Unleashing the Anti-Money Laundering Potential with Cloud Technology
Advantages of cloud technology for AML
The migration to the cloud is not new. Process rationalisation and harmonisation, data centralisation and cost reduction are on top of the IT agenda. From an IT perspective, there is already momentum for a transition to the cloud. However, there is a shift in the driving forces behind the cloud journey from IT to business, as businesses become more acquainted with the benefits of cloud technology. In the context of AML, we identify 5 core advantages of cloud technology that could accelerate AML effectiveness:
1. Data control
Fundamental to a robust AML approach is control over data. Without the availability of the correct data, it is impossible to trace money laundering risks accurately and quickly. Cloud technology offers the possibility to manage data centrally and ensure data traceability (lineage) from source to use. Data is no longer scattered across applications, but instead hosted in one centralized location. All ongoing AML processes, including business as usual activities such as Customer Due Diligence (CDD) and Transaction Monitoring (TM), can draw upon this centralized data regardless of how much data is involved. They can all be based on a common AML ‘feature set,’ providing indications of potential money laundering risks. Additionally, data structures and pipelines can be adjusted swiftly. This means data availability is no longer a blocker but becomes an enabler.
2. Compliance by design and cost-effectiveness
Cloud technology enables the construction of an IT approach that is compliant by design. The cloud platform can be securely managed using standardized services, as cloud solutions incorporate the latest data security methods. This includes not only managing the platform itself, but also the AML components built on top of it. Modern IT management tools and methods like Continuous Integration/Continuous Delivery (CI/CD) and Machine Learning (ML) Ops are natively supported. Furthermore, the cloud is cost-effective. With an IT landscape consisting of dozens of solutions, the costs for legacy infrastructures increase. Unlike traditional approaches that require substantial upfront costs and subscriptions to expensive licences, cloud technology works with cloud cost management, enabling businesses to ensure that cloud resources are used sensibly and with the appropriate pay-per-use controls.
3. Agility and speed
The licensing setup of traditional systems not only has financial implications, it also binds organizations to specific solutions for a longer time, impacting the agility to adapt. Cloud technology allows for the swift development, activation, or abandonment of new AML solutions with a simple click. All modern AML technology solutions can be directly deployed on the major cloud platforms, and cloud service providers are beginning to develop AML services as well. AML in the cloud provides the flexibility to scale up or down where necessary and offers more opportunities for innovation and testing. This makes it easier to respond to developments, making the AML approach more flexible and powerful. It is generally expected that developments in AML technology will occur rapidly in the coming years coming years: what is the best capability in the market today, can be outdated half a year later. Having a platform that enables organizations to keep up with this high pace development and allows for experimentation is a key enabling factor towards more effectiveness.
4. AI integration
One specific and impactful example of such technological developments is AI. Cloud platforms generally enable access to advanced AI services. While vendors or standalone solutions may also offer AI functionalities, it might be harder for those solutions to incorporate the latest and most advanced AI technology available. Cloud platforms typically offer the workbench (including notebooks, code repositories, libraries, and data pipelines) that data scientists demand to develop new models and experiment with the latest AI methods. Alternatively, standardized, and pre-trained models can be leveraged as a service. This accelerates the adoption of AI and enables fast implementation in AML processes. Enhanced AI capabilities contribute to improved detection of potential money laundering while reducing operational costs, resulting in greater AML effectiveness.
5. Collaboration across the AML chain
Another critical element of a modern and robust AML approach is collaboration with stakeholders in the AML chain and the broader financial ecosystem. Collaboration fosters better insights into new financial patterns and provides institutions with a deeper understanding of their clients and the associated money laundering risks. Cloud technology facilitates this collaborative approach by enabling secure data sharing. Cloud-based collaboration enables organizations to work simultaneously with the same data and facilitates easier data exchange within and beyond the organization.
