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Nasdaq launches machine learning tech for Nordic Markets surveillance

First Published 7th September 2017

Nasdaq's SMARTS and Nasdaq Nordic deploy machine learning capabilities to analyze abnormal market events and improve alerting processes surrounding market abuse detection

Stockholm - Nasdaq has deployed machine learning technology across its entire Nasdaq Nordic markets-Stockholm, Copenhagen, Helsinki, and Iceland to bolster its market surveillance efforts.

Nasdaq's SMARTS, in collaboration with the Nasdaq Nordic Market Surveillance team, has implemented machine learning within its surveillance technology to analyze abnormal market events and their subsequent categorization by surveillance analysts across the Nordic markets. 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 discover new relationships within the data-thereby strengthening Nasdaq Nordic's surveillance mechanism to detect market abuse. The next stage will be to integrate machine learning technology into the SMARTS offering for exchange and regulator clients worldwide.

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. Lastly, the existing alert designs will be evaluated based upon new relationships or rules revealed by the machine learning technology and redesigned and improved accordingly.

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