UBS pushes for more robots in the trading floors

Robots are moving on to the trading floors of investment banks. Many of the world’s biggest banks have for years been automating manual, repetitive tasks done by support staff to save money. But now they are putting the latest forms of artificial intelligence to work at the heart of operations among their star traders, allocating funds and analysing data to develop strategies.

According to a report by the Financial Times, UBS is about to take robots to trading floors. The company has shown how two AI solutions can assist traders in enhancing their performance.

“There has been a lot of talk about automation of the back office,” Beatriz Martín Jiménez, chief operating officer of UBS’s investment bank, told the Financial Times. “But we decided to start a conversation with the front-office guys on whether there were processes we could use a robot to do and we found a number of them.”

The first program, developed in collaboration with Deloitte, deals with clients’ post-trade allocation requests. The program scans for clients’ emails describing how they would like to allocate large block trades among funds. The system then processes the data and executes the transfers. According to UBS, the AI system performs a task that would usually take a person about 45 minutes in only about two minutes.

“The robot can pick up the email and do the whole allocation,” said Ms Martín Jiménez, watching the system swiftly process client requests on a big screen in the ultra-modern headquarters that UBS recently built for its investment bank in London. 

The second of the new solutions uses machine learning to develop new strategies for trading volatility on behalf of clients. It scans vast amounts of trading data and creates a strategy based on learning from market patterns. The strategy, however, has then to be approved by human employees.

UBS claims it is the first “adaptive strategy” product offered by an investment bank. It has been marketing the offering to clients for a couple of months and they have been “very receptive”. While the bank is yet to convince a client to put its money into it, it expects to secure its first contract within a few months.

JPMorgan Chase has developed a similar system based on machine learning for its equities business, which helps to analyse the best way to execute a big block trade by reading market conditions.

“The artificial intelligence comes up with a trading optimisation strategy that is then validated by humans,” said Ms Martín Jiménez, adding that it was likely to be “several years” before computers were let loose to execute trades without them first being approved by bankers.

Goldman Sachs has already begun to automate currency trading. The findings are dismal for traders, as four traders can be replaced by one computer engineer, according to Mr Chavez, Goldman Sachs’s deputy chief financial officer and former chief information officer. Currently, approximately a third of Goldman Sachs’s staff are computer engineers.