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HSBC uses AI and machine learning to fight anomalous, suspicious transaction
Last update: 06/11/2019

Exclusive report by Zulfazlin Baharuddin

KUALA LUMPUR, Nov 6 -- Global banking giant, HSBC has been able to deal promptly with any anomalous or suspicious transaction through the adoption of new technologies namely Artificial Intelligence (AI) and machine learning.

Regional Head, Financial Crime Threat Mitigation, HSBC Hong Kong, Paul Jevtovic said with the application of new technologies HSBC has managed to enhance the efficiency of the financial institution, especially when facing significant threats to the bank.

"We have 608 million transactions every month. Hence, with AI and machine learning we are able to identify a good transaction done by an innocent person versus transaction conducted by criminals,” he told Bernama at the sidelines of the International Conference of Financial Crime and Terrorism Financing (IFCTF 2019) here today.

Facing a huge amount of transactions,  AI and machine learning technologies adopted by the bank avoid mistakes committed by people, he said.

In addition to that,  technology ensure the bank operates in a more effective way as well as being efficient in preventive controls.

Machine learning is an application of AI that provides the ability to automatically learn and improve from experience without being explicitly programmed. 

Jevtovic said HSBC is committed to working with regulators and relevant authorities to combat financial crimes and in protecting valuable customers data.

"Our shared objective is to develop our capabilities to make it much harder for criminal to use the financial sector,” he said.

He also commended Bank Negara Malaysia for their good leadership in fighting financial crimes, adding that HSBC as an international bank operating in Malaysia supports the central bank in combatting money laundering and terrorism financing.

“I have personally been involved with Bank Negara Malaysia and I think they are a very positive and forward-thinking regulator,” he added.

-- BERNAMA

 


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