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ING Groep NV has introduced a new AI model to handle currency pricing, replacing the traditional role of human traders.
This move marks a significant advancement in the banking industry’s ongoing shift towards using AI and automation for better efficiency in the fast-paced $7.5 trillion-a-day global currency market.
ING’s AI system employs reinforcement learning, a technique that enables the model to learn from trial and error, similar to human decision-making. This helps it adapt to unpredictable market conditions.
The Benefits of AI in Currency Trading
According to a Bloomberg report, the AI model developed by ING’s team, which includes an expert in machine learning recruited from UBS Group AG, has shown impressive results. The model has outperformed human traders, taking over tasks like adjusting spreads and managing market risks.
According to the bank, using AI for this role has freed up significant manpower and delivered results beyond expectations.
The AI can monitor markets, make real-time decisions, and adjust its approach based on continuous learning, making it faster and more accurate than manual trading methods.
Simon Bevan, ING’s global head of electronic trading, explained that this AI system performs tasks once managed by human traders full-time.
New Developments and Future Plans
ING’s introduction of AI into its foreign exchange (FX) division is just the beginning. The bank is also exploring ways to apply AI technology to other asset classes, aiming to expand the use of these models beyond currency trading.
To lead this transformation, ING hired James Robinson, a PhD holder in machine learning, to develop and test the AI model. Despite these advancements, human oversight remains essential. ING ensures that traders still have control over the AI system.
Bevan acknowledged that traders will always be able to intervene if necessary, with a safeguard system, described as a “big red button,” to stop the program in case of malfunction.
ING will also restructure its trading team to expand the AI technology initially developed for its FX division into other asset classes. Other financial institutions are making similar moves, recognizing that AI’s potential is not just in currency markets but also in areas like equities trading and credit risk assessment.
Goldman Sachs has also invested heavily in machine learning to predict market trends and optimize trading strategies.
