Case study for automated trade surveillance via machine learning. The Challenge > The Trading Compliance team at a large Canadian bank required a solution for automated surveillance of all of their fixed income and foreign exchange trades, in order to allocate more time to investigating suspicious activity > Rapid increases in market and trade complexity, as well as transaction volumes, have rendered manual surveillance processes obsolete > Growing a compliance team of domain and subject matter experts is challenging and costly > Existing trade surveillance systems produce numerous false positives, reducing the time a compliance officer has to analyse suspicious activity > The bank must address these surveillance challenges in order to avoid increased compliance risk and regulatory scrut

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