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Evolution or revolution?
The maturing of anti-money laundering controls
By Alexon Bell, Compliance Solution Director, SAS
The world’s largest financial institutions are focused on reforming their anti-money laundering (AML) and counter-terrorism financing practices. New regulations and guidance on risk-based approaches to AML have concentrated attention on the shortcomings of the old monitoring and control regimes.
The US authorities have given stiff fines to organizations for failing to adequately detect money laundering. These have included a $1.9 billion penalty issued to HSBC and an $8.9 billion charge handed to BNP Paribas.
The scope of the regulations and the scale of the fines have underlined the urgency of addressing this issue. Today, it’s clear that AML is no longer simply an operational numbers issue. Instead, financial institutions need to take a true risk-based approach, applying new capabilities and technologies to meet the evolving regulatory environment.
Using HPA in a co-existence mode - alongside incumbent solutions – can reduce false positives in the older system by up to 80 percent.
High performance analytics (HPA) are changing the way institutions monitor risk. HPA enables users to:
- Run more rapid, comprehensive analytics to visualize the flow of funds as patterns emerge.
- Reduce processing time from hours to minutes or seconds - that speed transforms an institution’s ability to identify risk exposures and implement controls.
- Improve the quality and accuracy of the detection process to reduce false positives and increase operating efficiency.
Through the use of HPA, a new AML landscape is emerging that retains the traditional controls of first-generation solutions and layers on intelligent analytics to manage risk and alert volumes. This is helping bring together vendors and a compliance ecosystem to achieve an intelligent risk-based AML solution. It is an approach that will deliver transparency, making it easier to meet evolving regulatory requirements.
How can you make it happen?
- The first step is to define how you are going to monitor. Your organization must break free from the destructive cycle caused by an overload of false positives, the sheer volume of which is placing strain on compliance budgets and programs.
- The next critical stage is control. The growing interest in the governance model will continue over the next few years as organizations evaluate how their control environments and systems behave and how they govern them.
- The final element is about effectively managing the AML environment, delivering an end-to-end monitoring system that ensures full risk coverage. A best practice approach must focus on multiple stages in the monitoring and control lifecycle with the ability to add more contextual information when required and process it quickly and efficiently. For this, big data analytical technologies such as Hadoop combined with HPA tools are a must. New features such as dynamic data exploration allow investigators to analyze and identify the problems.
In parallel, data scientists can further improve detection quality by using hybrid analytics, including advanced data mining techniques, text mining and social network analytics to map organizational links between the money launderers.
Your existing systems may struggle to keep up with the new regulatory requirements and the fast-changing behavior of the money launderers. But your regulators need to be confident that you can actively detect new money laundering techniques and that your systems can be quickly brought up-to-date if required. And so the constant for your institution will be the need for flexibility, agility and transparency.
That’s not to say that all organizations should abandon their existing first-generation solutions and put more flexible second generation ones in their place. For most, a rip and replace approach is simply not possible in the short-term. Instead, they are using HPA alongside incumbent solutions.
Using HPA in a co-existence mode like this can reduce false positives in the older system by up to 80 percent, dramatically cutting the workload and total cost of ownership and paving the way for a smoother upgrade path for adopting the latest detection and analytical technology.
Ultimately, next-generation systems must be flexible and agile and should harness technology to transform compliance for the benefit of banks, regulators and society as a whole. There is still much to do, but the industry is moving in the right direction. Learn what it takes to create an enterprisewide view of customer relationships and risks, monitor activity using multiple detection methods, adapt that monitoring as appropriate for each customer's risk classification, investigate and document suspicious cases, and produce required regulatory reports – all within an integrated solution.
Learn what it takes to create an enterprisewide view of customer relationships and risks, monitor activity using multiple detection methods, adapt that monitoring as appropriate for each customer's risk classification, investigate and document suspicious cases, and produce required regulatory reports – all within an integrated solution.