In looking at compliance officers (from the buy side, sell side, exchanges, and regulators) I saw only one person with a background in data science, machine learning, decision science, statistics or other data analysis discipline.
Granted, my search was wholly unscientific. My college professors in Decision Science at Indiana University would give me poor grades. I simply looked through the background of three dozen LinkedIn compliance officers in my own personal network.
Backgrounds observed in my research showed people who entered compliance with either an educational or professional background in the following:
• Project Management
Of all the compliance professionals I surveyed only one had an educational background in Decision Science. And she is no longer working in compliance.
In the past decade High Frequency Trading, Low Latency Trading, and Algorithmic Trading have taken off. New ways of market manipulation including Spoofing, Pinging, Quote Stuffing, and others have caused the need for compliance to get more and more involved
in data analysis.
Compliance officers have moved from looking at a few tickets to find instances of infringements to needing to look at whole patterns. Modernizing trade surveillance requires divining proof of trader intent. Compliance needs to be able to form a hypothesis;
"This trader intended to manipulate the market." Once the hypothesis is formed they must apply new skills, and new tools, to determine if the hypothesis can be proved within the order audit trail and in the corresponding market data.
One reason that I am excited to be back on the vendor side is to bring skills and tools, like machine Learning, data science, and structured statistical analysis, back into the industry. Our regulated markets should be fair and orderly.
Traders, with very little technology are able to manipulate the market. This was proven when the CFTC went after Navinder Singh Sarao. He was using a trading station and some programming using an API provided by the trading station vendor.
Compliance officers must have the skills to see data patterns, trade clusters, and market data that point them into better hypotheses and better decision making about the intent, and the effect of their traders.