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When a large tier-one bank with operations around the world realized that their legacy trade surveillance system not only failed to detect patterns of potential spoofing activity, but also generated too many false positive alerts, their compliance staff knew they needed to make a change. 

This bank, a long-time Trading Technologies client, had already migrated hundreds of users from the legacy X_TRADER® platform and three internal trading platforms to TT®. The TT platform includes a fully integrated solution for trade surveillance and compliance, TT Score. This unique offering leverages machine learning to identify trading behavior, such as spoofing, that may prompt regulatory inquiries. The bank’s desire to bolster their existing legacy parameters-based system with a machine-learning-powered Spoofing model sparked their interest in TT Score.

TT Score’s Spoofing model helps identify various forms of market abuse that involve false or misleading order activity known as spoofing.

The bank’s initial deployment of TT Score was on a large internal trading desk, which was up and running within a week. The initial results were positive, but the team wanted to take a deeper dive into the efficacy of the machine-learning technology. They decided to upload a month of historical trade data for analysis to see if TT Score could accurately identify activity that had drawn regulatory attention—activity that their existing legacy system failed to detect—while also avoiding the generation of too many false positives.

TT Score accurately identified the activity of interest, and also applied “risk scores” for the activity that were in line with the compliance officer’s expectations. Because TT Score was able to identify the “needle in the haystack” without generating a large number of false positive alerts, the bank committed to deploy TT Score at a broader level. 

The Heatmap display allows the user to see which traders or accounts are generating activity that has a high degree of similarity to regulatory cases. The bright red indicates high-risk clusters, and the size of each square indicates the number of clusters.

The TT Onboarding team provided the bank with access to all internal trading activity on approximately a dozen futures markets around the globe on TT Score within one week. The bank now has a customized setup on TT Score where each line of business can have access to TT Score to supervise their own trading activity, then generate periodic compliance reports for that business unit based upon surveillance results. The bank has also leveraged TT Score’s domain experts for user training and interpretation of results.

The bank’s ultimate goal is to streamline their compliance and risk reviews by identifying, prioritizing and addressing higher-risk activity sooner and more efficiently across all internal users and external customers.

To learn more about TT Score and see how it can benefit your operations, contact your TT Customer Success representative or fill out our online inquiry form.