- UBS says AI could boost banks’ revenues by 3.4% and cut
costs by 3.9% over the next three years.
- Investment and retail banks are looking at the
application of AI for things like “robo advisors,” chatbots,
and compliance tools.
- But there are challenges to implementation, as most
banks need to sort their data sets out to handle AI.
LONDON — Banks are getting excited about the potential of
artificial intelligence in finance, with hopes that AI could both
cut costs and boost revenues.
Artificial intelligence has advanced in recent years and
financial services companies are now looking at its potential
applications in both investment banking and retail banking.
Advocates tout AIs potential in everything from bond markets to
“Based on our UBS Evidence Lab survey of 86 banks, an optimal
scenario of limited disruption suggests AI technology could
potentially lead to a 3.4% revenue uplift and cost savings of
3.9% over the next three years,” UBS strategist Philip
Finch wrote a recent note titled “Is AI the next revolution in
“I think the future of financial services is AI,” Barnaby
Hussey-Yeo told Business Insider. Hussey-Yeo is the CEO and
founder of Cleo, a “chatbot” app that uses artificial
intelligence to give people advice on how to optimise their
“Fundamentally, what we’re trying to do is build an AI that is
near human in the way it interacts with your finances. Cleo
should always be working on your behalf to help you take the best
possible course of action,” Hussey-Yeo said.
“The future is that you don’t have to think so hard and worry
about money in the way people do at the moment. You can simplify
all financial services.”
‘There are huge areas of potential across the firm’
AI has come into particular focus in 2017 thanks to public
successes such as
Google’s DeepMind beating Go world champion Ke Jie at the Chinese
board game, which has traditionally out foxed AI, and
warnings from figures such as Professor Stephen Hawking that
huge, potentially dangerous, breakthroughs in the field are
UBS highlighted in its recent note that $11 billion has been
invested into artificial intelligence since 2010. That figure is
set to rise to more than $47 billion by 2020.
Advances in fields such as machine learning and natural language
processing have particular relevance for finance, allowing
investment algorithms to optimise themselves and for customer
service bots to interact with customers. In short, AI now has the
potential to tackle complex tasks once reserved for humans.
UBS, which highlighted its potential, has
already launched a so-called “robo advisor” — a digital
tool that uses machine learning to offer automated
investment advice based on people’s financial circumstances.
Other applications include customer service chatbots, automated
reporting, improved risk assessment, and tools to help sell-side
bankers be smarter in their targeting.
“It’s definitely something we’re looking at,” Craig Butterworth,
global head of client eco-system at Nomura, told Business Insider
when asked about AI. “There are huge areas of potential across
the firm, front to back.”
“On the front office side, there’s this concept of helping people
make the right call, to the right client, at the right time.
Understanding what types of coverage they like to receive, what
are the different activities that they’re engaging with the firm
with,” Butterworth said. “Leveraging AI will enable us to do this
at scale, near real-time and with minimal marginal cost.”
Dutch bank ING recently launched a tool called Katana that uses
“predictive analytics to help traders decide what price to quote
when a client wants to buy or sell a bond.”
Santiago Braje, Global Head of Credit Trading at ING Wholesale
Bank, said in a statement: “With Katana, AI is applied to enhance
the traders’ decision-making abilities, allowing them to deploy
their natural intuition and expertise in the most effective way.
This is a powerful combination.”
‘You won’t only understand what happened, you understand why it
London startup AiX is exploring the same territory as Katana. It
plans to build a “chatbot” broker that would replace traditional
voice brokers, such as Tullet Prebon, who traders currently call
to get prices in over-the-counter markets.
“All AiX is doing is taking inputs from people who want to
trade and inputs from financial market participants to get done
what human beings want to do, in the best way possible,” Steve
Compton told Business Insider.
Compton recently left investment bank Citi after a 26-year career
and became an advisor to, and investor in, AiX. Compton
used to oversee teams of traders at Citi and said AiX’s idea
“instantly resonated” with him. He estimates that the tool could
reduce brokerage fees by up to 50% or as much as 95% for the most
“There is a cost if you have a very well paid broker sitting
between two traders and that is reflected in the cost investment
banks’ pay,” Compton said.
AiX also has the potential for “massive savings for
compliance and massive saving by regulators,” he said. The
chatbot will record and log all the interactions with the trader.
The internal logic of the AI engine is also fully auditable,
meaning a regulator can check why the bot quoted a specific price
at that time.
“It’s a challenge for all organisations to know exactly how
negotiations took place and what they meant,” Compton said. “What
is fact, what is evidence, what is banter, what is sarcasm, and
what is a trade negotiation?
“With AiX, you won’t only understand what happened, you
understand why it happened.”
AiX plans to test its service in the commodities options
market, equity derivatives, and cryptocurrency markets next year.
CEO and founder Jos Evans, a former commodities trader, said
he is already in conversation with investment banks and the
reaction so far has been “hugely positive.”
“Traders have been really excited too,” he added, explaining that
there’s a lot of “friction and frustration” in the current
process. Traders can wait five minutes for a broker just to
acknowledge their order in some cases, Evans said.
‘You have to clean your data first’
But Nomura’s Butterworth said banks shouldn’t get carried away
over the potential of AI just yet.
“With AI, you have to have your data clean first,” he said. “Yes,
we’re thinking about the exciting elements but it’s like
building a house — you’ve got to get your
foundations laid before you build your house on top.”
Butterworth said Nomura has been undertaking such foundational
work over the last year but it’s a big job for all banks.
“Lots of people are excited about it, understandably because of
the scale of the opportunity. But there’s a difference
between being excited about it and wanting to explore
it, versus actually being ready to start launching
these applications,” he said.
Hussey-Yeo is also sceptical of how fully banks will embrace the
potential of AI. He said: “As you grow a team, it becomes harder
and harder to turn the battleship. [Banks] have got capital and
they can hire people but its more inertia of the business model,
the inertia of the traditional staff thinking.”
UBS thinks that banks which “are quick to embrace innovation and
new technologies, such artificial intelligence, will be well
placed to maximise opportunities to improve revenues and
efficiency while mitigating disruptive pressures.”
“In contrast, banks that are slow to adapt and invest are at risk
of losing their competitive strength, market positioning, and,
ultimately, their earnings power.”
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