September 2014: Change Is the Only Constant

victor-anderson-portrait
Victor Anderson, editor-in-chief, Waters

Machine learning and artificial intelligences are reshaping algorithms into adaptive programs that can adjust on the fly, which Victor says could end up all but eradicating losses.

I’m now into my 14th year of covering the financial services technology industry. A lot of change has come about during that time: We have seen financial institutions and technology firms come and go; a staggeringly large number of jobs—both technology related and revenue generating—have simply disappeared, primarily in the wake of the global financial crisis; and we’ve witnessed the introduction of an unprecedented amount of regulation, refining and bolstering the market structure and governing the way market participants are required to conduct themselves if they want to be part of this ever-changing industry. Whether all that change is a good or a bad thing is a moot point—it has come about for a variety of reasons, and the only constant we can be sure of is that there is a whole lot more change coming down the pike. 

It doesn’t take a futurist to predict that technology will play a pivotal role and touch almost every business process of every capital markets firm at some point. The logical conclusion is that capital markets firms will turn to machines to manage every conceivable aspect of their day-to-day business, while humans, like airline pilots, will be on hand to take care of emergencies, take-offs and landings. Thankfully that time is still a long way off, but as James Rundle’s feature illustrates, more than a smattering of firms have adopted machine learning, underpinned by various artificial intelligence (AI) technologies, to varying degrees. The gist of the feature deals with the development of a new generation of algorithms, specifically designed to learn from past “experience” and crucially amend their “decision-making processes,” ensuring that in the event that similar scenarios arise, the most advantageous action is automatically taken.

One of the drawbacks associated with “dumb” first-generation algorithms is their relatively short lifespan—generally two to three weeks—requiring their various parameters to be tweaked in order for them to remain relevant to the market in which they operate. In contrast, algorithms possessing AI are able to adjust themselves on the fly, based on their market observations and interactions, thus ensuring that they’re constantly at the top of their game. This really is the era of “set and forget.”

An added benefit offered by AI-enabled algorithms is their ability to be assigned to various roles within the firm. For example, some might have execution tasks while other might be assigned, say, monitoring remits, specifically looking to identify instances of market abuse or where execution algorithms are acting “strangely.” Given their ability to monitor extraordinarily large numbers of activities on a near-real-time basis, this would mean that potentially loss-making instances could be all but eradicated. And that can only be a good thing.

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