TT Score is a trade surveillance tool that uses pattern recognition based on machine learning to identify trading behaviors that pose the greatest regulatory risk to your firm. It scores all activity based on similarity to actual regulatory cases such that compliance officers can identify risk, prioritize work and address problematic trading behavior. TT Score is an integrated component of the TT platform that requires no implementation or integration and can simply be activated from within Setup.
TT Score features a number of data visualizations and filters to assist in the review and evaluation of trading activity and provides the ability to record dispositions.
TT Score uses the following models to analyze data for problematic trading patterns:
- Abusive Messaging: Quote stuffing schemes designed to introduce predictable latency into an exchange's quoting engine or malfunctioning algorithms that might cause market disruptions.
- Cross Trading: A cross trade occurs when a buy order and a sell order for the same instrument are entered for different accounts under the same management, such as a broker or portfolio manager.
- Momentum Ignition: Behaviors that indicate an attempt to create an artificial price movement with aggressive orders followed by an attempt to capitalize on such movement.
- Pinging: The entry of multiple small orders intended to discover hidden book depth followed by a series of order actions designed to force the large order to trade at less desirable prices.
- Spoofing: Patterns of manipulative or disruptive trading activity that involve the placement of a number of orders for which a trader has no intention of executing in an attempt to move the market.
- Wash Account: The same account ID is both the buyer and seller in the same transaction.
- Wash Trader: The same trader ID is both the buyer and seller in the same transaction.