Most financial institutions have some form of trade surveillance: a complex set of processes that monitor buy- and- sell-side operations or, alternatively, specialized trading venues put in place to prevent fraud. However, very few of these types of solutions are proving effective for today’s organizations. They are not helping to quickly meet ever-changing industry requirements. And on average, organizations are looking at a potential multi-million dollar financial impact if they don’t have effective trade surveillance.
By including machine learning in your trade surveillance solution, you have the chance to reduce false positives, bring real-time surveillance, and integrate real-time and past data for better contextual understanding. You will be able to broaden scope to catch more breaches and gain more control over investigations with case management tools. Plus, you can apply these results to market risk analysis and payment surveillance.
Download this whitepaper to learn more about how you can implement machine learning in the financial services industry to drive better services and a superior customer experience.