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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
2023 PRINCIPAL SPONSORS JULY 2023 e-FOREX 69
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Page 47 and 48: THE e-FOREX INTERVIEW Michael Idzko
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Page 55 and 56: SPECIAL REPORT JULY 2023 e-FOREX 55
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