering detection technology. This tool helps firms enhance their efforts to address criminality and comply with new AML laws and regulations more quickly and efficiently.
Over the past decade, regulators have increased scrutiny on institutions, mandating they justify the rationale behind AML model changes, as well as validate the efficacy of existing models and the assumptions upon which those models are built. To satisfy regulators, many organisations undergo long, costly AML model tuning engagements on a periodic basis, which leaves them exposed to money launderers who are constantly presenting new threats. Other institutions employ analysts en masse to manage ongoing model testing and tuning, with some large teams costing millions per year.
The status quo is no longer sufficient or cost-effective. AML Optimisation improves on the effectiveness and efficiency of traditional AML monitoring and detection programs. It is designed to help financial services providers save time and money spent on what often turn out to be false AML alerts.
Providing a structured, user-friendly methodology, AML Optimisation ensures the continued effectiveness and efficiency of AML transaction monitoring and detection models, helping institutions enhance ongoing compliance, increase value, and minimise false positives. Using advance machine learning techniques, this module eliminates time-wasting trial and error, providing analysts with recommended model configurations and the means to test, simulate, and export updated models into production, all while maintaining a detailed record for internal or regulatory audit.
AML Optimisation enables financial institutions to:
  • Increase coverage – Create an AML program that is both more effective and easier to manage using advanced analytics to uncover risk across product lines
  • Maximise analyst efficiency – Reduce analyst time spent on investigating false positives and focus on highest priority issues
  • Reduce personal and institutional liability – Clearly demonstrate effectiveness, efficiency and ongoing process improvement, mitigating potential reputational and financial harm to both the institution and senior management
  • Stay ahead of the curve – Adapt to the changing financial and regulatory environment with the flexibility to analyse, tune, test, and enact new rules in advance of internal and regulator audits 
Find out more about our AML optimisation module here
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How Dirty Money Moves: AML Report

How Dirty Money Moves

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