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I recently participated in a roundtable discussion on spoofing that became the basis for the JLN Special Report: Chicago Trading Community Faces off in Spoofing Fight.

As defined in the report: “Spoofing is an illegal trading strategy used on electronic markets where a trader enters orders with no intention that they be executed–in fact, with the hope that they not be executed. Spoofing is intended to mislead other traders about the true balance of supply and demand.”

In our discussion, we talked about the fact that even though spoofing is widely viewed as a somewhat vague rule, it continues to be a primary focus of the CFTC and other regulators as evidenced by the fines growing bigger every year. One point that struck me was a comment from an attorney who said that in order to better understand the rule of spoofing, it is very important for market participants and compliance professionals to spend some time looking at spoofing through the eyes of those who enforce and interpret the law.

That’s exactly what we do with our TT Score trade surveillance system. Simply put, we allow our users to “see the activity through the eyes of the regulator,” so that they can more effectively understand the regulatory risk within their organization, and prioritize their workflow accordingly.

How do we accomplish this? Unlike legacy systems that require their users to set (and constantly tune) parameters to identify spoofing activity, we train our machine-learning powered Spoofing model with data from real regulatory cases. These data sets contain patterns of trading activity that we know have drawn regulatory attention in the past.

By taking this machine-learning based approach we are removing the human bias that is inherent in the parameter-setting process, and instead allowing our users to see through the “eyes of the regulator” by mathematically measuring the patterns within their own trading activity against the patterns of trading activity from the regulatory case data that we know have drawn regulatory attention in the past.

While most if not all of us are working from home right now, technology makes it possible for you to see all of TT Score’s models and features in action from the comfort of your home. So schedule an online demo today to learn more, and get a sneak peek at TT Score’s new Collusive Spoofing model as well.