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Dark money, and what banks can do about it

Recent money-laundering scandals have shaken public trust in the banking sector. How can banks rethink their approach to AML? 

The BBC’s recent Panorama documentary, “Banking Secrets of the Rich and Powerful,” is an uncomfortable watch for anyone working in the banking sector. While all banks have anti-money laundering (AML) teams and talk about the significant investments they make in monitoring and reporting financial crime, a string of recent scandals has shown that the current system just isn’t working.

I recently spoke with one of the contributors to that documentary: Graham Barrow, who runs The Dark Money Files, an organisation that focuses on educating the public about the mechanisms and impacts of money laundering, corruption, bribery and tax evasion. 

UK companies’ role in international money laundering

As Graham says in the programme, every major money-laundering scheme he’s ever investigated has had UK companies at its heart. The UK financial system has become central to international money laundering because it’s so easy to set up a company as a limited liability partnership (LLP) – with almost no checks on company ownership, business activity or even accounts. Using these and other similarly opaque corporate vehicles, criminals can move dirty money without leaving a trace.

Some of the methods that criminals use are incredibly brazen – such as registering hundreds of companies at the same address and even filing identical accounts for each of them. To be fair, banks do typically comply with AML regulations by filing a suspicious activity report (SAR) whenever they detect this type of problem. Yet while these SAR red flags are often plain to see, they are still commonly ignored. Why?

Critical flaws in suspicious activity reporting

The SAR process is critically flawed because the volume of reports is so high, and the regulatory resources devoted to handling them are so limited. In the UK alone, banks file around 2,000 new SARs every day. And there are only about 100 people reviewing and investigating them. 

Contrast this with one of Graham’s recent investigations, where 400 specialists from the International Consortium of Investigative Journalists (ICIJ) put a leaked set of just 2,300 SARs under the microscope for several months to piece together the shocking story of a huge international laundromat for dirty money. 

Without this kind of dedicated, focused resource, it’s likely that the majority of SARs that banks file won’t even get reviewed, much less investigated. There needs to be a better way to handle the flood of incoming data on suspicious activity so that investigators can focus on the biggest and most serious flows of illegal money. 

Technology and collaboration are the keys to progress

As Graham told me, we need to utilise the power that SAS and other analytics companies can bring to help AML teams isolate the signal from the noise so they’re not spending 98% of their time reviewing false positives. 

Better collaboration between AML specialists and technology teams is a key area for improvement. Graham shared a story about a bank that had never updated the rules it used for transaction monitoring because its investigation team didn’t have the skills to update the system. Graham decided to convene a regular meeting where investigators could present difficult cases to the bank’s technology team. And as soon as the tech team understood the problem, they offered to write new algorithms that would catch a higher percentage of suspicious transactions. Building a forum where AML experts and technologists can come together and establish a shared vocabulary is vital if you want to make progress.

Opportunities for artificial intelligence

There are also big opportunities for new technologies, such as artificial intelligence and machine learning (AI/ML), to contribute to the fight against international money laundering. Especially for identifying patterns in unstructured data, such as text documents and audio recordings. These techniques offer great potential to help investigators find the needles of financial crime in a vast and ever-growing haystack of SARs. The main challenge, at this point, is transparency. AI-based techniques are often a black box, but we will need the results they produce to be explainable, as well as accurate, if we’re to shine a light on the inner workings of the world’s greatest criminal machines.

Counting the human cost

Since watching the Panorama documentary and speaking with Graham, I’ve been having conversations with AML engineers and specialists at several of the UK’s biggest banks. And it’s been enlightening to see both their intellectual and emotional response to a broader perspective of how money laundering impacts real people and society as a whole. When you’re working on these problems every day, it’s all too easy to get bogged down in the details and forget why what we’re doing matters. But the big picture is really important. 

In short, money laundering isn’t just a white-collar crime that shuffles virtual money between banks’ computer systems. Specifically, money laundering is not just the last mile of the criminal process; it’s often the first. Once criminals establish an easy way to clean their dirty money and get away with it, it creates a huge incentive for further criminal activity. If there’s a safe space for the proceeds of organised crime, then bribery, corruption, fraud, drug and people trafficking, exploitation, and murder are the inevitable outcome. The human cost is too great and too terrible for any of us to ignore.

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This post is from a series of posts in the group:

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