JPM Develops A.I. Robot To Execute High Speed Trades, Put Humans Out Of Work

With high-margin FICC revenues stuck in a secular decline across the financial industry, banks are forced to extract as much profit as possible from existing product lines. Which explains why JPMorgan will soon be using a "first-of-its-kind robot" to do away with carbon-based traders altogether and execute trades across its global equities algorithms business using a "robot", after a recent trial of JPM's new artificial intelligence (AI) program showed it was "much more efficient than traditional methods of buying and selling", the FT reports.

JPMorgan, the world’s biggest bank by revenue, believes it is the first on Wall Street to use AI with trade execution and said it would take rivals 18 to 24 months and an investment of “multiple millions” to come up with similar technology.

The AI — known internally as LOXM — has been used in the bank’s European equities algorithms business since the first quarter and will be launched across Asia and the US in the fourth quarter, Daniel Ciment, JPMorgan’s head of global equities electronic trading, told the Financial Times.

In the latest victory for robot kind over humans, LOXM’s job will be to execute client orders with maximum speed at the best price, "using lessons it has learnt from billions of past trades — both real and simulated — to tackle problems such as how best to offload big equity stakes without moving market prices."

In other words, one giant "big data" aggregator, using historical precedent to guide future decisions, which coming in a time when "this time it's certainly different" for the broader stock market, could be a big mistake.

“Such customisation was previously implemented by humans, but now the AI machine is able to do it on a much larger and more efficient scale,” said David Fellah, of JPMorgan’s European Equity Quant Research team. Mr Ciment said that, so far, the European trials showed that the pricing achieved by LOXM was “significantly better” than its benchmark.

The development guarantees another round of downsizing among bank front offices as increasingly inefficient human traders are removes from the equation... and payroll. As the FT notes, investment banks have been increasingly using AI, automation and robotics to help cut costs and eliminate time-consuming routine work. "For example, UBS’s recent deployment of AI to deal with client post-trade allocation requests, which saves as much as 45 minutes of human labour per task. UBS has also brought in AI to help clients trade volatility."

Commenting on the launch, Ciment said that “best execution is becoming more and more important to clients,” adding that it could become part of the marketing pitch the bank makes to clients.  The AI was developed using “Deep Reinforcement Learning” methods, which are able to learn from millions of historic scenarios. Mr Fellah said DRL had “many other potential uses in banking, such as in automatic hedging and market making”.

One possible evolution of LOXM is teaching the machine how to get to know individual clients, so that it could consider their behaviour and reaction as it decides how to trade. “Any customisation would only be if the client agrees to that,” Mr Ciment added.

Unlike similar robotic advancements on the buyside, especially at Blackrock which is increasingly automating stock-picking using "big data" and robots in a wholesale push for passive investing, JPMorgan’s AI has no decision-making capabilities around what is bought and sold - a differentiation from existing robo advisors - as its role is solely to decide how things are bought and sold.

JPM also said it had no risk management issues with the technology. “The machine is restricted in its trading behaviour, as it learns under, and operates within, our general electronic trading risk framework, which is overseen by internal control groups and validated by regulators,” Mr Fellah said.

Of course, with such rapid propagation of technology among both stock investing and trade processing, it is only a matter of time before a "black hat" hack takes place, and sends trading - and markets - haywire. Which, incidentally, may be among the reasons for the concerted push: after all what better way to avoid blame for what is coming than to blame it on, who else, Russian hackers.