United Overseas Bank (UOB) today announced it has collaborated with Intel to successfully test how federated advanced data analytics can enhance cross-border anti-money laundering (AML) efforts.
The joint project between UOB and Intel set out to use a combination of leading technology and advanced data analytics to provide greater clarity about the extent of transactions made across countries and entities by a single client. As cross-border transaction data sit in multiple localities, maintaining data sovereignty and determining the risk of money laundering across geographies can be difficult and complex.
UOB is the first in the world to pilot federated analytics using Intel® Xeon® Scalable processors with Intel® Trusted Execution Technology (Intel® TXT) and advanced analytics for cross-border AML efforts.
UOB and Intel explored a federated analytics model to enable financial institutions to have an expanded view of a customer’s banking activities across borders without breaching customers’ privacy and data protection regulations. A federated analytics model enables this as it facilitates the sharing of algorithms across different geographical data sites without the need to share data. These algorithms are designed to draw out specific insights, indicators and patterns to identify money laundering activities within the global banking system.
For the project, UOB created scenarios and corresponding datasets to simulate transactions by a customer with bank accounts in Singapore and Thailand. The Monetary Authority of Singapore (MAS) and the Bank of Thailand were independent observers of the project.
Mr Richard Lowe, Chief Data Officer, UOB, said, “With the proliferation of data and next-generation technology, banks and financial institutions can apply innovative advanced data analytics solutions to enhance their processes and capabilities. This is why UOB is the first ASEAN bank to establish an enterprise-wide centralised big data analytics centre to test and to implement quickly data-centric and data-driven projects. The success of our federated analytics project with Intel to analyse and to identify cross-border money laundering risks is one such example of how we can improve AML processes and deter fraudulent activities within the global banking system.”
Ms Lisa Davis, vice president of Intel’s Data Center Group and General Manager of Digital Transformation and Scale Solutions said, “The collaboration between Intel and UOB uses Intel-based advanced federated analytics technology to deliver analytics and AI in new ways to address business challenges such as AML. The successful test based on the Intel data exchange concept demonstrated how banks could manage data analytic across country boundaries while complying with data sovereignty. We look forward to continuing to work with our ecosystem partners and the industry to implement and deliver federated analytics at scale.”
The project was co-funded by the MAS’ Artificial Intelligence and Data Analytics (AIDA) Grant under the Financial Sector Technology and Innovation Scheme. The AIDA Grant was launched at the Singapore FinTech Festival in 2017 to encourage the use of artificial intelligence and data analytics among financial institutions.