Brace For Layoffs: ING’s New AI Model “Definitely” Outperforming Humans In Pricing Currencies
Brace for mass layoffs on Wall Street.
It’s becoming evident that ING’s new AI model, which uses “reinforcement learning”, is doing a better job at pricing currencies than humans, according to a new report from Bloomberg.
The AI process “mimics the trial-and-error process humans use to make pricing decisions to keep up with market volatility,” according to global head of electronic trading Simon Bevan.
He continued: “It makes sense to take what we’ve done and see how we can use it in different asset classes. Working on more AI models will be a big focus for us going into next year.”
In an interview with Bloomberg, he said: “It’s a full-time job monitoring the market, adjusting spreads and managing the risk, so it’s freed up basically a whole person. This model completely takes care of that and has performed way beyond our expectations, it has definitely outperformed a human.”
Bloomberg writes that banks are racing to deploy advanced technology in the $7.5 trillion-a-day global currency market to cut costs and stay competitive. The focus has shifted to AI, which could streamline operations and reduce the need for human traders.
ING recently hired James Robinson, a machine learning expert from UBS’s electronic FX trading team, to spearhead this effort. After a three-month build and six weeks of testing, Robinson is now developing additional AI solutions.
The role of traders is evolving as AI becomes more prominent, but complete automation remains uncertain. At a recent conference, dealers expressed doubts about eliminating human oversight and raised concerns about accountability if issues arise.
Despite these worries, ING’s Bevan emphasized that traders will still be responsible for monitoring and halting any AI malfunctions. The bank’s model approval process has been smooth so far, the report says.
“The speed of change within the FX landscape makes accurately measuring and reacting to these changes with traditional algorithmic models challenging. This sort of new AI-based algorithm “has vast applications across financial markets,” Kimiya Minoukadeh, global head of quant trading, concluded.
