A research project in Singapore aims to develop new anti-money laundering (AML) capabilities for the wealth management industry, powered by artificial intelligence (AI) and machine learning.
The technology could help institutions to detect unusual money flows or transactions that might be signs of money laundering, said Nanyang Technological University (NTU).
The team of experts from NTU’s Wealth Management Institute (WMI), School of Computer Science and Engineering (SCSE) and Data Science and Artificial Intelligence Research Centre (DSAIR) is also seeking to create a technological prototype that can facilitate real-time intelligence sharing among institutions.
An expert panel comprising executives from UBS, UOB, DBS Bank and OCBC Bank, as well as the Commercial Affairs Department and the Monetary Authority of Singapore, will offer guidance to the project.
“With new technological advances and paradigms, the tools available to money laundering perpetrators may disrupt the financial institutions’ existing AML mechanisms,” said WMI chief executive Foo Mee Har. “This collaboration with NTU researchers and experts who are at the forefront of advanced AI and machine learning technologies presents a win-win solution for everyone involved.”
UBS managing director and regional head of financial crime prevention in the APAC region, Mabel Ha, added: “Many banks have been applying the same concepts in system-based AML Transaction Monitoring for years, that generate a high number of false positives.
“Within this project we want to seek new and practical ways for wealth management institutions to apply AI and machine learning techniques to achieve superior results.
“With our distinguished panel of experts, the project will have access to deep knowhow of customer and transactional data maintained by banks, and AML risks faced in the banking industry.”
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