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HKEX Deploys Nasdaq SMARTS Machine Learning Technology for Market Surveillance

HKEX Deploys Nasdaq SMARTS Machine Learning Technology for Market Surveillance

Nasdaq Inc. (Nasdaq:NDAQ) has announced that Hong Kong Exchanges and Clearing Limited (HKEX) is the first exchange customer in Asia to successfully deploy Nasdaq SMARTS Market Surveillance’s latest machine learning and participant relationship discovery technology across its equity market, enhancing its capabilities to safeguard market integrity, and better protect investors.

Nasdaq has worked closely with HKEX’s Market Surveillance team in implementing machine learning to analyze unusual trading activities and their subsequent categorization by surveillance analysts. The aim of these algorithms is to predict which actions analysts are likely to take based upon their handling of historical activity as well as discovering new relationships within the data. With new machine learning capabilities, the surveillance functions of HKEX will be strengthened by increased efficiency by focusing on unusual trading activity.

“As a market operator, we have always strived to be at the forefront of embracing and applying emerging technologies that will strengthen the integrity of our markets,” said Garbo Cheung, Managing Director and Head of Market Surveillance and Monitoring, HKEX. “We look forward to continuing our collaboration with the SMARTS team in further building our machine learning capabilities in our market surveillance endeavours.”

“HKEX has been instrumental in contributing to this collaboration and embracing emerging technology to protect market participants,” said Valerie Bannert-Thurner, Senior Vice President and Head of Risk & Surveillance Solutions, Nasdaq. “The evolution of SMARTS is heavily driven through client collaboration and our mutual interest in improving and maintaining market integrity, and we look forward to supporting their continual innovative approach to market surveillance.”

The machine learning capabilities will initially be used to prioritize the surveillance workflow. The technology predicts the likelihood that the event will lead to an action by an analyst. This will particularly help in situations where work load is high, such as during the opening and closing of the markets. The new prioritization ranking is then used to complement traditional quality controls in relation to alert handling, which then enables surveillance officers to identify outliers where the actual handling of alerts has differed from the prediction of the algorithm.

Further, SMARTS has also supplied enhanced trade relationship visualization to complement a suite of market abuse alerts targeting group activity. The new visualizations enhance the efficiency of HKEX to immediately review how participants coordinate trades through multiple accounts for all historical market activity.

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