By Mike Coats, CTO, TradingHub
In the analog days of trading, regulators were concerned with finding instances of the good old-fashioned pump and dump, insider trading, or market timing schemes. But digital transformation has reimagined the entire financial system, and while some bad actors have simply digitized legacy forms of market manipulation, most have used technology to originate new, more intricate forms of abuse. For banks, this means that the trade surveillance problem is now more complicated than ever before.
Regulators turn a keen eye to the cross-product problem
As markets have become more complex and interconnected, the potential for illicit activity has expanded. This is especially true when it comes to the opportunity for market manipulation presented by ‘cross-product’ trading patterns – correlated activity that spans multiple asset classes and trading venues, often across both lit and OTC markets. But no matter how complex this trade surveillance problem is, regulators expect market participants to have a handle on it. We can see this message clearly in the large number of enforcements in this space in recent years.
Despite the capital markets industry investing heavily in compliance and surveillance capabilities in the hopes of avoiding regulatory hot water, recent high-profile fines against Bank of America, JPMorgan Chase, NatWest, HSBC, and others, indicate that these efforts are falling short.
So why is cross-product abuse slipping through the gaps of some banks’ preventative systems? And what can be done to safeguard against the huge financial and reputational risks of regulator action?
Operating cross-product and cross-venue
The truth is that the market abuse problem is a web that’s spread across the entire capital markets. Today, virtually every sell-side trading desk makes money by employing cross-product strategies, often laying off risk arising from illiquid client-transactions with benchmark or listed products. Trading floors approach their activity by thinking in terms of ‘market risk’, and as such they trade across a variety of securities, products, and venues to manage that market risk, while calculating the relationships between various assets.
This means that taking a single-venue or single-instrument approach to trade surveillance – which is the default at a lot of banks – is no longer sufficient. These systems aren’t equipped to identify the instances of abuse which present the highest regulatory risk, because they’re not looking at the cross-product picture. Because today’s riskiest forms of market manipulation are happening across various interconnected places that traditional approaches are not capable of spotting, banks are left with costly blind spots.
Surveillance models now need to understand the relationships between instruments so that they can assess pricing impacts to indicate the intent behind any trading pattern. Buying one instrument and selling a related one – albeit elsewhere on the markets – is a position in the spread between the two, not two independent positions, so looking at any transaction independently misses the full picture.
An interconnected web
For example, in fixed income a nefarious trader might use a series of trades in a liquid instrument like government bonds to move the price of a much less liquid instrument like certain over-the-counter (OTC) derivatives. Many fixed income products are interconnected, therefore effective surveillance must consider trading activity in correlated products — such as cash vs. futures, or products with different durations.
Every single bond from government to corporate, and every single product from bond futures to swaptions are expressions of interest rate risk. This means they will manifest significant correlation in their price evolution. These ever-present relationships between different instruments are the very reason that traditional trade surveillance methods have proven inadequate to police such complexity.
What’s more, because trade surveillance approaches are so out of date based on today’s markets, any bank monitoring trades in isolation is now going to be dealing with an onslaught of expensive false alerts. This monopolizes a compliance team’s time, yet the bank will remain incapable of capturing the severe cases of wrongdoing because the cross-product picture is not being accounted for or it’s lost in the pile of false positives.
Rules-based efforts are futile
Traditional trade surveillance systems are using rules based approached to detect instances when a trader is trying to artificially move the price of an instrument to his or her advantage by executing trades or placing and then cancelling orders.
This approach reflects more straightforward equities abuse detection tactics and has resulted in institutions deploying technology platforms that flag every potential instance of manipulation based on lengthy, rules-based taxonomies that can include 60-70 or more categories of market abuse types. The result is an unmanageable deluge of alerts that flag any potential instance of market price movement – which costs millions of dollars just to investigate.
Yet despite most trading desks operating using cross-product strategies today, only one of those 60-70 categories is likely to be a row labeled cross-product abuse. This implies that cross-product abuse is still a rare and niche risk, instead of one of the most common market manipulation strategies that it has become today.
A different surveillance POV: using a trading floor way of thinking
There is no question about it – trade surveillance must adapt. And this adaptation cannot take the shape of simply bolting on additions to chronically unperforming legacy technology. To truly protect against the costly fines and reputational damages of regulatory action, the entire system must be reoriented to reflect how traders actually think, behave, and trade today.
Trade surveillance systems must think in the same way that those on the trading floor do: in terms of risk sensitivities, not rules. A bond and a bond future are basically the same expression of risk, although they might trade in a different way, over a different venue. In both cases, by buying or selling this product a trader is forming an opinion on what’s going to happen to interest rates.
Trades in different instruments are, in most cases, likely to form part of the same abusive strategy, so rather than treat them individually, a surveillance system must intelligently group them together.
Asset classes which require risk-based methodologies like OTC derivatives or fixed income products, are impossible to monitor using traditional surveillance methodology. But thinking in terms of holistic market risk can map how a trader’s positions across a combination of instruments and across a series of maturities are all linked, thereby determining the intent of a behavior and whether manipulation is likely to have occurred.
Market-risk models are able to put the trader’s mindset at the forefront to enable surveillance teams to capture hidden signals that traditional trade surveillance systems are blind to.
This approach not only reduces false positives dramatically, but it enables compliance teams to focus their resources where they really matter to protect against the growing reputational, financial, and legal risks of the most prevalent market manipulation types today.
It’s time to expand the trade surveillance lens
Our industry has built trade surveillance by thinking rules upwards instead of market risk downwards, resulting in the worst kind of complexity.
It’s like trying to spot a shooting star by looking through a keyhole – you’re not likely to see it, because you’re not looking at the whole sky. Now is the time to reimagine the trade surveillance approach so that banks can significantly expand the lens they’re looking through and capture the alerts which genuinely demand their attention.
