Cash & Liquidity ManagementFXUBS banks on machine learning for algorithmic trading systems

UBS banks on machine learning for algorithmic trading systems

In a bid to expand its liquidity offering to clients, UBS is looking to machine learning to plug FX liquidity gaps on its algorithmic trading systems

UBS has announced that it is making use of machine learning to run the algorithmic trading systems for its foreign exchange business – at a time when global currency markets are dealing with a number of flash crashes.

Algorithmic trading, also known as algos, is a vital part of the $5.1 trillion-a-day global FX market. It accounts for up to a fifth of all trading and about 70 percent of all orders placed on multi-dealer currency platform EBS.

UBS is not the only large bank investing millions of dollars in algorithmic technology as it cuts back on trading teams and relies more on automatically computed strategies to trade more efficiently. JP Morgan, which also reported double-digit growth in its algorithmic trading business in recent months, has released a new machine learning algorithm, and Citibank is another top player in electronic currency trading.

As socio-political uncertainty and volatile economic conditions continue to wreak havoc on foreign exchange markets, treasurers must prioritise foreign exchange risk management in order to deliver sustainable growth.

Best available liquidity

ORCA-Direct, one of the algorithms used by UBS, computes a wide range of liquidity sources, including ECNs, futures and the bank’s principal price. It learns in real time, utilizing historical trading data to find the bank’s clients the best available liquidity when volatility rises. ORCA stands for optimal routing control algorithm.

First rolled out to a limited numbers of clients in May 2018, it helped volumes in the bank’s algorithmic FX business double in 2018. That made UBS the fastest-growing FX algo broker by market share from the second to the fourth quarter.

The algo combines machine learning-driven analytics with synchronised order placement, making Orca-Direct a good match for clients that need to be filled urgently. The bank has now enabled all of its algos to use the Orca technology for liquidity access and it will continue to develop analytics capabilities too.

Determining the best platforms and execution sequence

Chris Purves, Head of the bank’s FRC Strategic Development Lab said: “What is unique about ORCA is the machine learning we put into it. Clients can see their executions improving, they can see their fill rates improving.”

ORCA’s machine learning enables the algorithm to determine within microseconds the best platforms and execution sequence to use, estimating the probability of trading and market impact for each specific order and reducing costs for the bank’s clients.

That can be crucial in the fragmented currency market, where about 70 different platforms exist with multiple banks, hedge funds and technology firms jostling for market share.

The growing number of flash crashes – where prices of currencies can swing wildly within seconds – also complicates matters.

The bank expanded ORCA to US Treasury trading in late 2018, with further roll-outs expected in the Foreign Exchanges, Rates and Credit (FRC) space.

Digitizing UBS

Last week, UBS retrained 350 of its back-office employees in automation software and asked its entire investment banking staff to come up with ideas for digitizing the company, as it looks for more ways to use technology to overhaul its business.

The bank began its digitisation drive in 2016 and now has more than 1,000 “robots” automating functions such as clearing and settlements and converting unstructured data like emails into a usable digital format.

The idea is to “harness collective wisdom”, according to a memo sent out about the initiative, through mass discussions on an internet forum on how to take the strategy forward. The bank will hold sessions for employees on digitalisation and innovation, from Tuesday until Thursday.

Investment Bank Chief Operating Officer Beatriz Martín Jiménez said: “Banks have traditionally focused on premium clients but new digital technologies would allow access to a broader customer base.

“The way forward for everybody is to build a platform where you’re going to be able to serve a much wider group of clients at a very low margin of cost per new client.”

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