This is an extract from FCN’s Global Threat Assessment, coming soon, which can now be pre ordered by contacting Financial Crime News. It is also featured in FCN Issue 3 which is freely available at the end of September, 2019.
In providing guidance in 2018, FATF described Securities Markets as “characterised by complexity, internationality, a high level of interaction, high volumes, speed and anonymity,” and that , “some of the same characteristics associated with the sector can create opportunities for criminals.”
In 2017 the UK’s National Risk Assessment (NRA) highlighted Securities Based ML as “a significant emerging risk,” relevant as the UK is one of the world’s largest financial centres, and home to large Securities Markets.
The realisation that an intelligence gap in the understanding and usage of Securities Based ML was evident came in 2017, with the handing out of the UK’s largest AML related fine to a major European Bank.
The Bank’s Moscow based customer was able to convert at least US$6 billion worth of Roubles into US$ using the equity markets, buying and selling major publicly traded Russian stocks, using a technique called “mirror trading.”
This typology involves simultaneous, buy and sell orders of the same securities that are settled in different currencies by customers that are linked by common owners and or controllers. This enabled Russian funds to be transferred offshore, converted from Roubles to US$ and deposited into bank accounts in countries such as Cyprus, Estonia and Latvia.
Whilst Securities Markets have long been used by criminals, for example committing crimes such as insider dealing and market manipulation, the use of Securities Markets to launder money has been under appreciated.
According to the NRA, “capital markets have relatively weak compliance controls & low levels of suspicious transactions reporting,” & FATF describes a lack of AML awareness, and only a limited number of ‘securities-specific indicators and case studies.” The UK FCA published the outcome of its thematic review on ML in capital markets in June 2019.
The Report did not attempt to provide an estimate of the size and scale of ML in or through the Securities Markets, as no empirical information exists, instead typologies that indicated potential suspicious activity and findings directed at FI’s participating in the Securities Market, that:
- some market participants needed to be more aware of ML risks… and needed to do more to fully understand their exposure
- effective customer risk assessment and due diligence are key to reducing ML opportunities, and
- controls could be improved, including with transaction monitoring (TM)
Even more recently the EU, in the 2019 Supranational Risk Assessment identified 47 products and services that it regards as both TF and ML threats and the extent to which controls and responses address the residual vulnerability. Using a rating system of 1-4, (4 being the highest) Securities Markets (Institutional Banking & Institutional Broking) are rated for ML purposes at a “threat” level of 3 with a “vulnerability” rating of between 2-3 and 3 respectively).
Current Challenges:
Knowledge gaps around money laundering through securities markets is starting to raise concerns, particularly as a result of recent schemes uncovered at a number of major European banks, where Securities Markets have also been used as well as the more traditional cash markets in particular to disguise suspected outflows from, for example, Russia.
Not surprisingly, FI’s with Securities businesses, will be asking whether their current understanding of the risks is up to date and whether controls are sufficient to mitigate the money laundering risk. Risk may be being overlooked, because the Securities Markets are rarely used in the placement stage of ML and is more likely therefore carried out via the integration stage and consequently more difficult to spot.
By relying on traditional transaction monitoring systems, many FI’s have found extremely high alert volumes and false positive rates, often as high as 99 percent, with many questioning their relevance and usefulness.
Another challenge is Data, which can present significant problems to enable a full and accurate picture of a customers activities, across numerous booking locations, with different systems being used. Even when data is available, it often requires a lot of work to collect, structure and organise to normalise it, so it is useful for monitoring or investigations.
A further challenge is People, where Investigators who are unused to the particularities of the Securities Markets have difficulty in conducting thorough investigations.
Recommended Actions:
FATF stressed the need for securities firms to pursue a “group-level approach” to adequately mitigate ML and TF risks and to avoid a “one-size-fits-all approach” to controls. The FCA are encouraging FI’s to raise awareness of this risk, ensure customer risk assessments are appropriate and consider moving beyond existing TM approaches.
The FCA is encouraging technology innovation in this area in the belief that next generation technology can provide additional context to identify those FI customers of increased concern, and potentially problematic transactions or relationships. FI’s that leverage these solutions, will be better enabled to identify new or emerging risks, more precisely model customer risk and Identify relevant ML typologies. By better monitoring customer activity and relationships, FI’s can focus their resources on increased risk areas and move away from a coverage model that is highly inefficient.
In time FI’s will want to move away from transaction monitoring to entity surveillance, and entity resolution tools and network analysis are tools that will play a large part in this transition, as FI’s seek to build a more complete picture of the customer’s relationships across the institution, not least in order to detect potential suspicious activity. Finally FI’s may need to re train or invest more in educating investigators.
As new systems and tools are introduced, a check the box approach to closing and escalating investigations is unlikely to be productive. Since the products involved are so complex and highly nuanced, investigators will need to firmly understand the products and services offered and the activities of customers, to be able to both use the new tools effectively and to make reasonable risk decisions.
Good insights, coming collaboration in between FI with AI is a must and unable to avoid, still people ethics and risk awareness has to be raised as well.