IBM RegTech Innovations

Stemming the AML crisis and seeing immediate value with AI

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When it comes to AML compliance, or the lack thereof, the financial industry is having rough year. A number of money laundering schemes have come to light, including the $8.8 billion Troika Laundromat, which have exposed or implicated a large swathe of the industry.

Despite wide talk of deregulation, penalties from Office of Foreign Assets Control (OFAC) of the U.S. Department of the Treasury alone have been higher in the first four months of 2019 than the last four years combined (approximately USD 1,227 billion vs. 812 billion). Keep in mind, this is only one regulatory body in one country and barely four months into 2019. We’re just getting started, as can be seen from the $1.3 billion fine just settled with an Italian bank a few weeks ago.

What’s changing in AML compliance

The high-profile money laundering exposés, from Troika to the Paradise Papers, and the subsequent regulatory penalties that typically follow them, suggest that the current approaches are not working – and that financial services organizations just cannot move quickly enough to address money laundering while it’s happening.

We’ve talked about the changing attitudes of regulators to advanced analytics and artificial intelligence (AI) and how financial institutions can truly balance reducing AML costs while still appeasing regulators.  And while many financial institutions don’t have the time, let alone the funds, for a complete overhaul, remedial action and better results are needed immediately. The reality is, they need immediate help and can’t spend the next two to three years and multiple millions of dollars it typically takes to replace existing AML platforms. The ideal state is too far off, but there are critical strategies that can be had now.

Waiting for ideal is no longer an option

In an ideal world, banks would decommission their outdated legacy systems and replace them with the latest solutions that take advantage of newer technologies like automation, cognitive and artificial intelligence. However, this takes a lot of time and money, which is one of the reasons many institutions continue to use aging systems that can produce a high number of false positives. Just throwing more people at the problem has been viewed as a much simpler approach, even if not as effective.  But there is another way.

Instead of the typical rip and replace, financial services organizations can take a more agile approach to complement their existing capabilities with explainable AI, automation and advanced analytics in a fraction of the time it would take to start from scratch and rebuild years’ worth of detection models, integrations and processes. Likewise, waiting for an existing system to be updated or upgraded can waste bank resources on low quality alerts and mundane manual processes.

Working toward more “open” AML

IBM has been a long-time advocate for open technology and designs its solutions for interoperability. This mindset permeates our cloud approach, Red Hat acquisition, and financial crime prevention strategy as well. Interoperability and open source mean that updated technologies and improved results can be adapted quickly across more functional areas, geographies, systems, clouds, vendors and processes – without expensive, time-consuming rip and replacement of existing systems. These capabilities can be applied and adapted to existing financial crime detection models – with existing tools. Interoperability and open source contribute to the speed and cost-efficiency of these solutions.

What are the “updated technologies” and what can they deliver for a financial institution today? Machine learning, AI and ensembles of various advanced analytics can deliver some enviable capabilities for AML, including the ability to automate low-value but highly time-consuming processes, and cognitive self-learning that keeps optimizing outcomes based on previous decisions. Techniques like these can drive increases in accuracy and consistency – contributing to faster return on value as well as greater effectiveness and more engaged analysts that focus on decision-making rather than data gathering. These features are part of the IBM Financial Crimes Insights solution, designed for use without disrupting existing AML compliance or financial crime prevention infrastructure.

Smarter approach to AML

It’s time to move beyond the “walled garden” approach to technology, which leads banks and insurers to depend on outdated systems that require greater numbers of analysts but don’t produce better results. The tools are available now through updated technology, open and interoperable approaches, and agile, evolutionary improvements. Both financial institutions and technology providers can work collaboratively to help stem the AML crisis, but only if we use the modern, open capabilities that can make an impact today.

Vice President, Financial Crimes & Conduct Risk

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