Singapore, which is increasingly using technology to combat money laundering and terrorism financing, faces a shortage of skilled data analysts who can help banks track down illicit cash flows.
The skills gap could be addressed by importing foreign talent and training locals, according to a report released last week by a partnership of banks, the financial regulator and police. Lenders in Singapore have been looking at using data analytics to detect suspicious transactions because current systems yield too many false alerts and manual processes are vulnerable to human error, it found.
“On a national level, the relevant talent pool in Singapore needs to be grown significantly to meet this demand,” the report said. “This can be achieved through the importing of talent from outside Singapore as well as through the ‘upskilling’ of Singapore’s existing workforce.”
Singapore is stepping up efforts to tackle white-collar crime as it seeks to build on its status as one of Asia’s biggest financial centers. High-profile cases such as the 1MDB embezzlement scandal are increasingly involving large networks of sophisticated cross-
border fund transfers, underscoring the challenge for banks and regulators dealing with thousands of dubious transactions each year.
The Singapore government has recently signaled that it’s willing to ease some restrictions on importing labor for the financial-technology industry and other sectors where it’s facing talent shortages. The city-state tightened its immigration policy following 2011 elections, when residents voiced worries that an influx of foreign workers in the past decade had strained services, driven up competition for real estate and threatened jobs.
The Monetary Authority of Singapore “strongly encourages the use of data analytics” in anti-money laundering and countering the financing of terrorism, said Ho Hern Shin, assistant managing director, banking and insurance, at MAS. It “has the potential for bringing about transformative change in our approach to combating financial crime,” she said.
Singapore’s three major banks – DBS Group Holdings Ltd., Oversea-Chinese Banking Corp. and United Overseas Bank Ltd. – have started using artificial intelligence and data analytics to help enhance their detection of illicit flows. According to the report, one bank reported a 50 percent to 60 percent reduction in so-called false positives in a test that used AI.
“Any option that improves detection yield from the current situation – where often, nine out of 10 cases is a false positive – should be explored,” said Lam Chee Kin, DBS’s head of legal, compliance and secretariat. “While we are in early days and making marginal improvements, there is promise,” said Lam, who also heads the data analytics working group that wrote the report.
The working group was set up by a government-industry partnership aimed at fighting money laundering and terrorism financing. Formed last year, the partnership includes banks and is co-chaired by the Monetary Authority of Singapore and the Commercial Affairs Department, the white-collar crime unit of the nation’s police force. Chanyaporn Chanjaroen, Bloomberg