Guest comment by Ben Parker
Two trends are currently challenging how firms approach trade surveillance: AI and complex cross-border regulations.
The rise of AI is transforming the trading landscape. It is fuelling massive advances in data-driven trading, but it also has a darker potential to not only execute illegal financial trades, but cover them up. The problem is that AI and traders don’t need to operate within borders. And currently, regulations do. New research has revealed that three quarters of compliance managers believe cross-border regulatory challenges are an issue for their organisations.
Borderless markets require borderless surveillance. Yet conducting trade surveillance across borders and addressing issues like cross-market spoofing presents several challenges.
Regulatory frameworks can vary between regions in terms of market structure, trading practices, and surveillance mechanisms. Traders can therefore exploit loopholes and move activities across jurisdictions with varying levels of oversight and enforcement. Moreover, financial markets use various trading platforms and technologies that may differ across borders. This can complicate the integration of surveillance systems to monitor activities seamlessly and successfully.
So, why do we need borderless surveillance? And how can we achieve it?
Trading is more complex than ever. There are more players involved across a wider scope of markets and products/assets, with myriad fintechs, crypto, social media platforms and regulatory jurisdictions adding complexity to trading tactics and increasing the chance of market abuse. With so many interactions happening simultaneously, effectively monitoring and regulating cross-border market activities is a real challenge.
A variety of frameworks play into the hands of market abusers. Traders can capitalise on regulatory arbitrage to execute trades in a domain that suits their purposes
From the diversification of trading platforms to social media’s ever-growing reach, the global financial landscape is becoming increasingly interconnected and digitised. This is altering the flow of market dynamics, presenting bad actors with a host of new opportunities for market abuse; this means that they can potentially exploit regulatory gaps that sit beyond the remit of traditional surveillance and regulations.
So, when it comes to regulatory efforts, a variety of frameworks play into the hands of market abusers. Traders can capitalise on regulatory arbitrage to execute trades in a domain that suits their purposes, using different digital tools to mask their activity and target areas with less risk and little enforcement. With regards to surveillance, differences in the infrastructure, trading protocols and data formats of trading markets make integrating surveillance systems that much harder.
New landscapes: connectivity is an irreversible path
This is already a lot to consider, and we haven’t even mentioned AI’s role yet. With the growing use of AI in trading, it can be increasingly difficult for regulators to identify whether a trade is legitimate or not. AI empowers traders with new ways to perform insider trading, and the variability created around the authenticity of trades is perfectly suited for illicit activity.
Not only does AI create this direct risk, but it also amplifies the risk of bias and misinformation and allows those with little trading knowledge to use its capabilities to execute trades, adding to the challenges of growing interconnectivity and more individuals participating in trades.
The path towards ever-more connectivity is irreversible – the modern world will depend on it more and more. In this world, regulators are not only dealing with a lack of visibility of market abuse, but also in their knowledge of what firms are doing about it. This is leading them to up their expectations around how firms explain their controls. So, new initiatives are badly needed to align regulators and modernise institutions.
In an effort to amplify transparency around market abuse, regulators are fostering collaborative partnerships with national authorities, enforcement agencies and private companies. These cooperative networks are a key tool in moving to an intelligence-driven approach in identifying market abuse and capitalising on the overlap of objectives between regulators and the private sector.
Both the FCA and the IOSCO have highlighted the importance of these ‘partnerships’ between regulatory bodies and market players to combat risks to market integrity and limit regulatory arbitrage. And in a sign of looking to address the issue globally, not just domestically, the SEC is looking to streamline regulation beyond its jurisdiction (the US). This includes providing clarity on cross-border regulatory scope, addressing regulatory arbitrage across jurisdictions, and removing duplicative regulation.
This push is alongside an industry shift to focus on asset classes that, in the past, have merited less attention for market abuse, such as non-equity asset classes.
Despite the need for greater uniformity in cross-border regulation, when it comes to firms monitoring market abuse, market interconnectivity does not equate to taking a homogenous approach. Regulators have made it clear that a one-size-fits-all approach is not acceptable. It’s not just necessary for firms to have automated surveillance controls, but specific and targeted surveillance tools – each abuse check needs to be tailored for its market and product. Why has this shift emerged?
Traditional surveillance methods are insufficient in the digitised cross-border trading market that has emerged – and one that now has AI executing trades. In order to keep up with a rapidly evolving trading landscape, regulators are looking to AI and regulatory technology (RegTech) to better monitor market abuse. Through encouraging the wider use of surveillance technology, which has the ability to identify market abuse scenarios by asset class, they can match the sophistication shown by criminals that are executing trades. This sets a new standard for the industry – but for firms, it also brings a new, weighty expectation with it.
RegTech platforms can use AI to learn subtle patterns of market abuse and increase the precision of identifying and risk-scoring transactions. It’s a demonstration of using AI to fight AI
In order to stay compliant, firms need to adapt to market challenges and regulatory expectations quickly. The use of technology has not just become an expectation from regulators, but an essential step to stay compliant and manage market threats effectively. If some firms have tech and others don’t, or if they are working off systems of widely differentiating sophistication, the perpetrators of market abuse can profit. As a minimum, coherent adoption of RegTech can create an efficient and streamlined reporting process that stands up to scrutiny.
But if firms want to go a step further and embed AI into their systems, they can vastly improve their existing capabilities. For example, RegTech platforms can use AI to learn subtle patterns of market abuse and increase the precision of identifying and risk-scoring transactions. It’s a demonstration of using AI to fight AI.
The current regulatory landscape is stuck behind the rapidly evolving trading market: AI and traders have the luxury of working across borders, whereas regulators and firms are bound by differing and complex regulatory frameworks. So, first and foremost, all parties involved in market surveillance need to foster cross-border collaboration to successfully monitor a congested and interconnected trading market that is prone to abuse.
But even with this approach being adopted by regulators, it’s near impossible to fight AI- and tech-fuelled market abuse without the use of RegTech (and AI). Borderless markets require borderless surveillance. And regulatory technology will have a vital role to play.
Ben Parker is CEO at eflow Global
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