Automation and the human factor
The relevance of humans in a future where computers will handle monotonous and repetitive tasks has always been on the periphery of the AI conversation, so how can humans adapt in financial services to avoid a severance package?
The key word in all of this is automation, something that humans aren’t suited to and have repeatedly lost out to since the first industrial revolution. The AI argument and use of robotics are intrinsically linked to automation, and there are numerous instances where it should be implemented.
“Robotics and AI mean different things to different people, but the key is automation,” says OpenLink’s O’Toole. “You’ve got a lot of people pulling levers, pushing buttons and spending an inordinate amount of time reconciling databases or spreadsheets when there are already technologies that can take over that work. Automation will allow corporates to better focus on the task at hand, and start to use their heads a bit more when it comes to thinking of the future and what they should be looking at.”
One thing that humans must do to remain relevant is recognise the computer’s function: what it’s doing, why it’s doing it, and the impact it’s having. In doing this, humans move up the value chain to do something that – for now – the machines cannot do themselves.
“Computers are better than humans at processing statistical information, so humans stay relevant by learning how to work with the machines, and how to communicate what the machine is doing to managers who need to know,” explains Portware’s Waelbroeck. “Working with machines is not just using them ‘as is’, but using them to turn ideas into processes: intuition is a valuable trait when it can be turned into a quantitative model.”
There is no getting away from the fact that the fight against automation is one that people will not win, so the real fight is the one to stay relevant in an industry where there will be inevitably fewer jobs.
A vital part of this for people is adapting to new responsibilities and learning new skills in order to keep up and be able to work effectively with their machine counterparts. David Landi, Global Head of Financial Services at The Smart Cube, explains: “Automation through AI tools will definitely have an impact on the number of jobs for research analysts and traders. For instance, an increasing percentage of hedge fund trading is now being performed using automated trading rather than human traders.”
Continuing, Landi highlights some of the skills that people will have to develop to stay relevant once mass automation takes hold of the industry, and how job roles will change rather than disappear: “AI isn’t going to wipe out the jobs of analysts or traders, but their roles may change in the process, and therefore, the skills they would need to possess to grow in this market space will need to evolve. For instance, quant skills – using computer-driven models for trading – data science and computer science may become an important knowledge to hold in the industry.”
The use of AI and machine learning is also proving helpful to compliance teams, not just freeing up time and resources for an organisation’s staff through the automation of monotonous tasks, but ensuring that firms are being compliant even quicker.
Financial software provider Misys has recently made the foray into compliance-based AI solutions with a trade monitoring platform, for example. Its new solution red flags probable mistakes that can prove crucial to EMIR and FRTB compliance, as EMIR requires trades to be confirmed without errors within 48 hours, and FRTB requires daily risk reports which would breach compliance in the event that unidentified trade errors are found.
Indeed, as regulation continues to tighten up across Europe, the chance for firms to make compliance as simple and as inexpensive as possible is one that they will jump at.
“Compliance processes are vitally important and need to be done with high precision, but they involve a lot of standardised procedures. These are exactly the sort of tasks which are ripe for automation,” says Matthew Hodgson, CEO at Mosaic Smart Data. “AI allows these repetitive tasks to be automated, leaving staff to focus on the more subtle, valuable and interesting work.”
As there always is with the adoption of new technology, there is a timescale and schedule to consider. While the future may not be here just yet, the pace of technological evolution is so rapid that it’s unlikely to be long before AI and automation dominate standardised tasks.
“I don’t think AI will be an immediate threat to the jobs of traders, but it will be a threat to the basic and repetitive tasks carried out by traders,” says QuantHouse’s Leroy. “Of course, if some traders are focused on such basic and repetitive tasks, that could become a threat to their role within the organisation.”
A part of what makes AI such a tempting proposition for financial organisations is the fact that machines do not cause problems or take risks that could cost the company money in the same way that a human might – as Leroy notes, “technology is a solution, not a risk”. With that said, though, there is a risk attached to it, and it does revolve around cost.