Replacing a legacy capital markets platform like Front Arena is costly, risky, and often unnecessary. By extending the core with a modern integration layer, banks can deliver real-time analytics, regulatory reporting, and digital client experiences while preserving the stability of their existing trading systems. The key is treating market data, reference data, and transaction data as distinct modernization challenges.

A data platform should be lightweight, modular, and flexible. Avoid over-engineering and build for speed, control, and scalability.

As AI agents, APIs and automated workflows increasingly consume market data directly, traditional user based licensing models are coming under pressure. This article explores why market data licensing must evolve from a human display model into a governance and control layer for machine driven data use, with stronger focus on non display usage, machine identity, entitlements, auditability and infrastructure level controls

Most companies are adopting AI, but few truly control the data that powers it. As models become interchangeable, the real competitive advantage shifts to data ownership and architecture. This piece explores why data sovereignty is the foundation of scalable AI and how adapter-based architectures help enterprises avoid hidden vendor lock-in.

Market data is reaching its AWS moment. What was once a procurement function—buying feeds and managing vendors—is becoming a strategic orchestration challenge. As AI expands data volumes and cloud delivery becomes standard, firms must move beyond ownership toward control. The competitive edge now lies in vendor-neutral integration, standardized data, cost transparency, and scalable governance. Infrastructure is no longer overhead—it is strategy.