The Monetary Authority of Singapore (MAS) has intensified its supervision efforts on financial institutions to stamp out money laundering and terrorism financing, but more could still be done, its assistant managing director Chua Kim Leng said yesterday.
Mr Chua told a financial crime seminar organised by the Association of Banks in Singapore that stepping up such efforts is ever more important today as criminals are constantly finding more creative ways to launder money, finance terrorism, or engage in fraud or insider trading.
Technology can help, he added, noting that the MAS is working closely with banks here that are building a joint utility for Know Your Customer processes.
The utility could "free up resources and allow banks to focus on the more complex aspects of customer due diligence and monitoring, including monitoring and investigating unusual and suspicious transactions", he said.
"A well-designed and executed utility can also offer efficiencies of scale and reduce the need for customers to provide the same information to multiple institutions."
One way that criminals get their funds into the financial system is by abusing offshore companies and investment funds.
"A small number of individuals may use trust and company service providers to set up a large number of corporate structures in multiple countries. Many of these are shell companies with no apparent economic purpose," Mr Chua said.
These companies and investment funds open numerous bank accounts in different jurisdictions, then move large sums of money back and forth among themselves.
This can disguise the origin and ultimate destination of the money, as well as the true beneficiaries and purpose of these transactions.
And so, banks need to know their customers well and be alert to inconsistent patterns, behaviours and transactions, he said.
He noted that there is also room for improvement in transactions monitoring, and here too, technology can help. Current systems largely flag transactions based on preset rules, thresholds and scenarios, which generate a high rate of false positives. These alerts require extensive human effort to review. He said: "This is where better use of technology can help.
"The next generation of surveillance systems utilise sophisticated techniques such as machine learning, which can help identify unusual patterns of transactions across a network of entities and across time."