Citigroup Revolutionizes FX Risk Management with Cutting-Edge AI

Wall Street's sleeping giant just woke up—with algorithms.

Citigroup's new AI-powered FX risk system slashes exposure while traders sip their oat milk lattes. No humans were harmed in the making of these risk calculations.

The bank's quant team fed decades of currency swings into neural networks that now predict volatility better than that one guy who always 'called the '08 crash'.

Early results? A 40% reduction in unexpected losses—and a 100% increase in management taking credit for it.

One cynical take: Finally, a use for AI that doesn't involve generating cat memes or faking celebrity voices.

The pilot program was originally developed for aviation

According to Citigroup and Ant International on Friday, the initiative integrates Citi’s Fixed FX Rates solution, which is already widely used by clients in sectors like e-commerce, with Ant International’s Falcon Time-Series Transformer (TST) model, an AI-powered forecasting tool with nearly 2 billion parameters and the ability to help businesses reduce hedging FX costs.

The pilot program was originally developed to serve aviation clients, but it has shown great potential in the risk management sector. It has already been used in live transactions with major Asian airlines and the companies claim that it was able to reduce cost in the airline’s fixed FX hedging for online ticket sales.

The results are encouraging. Kelvin Li, general manager of Platform Tech at Ant International, said the achievement shows how cost efficiency can be achieved with AI-enabled FX hedging. He also expressed enthusiasm for the collaboration with Citi as it will help them reach more businesses and industries.

The launch comes about half a year after Citi started its roll out of new AI tools for employees in eight countries, and providing the same level of access to 140,000 employees globally.

Large banks have been using AI tools in more specific ways

Since the AI boom started, various industries have gradually shifted to adapt to the new development, and the banking sector has not been left behind.

According to reports, large banks are increasingly deploying AI tools for targeted applications to enhance efficiency, reduce costs, and improve decision-making.

Good examples include Morgan Stanley with its chatbot which was created to aid financial advisors in interactions with clients, and Bank of America’s VIRTUAL assistant Erica, created to focus on the day-to-day transactions of retail clients, using it to flag suspicious activity with greater precision.

JPMorgan Chase reportedly now uses AI for real-time risk assessment and regulatory compliance. It also operates the COiN platform, which reduces time spent on manual reviews by helping to analyze legal documents.

HSBC has also taken to using AI to detect money laundering patterns, a MOVE it claims has improved detection to 20% faster than legacy systems.

Commentators believe this widespread adoption of AI in the financial industry is encouraged by the desire of the big banks to outdo each other and stay relevant. Regulatory support has also played a role in the adoption.

In 2024, the Federal Reserve stated that AI could save the banking sector $80 billion annually by 2030.

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