AI Used To Tackle Money Laundering
Banks and financial institutions are experimenting with AI technology to tackle the multi-trillion-pound problem of money laundering, thereby hitting the traditional funding sources of major criminal gangs.
Money laundering is the process of concealing the origins of illegally obtained money by passing it through legitimate business or a sequence of banking transfers.
According to figures from the UN’s Office on Drugs and Crime, money laundering accounts for up to 5% of global GDP – the equivalent of £1.5 trillion per year. In the UK, National Crime Agency figures show that financial crime suspicious activity reports increased by 10% in 2018.
Also, in the UK for example, Companies House and estate agents (setting up new companies and investing in property) have been criticised by the government’s Treasury Committee as being key ways in which money laundering can take place in the UK.
The law in the UK (from 2017) relating to trying to tackle money laundering requires those businesses or sole traders who operate as “high-value dealers” i.e. you / your company accepts or makes high-value cash payments of €10,000 or more (or equivalent in any currency) in exchange for goods, must register with HMRC.
Money Laundering In The News
Some recent high-profile cases of alleged money laundering involving banks include:
- Swiss bank UBS being fined a staggering £3.2 billion for helping wealthy clients based in France to hide money from tax and launder the proceeds (the bank has lodged an appeal).
- In September 2018, Dutch bank ING Groep NV being fined €775 million euros after failing to spot that criminals had been money laundering through its accounts.
- In December 2018, 10 former employees of the local branch of Danske Bank in Estonia being arrested as part of an international investigation into (alleged) money laundering.
How AI Can Help
AI technology is being tested in the fight against money laundering because AI can crunch vast amounts of data (i.e. the data from millions of bank transactions) very quickly and accurately, thereby making it very good at detecting patterns and deviations from patterns. AI can, therefore, quickly detect patterns of unusual activity e.g. behaviour consistent with money laundering (AI also learns with experience), as well as being able to spot smurfing attempts (breaking down a transaction into smaller transactions to avoid being spotted), accounts that are set up remotely by bots rather than humans, and suspicious behaviour by corrupt insiders (known to be an important element in many successful money laundering operations).
What Does This Mean For Your Business?
Money laundering is often used to help organised criminals / criminal gangs continue to finance many kinds of other serious crimes which have a negative impact on society and the economy. It is, therefore, good news for businesses (particularly in the financial and property sectors) that an accurate, and reliable technology-based early detection system, that works independently from human influence and error is being set to work to crack an old problem using the very latest means.
Critics have said, however, that even though AI may be excellent at spotting unusual transaction patterns it will only be as effective as the data it is fed, and banks, financial institutions, governments and law enforcement agencies, therefore, need to share more information to get the best results from AI tools.
Some have also been sceptical of how effective an ‘off-the-shelf’ AI-based money laundering detection tool (of which there are several on the market) could be.