On the back of rising threats to national security from terrorists, which culminated recently in the London and Manchester attacks, the government has moved to disrupt the flow of money that fuels these acts.
New laws mean businesses such as banks, estate agents and accountants will have to carry out ‘stringent and targeted checks” to ensure money is from a legitimate source and is not going to used by terrorists.
Going into more detail, Stephen Barclay, economic secretary to the Treasury, said: “Terrorist financing and money laundering are significant threats to our national security, and we are determined to make the UK a hostile environment for illicit finance.
“These new rules will tighten our defences, protect the integrity of our financial system and help protect the British public from terror attacks and criminal activities.
Evidence has found that serious and organised crime costs the UK around £24bn a year, and future cooperation between the banking sector and law enforcement is key to limiting abuse.
The Treasury highlighted the way in which major UK banks provided 24-hour support to provide “critical financial intelligence” to law enforcement partners as an example of coming together to deal with terrorism and organised crime.
The new regulations will apply to credit and financial institutions, auditors, insolvency practitioners, tax advisers, independent legal professionals, estate agents, high value dealers and casinos.
However, whilst welcoming the government move, anti-money laundering expert Luca Primerano, from Fortytwo Data, said that increased due diligence cannot be relied on to solve illicit money flows once and for all.
“The transactional ecosystems within which criminals and terrorists hide their funds are so complex and vast that, manually, they can be near impossible to identify. The flow of illicit funds is often hidden in plain sight.
“Effective anti-money laundering and combating the financing of terrorism require not just tougher legislation but big data and machine learning-powered tools that can identify transactional patterns a human would never spot.
Primerano also believes that, while lowering the cash payment threshold above which customer identification is required could be a deterrent for some criminals, without the ability to analyse and integrate billions of data points from multiple sources to detect criminal behaviours, this could result in an increased burden of false positives.
