At iFX Dubai 2025, Jon Light, head of OTC products at Devexperts, delivered a deep dive into how brokers across the MENA region can use AI to improve their operations—from customer support and localisation to risk management and trader selection.
One of the most immediate impacts of AI is in trader-facing customer support. Devexperts, which has long maintained an in-house AI and machine learning division, is using chatbot solutions to deliver real-time, around-the-clock support for brokers.
These bots are trained on internal datasets like past support tickets and CRM records, enabling them to respond to around 70% of trader queries. This is particularly valuable in a region where speed, clarity, and cultural nuance in customer communication are essential. “It’s a no-nonsense market in the MENA region. You need to respond quickly and make the experience authentic,” Light said.
The complexity of the MENA region’s linguistic landscape also makes localisation a major challenge. With AI-driven natural language understanding (NLU), brokers can automatically identify a trader’s preferred language—and even adapt to dialects and cultural preferences. Whether traders favour formal or informal tone, AI can be trained to communicate accordingly, offering a more personal and appropriate experience.
On the risk management side, AI is helping brokers shift from static to dynamic B-book operations. Rather than adjusting B-book exposure a few times a day, AI can make decisions in real-time by analysing broker and trader positions, orders, and volatility. “AI also takes into account broker positions, trader positions, orders in the OMS, market volatility, and risk appetite, allowing for more efficient flow management,” said Light.
AI is also being used to flag manipulative trading behaviour, such as attempts to exploit platform delays. It can spot these anomalies early, giving brokers a head start in mitigating threats.
This extends to funded trader programmes, where AI can distinguish between genuinely skilled traders and those gaming the system. “We see traders buying two separate challenges and placing opposite trades to rig the system, doing whatever they can to get through. With AI, we can analyze their trading behavior early on.
“The best traders don’t dive into the most volatile markets. They tend to stick to a small number of instruments they understand well. AI can analyze those behaviors and help firms filter out traders who are just taking advantage of the system.”
For smaller brokers, Light urged caution when approaching AI adoption. While larger firms can afford to experiment, smaller players should focus on real business problems before investing. “Start with a real problem and find the right AI solution for it. Don’t create a problem just because you think you need AI,” he said.
One of the more forward-looking use cases Light highlighted was AI-driven algorithmic trading. As natural language becomes the interface for algorithm design, traders will no longer need coding skills to build strategies. “Start with a real problem and find the right AI solution for it. Don’t create a problem just because you think you need AI,” Light said.
For more insights from Light, read the full story here.
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