SteelEye to Monitor Social Media for Trade Reconstruction

Compliance vendor says upcoming automatic trade reconstruction will slash processing times and allow users to monitor news feeds to detect insider trading.

people connecting

Compliance platform SteelEye is currently testing an enhancement to its product with clients: an automated trade reconstruction offering that it aims to launch in the first quarter of 2020.

SteelEye’s Auto-Trade Reconstruction tool is intended to cut the trade reconstruction process down to seconds. It will also introduce a feature that allows clients to monitor suspicious trading volumes, using data from news and Twitter feeds.

SteelEye CEO Matt Smith says that in order to comprehensively investigate potential insider trading activity, firms must be able to monitor news feeds. Currently, the process of trade reconstruction involves studying data points around transactions and looking for unusual activity. “To really get the whole picture, you need to understand what is being said via communications, and you need to understand what’s going on with information that’s publicly available or not publicly available at the time of the transactional event,” he says.  

SteelEye has partnered with financial technology company Selerity, which will offer real-time Twitter feeds and news. The feeds will be aggregated and fed into SteelEye’s platform.    

One scenario in which this feature could be used is when volumes of trading activity in a particular company’s stock increase just before that company releases some positive news. A firm could then raise questions about inside knowledge the trader might have had.

“If somebody did a trade that was suspicious right before a piece of relevant information comes out about the company, where there might be an equity or fixed income traded around, did they know something? Maybe not. But maybe they did. What we do is give you that signal so that you can investigate it,” Smith says.

The platform will also have a machine learning-based tool called The SteelEye that will make suggestions for the user, front-running their questions by delivering the conditions around an event, such as communications related to a trade or trades related to other trades. The user will have the ability to approve or reject suggestions made on the platform. The tool will provide better results as it learns over time.

The tool will monitor news outlets including Twitter, regulated news service and mainstream media sources, as well as specialist financial outlets and central banks.

In recent years, regulatory requirements have put pressure on firms to speed up their trade reconstruction processes. In 2014, provisions in the Dodd-Frank Act came into force in the US that introduced a requirement of 72 hours to reconstruct events around a trade if requested. When Mifid II went live in Europe in 2018, not only did records have to be retrieved in a reasonable timeframe, they needed to be electronic, online and readily available.

Smith says automated trade reconstruction using SteelEye will take only one or two seconds. “And then you have to go through everything and make sure everything’s relevant, [or not relevant],” he says. “You don’t have to go through the process of finding things. It’s more about: OK, is that relevant? Yes or no? And as you’re saying yes or no, it’s automatically tuning it using the machine learning algorithms.”

Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.

To access these options, along with all other subscription benefits, please contact or view our subscription options here:

You are currently unable to copy this content. Please contact to find out more.

FCA declines to directly regulate market data prices

A year-long investigation by the UK regulator to determine whether competition is hindered in the wholesale data markets has concluded with its decision not to directly regulate much-maligned data pricing and licensing structures.

How GenAI could improve T+1 settlement

As well as reducing settlement failures, researchers believe generative AI can provide investment managers with improved research, prioritization, and allocation resources.

You need to sign in to use this feature. If you don’t have a WatersTechnology account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here