Trade Surveillance & Compliance
Use TT® Score and leverage machine learning software to identify trading behavior that may prompt regulatory inquiries.
Detect potential high-risk activity using advanced pattern recognition and flag hidden threats well before disaster strikes.
Discover manipulative or disruptive activity before violations happen, preventing fines and enforcement investigations.
Streamline compliance and risk reviews by identifying, prioritizing and addressing higher risk activity sooner and more efficiently.
Find outlier events by understanding historical trends, environmental context and correlation within firm activity.
Instantly Enable for Use with TT
Compliance officers can immediately monitor and evaluate order activity for all traders, and individual users can monitor their own activity.
Surveil Users of Other Platforms
Use FIX Drop Copy to pull order activity from any platform, including X_TRADER®, third-party vendors and proprietary systems, into TT and store it indefinitely.
- Get complete transparency into your firm's compliance risk with TT Score.
- Pattern recognition based on machine learning identifies behaviors that pose the greatest regulatory risk to your firm.
- Trained to recognize high-risk activity from actual regulatory cases and investigations.
- Learns as it becomes exposed to new data to improve accuracy.
- Adapts easily to new infrastructure, data sources and regulatory mandates.
Machine learning technology identifies patterns of behavior that pose the greatest regulatory risk with unparalleled precision.
Cluster and Score
Aggregate order message data into “clusters” of related intent to understand overall trader behavior. TT’s surveillance software automatically generate a “risk score” for each cluster that represents its similarity to patterns that have drawn negative regulatory attention in the past.
Visualize and Investigate
Illustrate the compliance risk of any firm cross-section, including trader, product or sales group. Quickly analyze trader activity and take corrective action where necessary.
Surveillance Model Overviews
Catch multiple types of potentially problematic activity.
Identify various forms of market abuse that involve false or misleading order activity known as spoofing.
Abusive Messaging Detection
Spot patterns of disruptive or excessive order activity.
Momentum Ignition Detection
Pinpoint behavior designed to initiate rapid market movement at the expense of other participants.
Identify spoofing patterns generated by multiple trader IDs to flag possible collusion.
Pinging and Phishing Detection
Detect activity designed to take advantage of hidden volume at the expense of slower market participants.
Wash Trade Detection
Identify executions with no change in beneficial ownership.
Cross Trade Detection
Expose potential cross trades without sufficient delay between order entries.
Marking the Close
Detect potential settlement price manipulation in outrights and spreads, and identify on-exchange activity that may have influenced the settlement price.
Influencing the Open
Detect indirect wash trades that occur before open trading in violation of exchange rules. Identify potential manipulation of the indicative open price during the pre-open period.
Detect an outlier point in time where significant changes in volume and price occur, then determine if a trader benefited from the outlier event earlier and/or later in the trading session.
Analyze trading behavior that creates artificial price movement in a single direction with aggressive orders.
Dominance at Open
Analyze and score clusters that may indicate that a single trader is dominating the total traded volume for an instrument during the market open.
Dominance at Close
Analyze and score clusters that may indicate that a single trader is dominating the total traded volume for an instrument during the market close.
Order Book Dominance
Analyze and score clusters that may indicate that a single trader is dominating the total traded volume for an instrument during a session.
Single-Sided Order Book Dominance
Analyze and score clusters that may indicate that a single trader is dominating the total traded volume for either the buy or sell side of an instrument during a session.
Analyze and score clusters that may indicate that a single trader is dominating the majority of the bid/ask volume of an instrument at different times during a trading session.
Detect trading activity intended to maintain the price of an instrument during the trading session.
Roundtrip Wash Trading
Identify behavior where a a trader buys or sells an instrument then shortly reverses out of that position at the same price to generate artificial volume.
Identify whether block trades are submitted within a specific time frame from execution (i.e., consummation time).
Learn how clients are using TT Score and why they choose us as their preferred business partner.
Trade Talk Blog
Banking on TT: Why One Global Financial Institution Switched to TT® Score for Trade Surveillance and Compliance
6 Real-World Examples of How TT® Score Solves Trade Surveillance And Compliance Challenges