Drawing on the databases of Bank of Singapore and parent company Oversea-Chinese Banking Corporation (OCBC), SOWA also cross-checks client information against benchmarks such as salary levels and company revenues, improving accuracy and reducing human error. The automation enhances both efficiency and accuracy, reducing human errors that previously arose from differing levels of experience among relationship managers.
Relationship managers still play a key role in reviewing and refining the AI-generated drafts before submitting them for further assessment under the bank’s anti-money-laundering and counter-terrorism financing controls.
For security, all data processed by SOWA is hosted on the bank’s private cloud, dedicated solely to its operations.
“In an increasingly complex risk landscape, AI can play a pivotal role by automating repetitive tasks like report generation and data validation. Agentic AI pushes the envelope further by enhancing efficiency, accuracy and consistency in decision-making,” says Kam Chin Wong, global head of Financial Crime Compliance at Bank of Singapore.
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He continues: “With AI integrated into the source of wealth reporting process, relationship managers can shift their focus from manual documentation to meaningful client engagement and risk assessment. This not only strengthens client relationships but also maintains high standards of regulatory compliance while delivering greater value.”
The use of agentic AI builds on earlier investments in generative AI and traditional AI by OCBC, which co-developed SOWA with Bank of Singapore.
