Nasdaq Nordic has launched a new machine learning surveillance system for the stock exchange that uses algorithms to help analysts categorise alerts of suspicious activity from Nasdaq’s different trading platforms and to provide managerial oversight into analyst behaviour and decision making. The new system that has been used in production for around four months is the brainchild of Nasdaq SMARTS and the Nasdaq Nordic Market Surveillance team. The exchange hopes it can be put to greater use in the future to weed out market abuse. Joakim Strid, head of European surveillance at Nasdaq Nordic, tells FBNW that the increasingly large sets of data available forms an excellent base for machine learning. He explains that one of the benefits of the new system is that it has enhanced Nasdaq Nordic’s method of quality assurance and manager oversight. “In trade surveillance, analysts take regulatory decisions every minute of the day. Needless to say, we trust the judgment of our analysts but we still need to perform oversight to ensure consistency and accuracy. The machine learning tool creates reports of outliers, where the action taken by an analyst has differed from the predicted one, which is a great complement to random or risk-based reviews,” he explains.
The new surveillance system has a been long time in the making and the team first started developing and testing it in 2016. “We obviously had to proceed with diligence, given that exchange operations in general and surveillance in particular is a highly regulated and sensitive area, so one challenge was that we had to allow the project to take time,” Joakim Strid says. He adds that the production phase has also further pushed the Nasdaq Nordic’s team of surveillance analysts to become more diligent in how events are categorised and actions documented, “in order for the [machine] learning processIf you’re new to Tell Media Group, create an account.
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