e-Forex-July-23-HighRes-SCREEN

Cutting through the hype: Where AI is already making its presence felt in FX
FINTECH
“The massive amount of fast moving data that is generated as
a result makes AI analysis (and speed) highly suited to FX,”
Tim Carmody
when they trade, then automatically
generating alerts for sales teams for
clients who may need more attention.
These AI generated alerts and signals
can also be combined with proprietary
algos hosted in the SmartTrade
AlgoBox allowing a bank, if it wishes,
to have automated reactions to these
actionable insights.
“This automation is clearly the
direction of travel of the front office
market,” says Culiniac. “How long
it will take to develop and to what
extent full automation will prevail of
course depends upon the specifics of
the bank, its clients, and the types of
action we are considering.”
Carmody agrees that both buy- and sellsides
can benefit from using AI, although
he suggests its access to vast resources
probably gives the sell-side the edge.
When asked how AI and machine
learning is already being used in FX
trading, Carmody says they are being
deployed to synthesise data effectively
from a large number of sources,
with applied ‘interpretation’ such as
sentiment analysis.
“This data analysis is combined with
market research and historical pattern
recognition,” he says. “Real time
transcription of voice trading is also
being adopted more widely to create
another source of data to feed into
trading engines, alongside algorithmic
order execution.”
Culiniac says AI and machine learning
have already revolutionised many
aspects of FX trading.
“They are used in data analysis to
process vast quantities of market
data to identify patterns and predict
future price movements,” he explains.
“In market research, AI algorithms -
particularly those involving natural
language processing - analyse
sentiment from diverse sources to
understand market influences.”
For liquidity management, AI assists
by forecasting supply and demand in
the FX market, helping to pinpoint the
optimal timing for trades and identify
the most liquid trading pairs.
“In risk management, AI systems
identify potential market shifts or
volatility spikes, adjusting trading
strategies accordingly to mitigate
risks,” adds Culiniac, who goes
on to outline the potential risks of
deploying AI that echo with some of
the observations made in the OECD
report.
RISK CONSIDERATIONS
“Deploying AI in loosely regulated
markets such as FX carries risks
associated with the concentration
of power, systemic risk, and lack of
transparency,” he says. “The use of
sophisticated AI systems may further
centralise trading power in large
institutions, potentially exacerbating
existing market inequalities.”
AI-driven trading can also increase
systemic risk if numerous systems are
trained on similar data and implement
analogous strategies, which could
lead to a cascade of trades amplifying
market volatility during certain
conditions.
“Finally, AI systems - especially those
based on deep learning - are often
perceived as ‘black boxes’ due to
their complex and non-transparent
decision making processes, which
poses challenges for accountability,”
continues Culiniac.
Due to the perceived relative newness
of the technology, some SmartTrade
Technologies clients have chosen to
use AI/machine learning tools to derive
actionable information from their data
and to enable them to have better
conversations with clients, liquidity
providers and internal stakeholders
rather than to fully automate mission
critical processes.
“It is almost inevitable that as
market acceptability increases and
the technology matures we will see
more and more aspects being fully
automated in the front office as banks
Alexander Culiniac
“In risk management, AI systems identify potential market
shifts or volatility spikes, adjusting trading strategies
accordingly to mitigate risks,”
68 JULY 2023 e-FOREX