Market intelligence and risk analysis both depend on financial data that is messy, fast moving and scattered across systems that were never designed to talk to each other. This session brings together panelists covering how multi-agent architectures are being used to pull structure out of that chaos. What this session will cover: - How multi-agent architectures handle fragmented and fast moving financial data - Design patterns for agents specialising in different parts of market intelligence and risk workflows - Where these architectures still struggle with data quality and latency - What a practical starting point looks like for teams building this today Three different vantage points on the same problem, rare to get all three in one room.