by Ben Cumming, Deputy Head, Conferences Chatham House (The Royal Institute of International Affairs)
Technological breakthroughs could revolutionise the fight against illicit financial flows, but they must be thoroughly examined if we are to reap their benefits and mitigate harm.
The FCA recently announced that financial crime in the UK had reached “epic proportions”, following a decade of banking scandals that further demonstrate the dire need to reassess our international toolkit for fighting illicit financial flows. These issues are compounded by the fact that, in an era characterised by geopolitical fragmentation, many traditional information-sharing relationships seem precarious at best.
At the same time, however, developments in machine learning and big data continue to advance, seemingly exponentially, and governments and corporations are increasingly looking at them with a mixture of optimism and alarm. But what are the supposed opportunities and risks associated with the various disruptions?
Take blockchain for example. On the face of it, blockchain technology and cryptocurrencies looked like bad news for international IFF efforts. The anonymity they provide would allow money launderers, terrorist financers and other financial criminals to hide their assets and conduct business online with ease, a concern perhaps best demonstrated in the regulatory opposition to Facebook’s Libra. However, blockchains by their very nature are a single connected ecosystem, and therefore their analysis could allow banks to paint a comprehensive, more nuanced picture of activity, and thus catch illicit flows when single instances of behaviour might not appear suspicious.
Machine learning presents another opportunity to fill information gaps. Banks and external stakeholders are systematically collecting data in such fantastic volumes that analysis without machine learning without be impossible. Furthermore, machine learning enhances our ability to distinguish between false positives and real instances of financial crime, adapting to criminal behaviours and identifying nefarious activity much more accurately. On the other hand, predictions based solely on algorithmic machine learning can be misleading, and we have an incomplete understanding of internal systems that flag questionable transactions, the so called “black box” problem. It is important that these mechanisms are combined with human expertise, and rigorously tested, so that they can be better understood before application.
As the FCA’s Head of Financial Crime, Rob Grupetta, warned at the Chatham House Illicit Financial Flows conference last year, “For every transformative innovation, there will be many dead ends or even dangerous ones, with the potential to cause significant harm”, going on to note that “financial crime doesn’t lend itself easily to statistical analysis”. However, with the development and adoption of such technologies only set to increase, banks and regulators must not only look to mitigate the risks they present but harness the accompanying opportunities.
Addressing these issues and more, Chatham House will once again bring together policymakers, business leaders, technologists and finance experts to explore the implications of technological developments at this year’s Illicit Financial Flows conference on 17 October.
To find out more and join this year’s discussions, visit chathamhouse.org/illicit-finance-2019.