Transform your anti-money laundering (AML) operations and discover how our expertise can support you in selecting, designing, and implementing AI/ML-based solutions that are cost-efficient, effective, and aligned with global standards.
Money laundering has become a global concern, fuelled by the rise of new methods, evolving typologies, sophisticated criminals, and control lapses. This alarming trend is estimated to range from USD 800 million to USD 3 trillion. As criminals constantly devise evasive techniques, driving up compliance costs and making traditional methods ineffective, banks are under immense pressure to find effective solutions to combat money laundering.
In this landscape, traditional Financial Crime and Compliance (FCC) operations struggle to keep up with the increasing transaction volumes, regulatory requirements, and industry competitiveness. Fortunately, AI and data analytics offers a solution to enhance FCC operations. These AI-enabled monitoring and surveillance solutions automate tasks, identify patterns, and swiftly detect suspicious activities. This can notably not only reduces compliance costs but also minimises disruptions to legitimate customers.
Traditional anti-money laundering (AML) methods, even with automated transaction monitoring (TM), suffer from excessive manual intervention, inefficiencies, errors, and a lack of contextual understanding. This means complex money laundering patterns may go undetected.
Organisations that rely on traditional AML approaches commonly face challenges such as:
Ensuring the solution has incorporated adequate measures to address such deficiencies can significantly enhance compliance operations.
Leveraging artificial intelligence (AI), and other advanced technologies throughout the customer lifecycle, can significantly benefit AML operations with enhanced efficiency, improved accuracy in identifying suspicious activities, and better compliance with regulatory requirements. It is important to ensure proper data governance, address potential biases, and maintain human oversight to mitigate risks and ensure the ethical and responsible use of AI in AML operations.
The rapid evolution of ML typologies and the sheer volume of transactions, along with the need to constantly redesign and recalibrate rules, has rendered conventional systems almost unusable in the current landscape. The complex and time-consuming nature of compliance operations increases the potential for lapses and the likelihood of substantial penalties. Hence, regulatory bodies encourage the adoption of automated systems to cope with the increasing complexity of modern AML. Thankfully, AI-driven AML tools offer efficient and expedient execution of essential tasks.
Client: A large retail bank facing multiple challenges in effectively identifying and preventing money laundering activities across its customer base.
Problem: The existing rule-based AML TM system generates a high number of false positives, placing excessive workload on the TM unit and resulting in a significant backlog of cases. Additionally, the manual tuning and rule design requirements have led to gaps in the overall AML risk coverage.
Solution and approach:
The bank implemented an AI-driven solution that combines several key components:
The use case demonstrates the successful application of an AI-driven solution to combat money laundering. The solution will provide the bank with multiple benefits in its AML TM operations, including:
By revamping your AML operations with the power of AI and data, you can significantly enhance detection capabilities and stay ahead of evolving money laundering activities. With that in mind, our comprehensive range of services is designed to support you in various critical areas:
Speak with our experts to explore how you can revolutionise your AML operations.
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