Real Time

Every trading system ultimately depends on one thing: market data. Get it late, get it incomplete, or get it wrong, and everything downstream — order routing, risk checks, pricing models, backtesting — is compromised. Yet market data infrastructure is the least glamorous and most under-invested part of most trading platforms. Firms spend millions on execution algorithms and risk models while running market data through a decade-old, single-threaded ticker plant that drops packets when volume spikes. Market data pipelines at trading firms exhibit a consistent pattern: the existing system works at normal volumes, fails silently during market events, and data gaps go undetected until a trade breaks. The fix is not a faster machine. It is an architecture designed for the scale, diversity, and reliability requirements of modern trading. ...

If you are building or operating a real-time payments platform in 2026, you already know that rules-based fraud detection is dead. Attackers use generative AI to produce thousands of synthetic identities per hour, payment rails like FedNow and SEPA Instant settle in under 10 seconds, and authorised push payment (APP) fraud alone cost UK consumers £460 million in 2025 according to UK Finance. The only way to keep up is machine learning operating at the wire — feature computation, model inference, and a decision returned before the payment completes. The modelling is the easy part. The hard part is building the infrastructure to serve those models at sub-100-millisecond latency, with features computed from streaming data, with rules and models running in the same decision pipeline, and with explainability that satisfies regulators. ...

Edge computing brings processing closer to the data source. For financial services, this means processing transactions, analysing risk, and detecting fraud at the network edge — closer to customers, exchanges, and data sources — rather than in a centralised cloud data centre. Edge computing is not new. Trading firms have colocated with exchanges for decades to minimise latency. But the cloud providers’ edge offerings — AWS Wavelength, GCP Distributed Cloud, Azure Edge Zones — have made edge computing accessible to a broader range of financial services firms. ...