Introduction to Trade Surveillance and Monitoring

Artificial Intelligence, Machine Learning, Trade Surveillance and Monitoring, Banking Services, Pre-Trading, Post-Trading Processing, Market Surveillance, Data Privacy
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Greed is good, says the not-so-great Gordon Gekko in Oliver Stone’s securities saga ‘Wall Street’. However, the numbers of those inspiring the likes of Gekko, and those being inspired by him, continue to rise. This is a key difference between securities market and the rest of the financial sector. All financial sectors are motivated by profits, while greed remains the mainstay of the securities market. While big scams and rogue trades end up hurting the small investor the most, the financial institutions and their top brass can also suffer severe consequences. While reputed firms like Bear Stearns got dissolved during the 2008 subprime crisis, JPMorgan Chase lost more than $3 billion due to rogue trading in 2012-13. Various department heads resigned, and CEO Jamie Dimon’s pay for 2012 was cut in half.

What is trade surveillance?

Market regulators are aggressively fighting the malpractices. They have several arrows in their quiver to combat this ever-present menace of securities fraud. A key arrow is trade surveillance.

Trade surveillance is a software that monitors the securities markets to check for illegal activities like market manipulation, suspicious trading patterns and fraud. The software monitors entire market and covers all asset classes, securities, as well as regions. It scans the gathered data for potential anomalies like misuse, abuse, manipulation, and fraud. The alerts go through another quality check, and suspicious activities are reported to the concerned authorities for further action. 

Here, some of us may be unfamiliar with the term ‘asset class’. Asset class is essentially a collection of securities having a similar financial structure. These include stocks, bonds, money, and future derivatives.

In simpler words, Trade surveillance tools may save organizations from serious consequences such as legal challenges, criminal prosecution, and even closure of an organization.

Areas under watch by the software

The software also covers pre-trading, post-trading, and market surveillance.

Pre-trading is share trading before the markets regular trading hours. Pre-trading offers the investors the opportunity to react to adverse events which can affect the market adversely. Such events include corporate misfortune, late news about changes in regulations, and overseas political turmoil. It is also used by less knowledgeable investors. Indeed, market veterans refer to pre-trade as ‘amateur hour’.

Post-trade processing is the next area keenly watched by the trade surveillance tools. As its name suggests, post-trade processing is the processing taking place after a share trade. Trades are usually a speedy affair, and traders often use phones to assist in speedy transactions. This process can introduce errors in the overall process, which may turn out costly later. Post-trading avoids these mistakes to enable safe exchange of commodities between the buyer and the seller. These processes include clearing and settlement. The investor becomes a shareholder after settlement.

Market surveillance means stopping and investigating manipulative and illegal activities in the securities markets. The software monitors trading activities across various markets and asset classes. Curbing market malpractices also helps in saving organizations from the possible losses and penalties resulting from such activities. The software also helps ensure regulatory compliance.

How does it catch the bad guys?

It scans the market activity in real-time. The software can integrate with a lot of external sources like trading data, voice and electronic communications, and a lot of third-party sources. The software scans various sources such as order books, which contain all information about trades in a specific exchange, trails of various audits, and trades from various assets and markets. The software gathers the data and analyzes it to detect anomalies and alert the concerned authorities.

The data analysis is now made easier and faster due to advent of newer technologies like Artificial Intelligence and Machine Learning (AI-ML). This is especially important as like many systems, trade surveillance systems also generate a lot of false positives. The large volume of data can be a tiresome task and carries the risk of failure to spot suspicious activities and emerging threats. Also, enforcing AI-ML helps the regulators go to offensive from defensive. The technology allows organizations to enforce advanced data mining techniques and unsupervised machine learning to help pinpoint risk indicators.


However, the technology also has limitations. The first and the biggest obstacle remains human ingenuity, or greed, depending upon the point of view. Activities like insider trading and market manipulation persist despite aggressive efforts by market regulators. Sadly, risk to reputation does not always matter to some when the gains are large enough.

Also, some security exchanges are not accessible for the small investors. These exchanges are colloquially called as ‘dark pools’ due to their complete lack of transparency. Dark pools are now becoming more popular as investors can discreetly trade in large quantities of shares and still stand to gain more than a similar sale in an open market. However, the lack of transparency can often lead to abuse or conflicts of interest. The opacity can also lead to predatory trading.

Another big hurdle is the increasing complexity in the market. Overall market activities have risen manyfold, and now there are multiple new digital communication methods like WhatsApp. This, coupled with the ‘human ingenuity’ mentioned above, means the software cannot always keep track with the market. That is also the reason newer software is equipped with always-increasing capabilities for integration with more sources.

Organizations themselves put a big block in the form of knee-jerk reactions to regulations. The new piece of software is haphazardly fitted with the previous legacy software. This also results in separate systems for separate processes and asset classes. This siloed approach not only makes monitoring hard, it also makes it more complex. Each system in this setup comes with its own security alerts and separate monitoring systems for threats. Such highly fragmented system setup limits the software’s ability to spot malpractices and noncompliance, which will prove costly.

Another block is the increasing concerns about privacy. Regulators are expected to keep extensive records of transactions and related communications. However, data privacy is first and foremost in many new regulations. Striking a balance between compliance and data privacy is making the regulators’ job harder.

Despite all the shortfalls, trade surveillance is a desperately needed tool. We will explore various aspects of the software and its impact in the coming chapters.

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