Yes — financial institutions still need enterprise-grade solutions. Agentic technologies like MCPs can orchestrate tasks, but they depend on robust foundations to deliver real business value.

AI agents do not replace enterprise platforms—they rely on them. In capital markets environments, agents require trusted data, systems of record, integration layers, and governed workflows to operate safely and effectively.

Without these, agents risk becoming unreliable, disconnected, or non-compliant in high-stakes, regulated workflows.

Start with your data foundation. Agentic AI in financial services is only as effective as the data it can access, interpret, and act upon.

Fragmented, inconsistent, or ungoverned data limits what agents can do—and increases operational and regulatory risk.

The first step is establishing a trusted, connected data environment, supported by systems of record and integration layers. This creates the foundation for workflow orchestration, enabling agents to move across capital markets processes with accuracy and context.

From there, firms can scale by embedding agents into workflows, automating processes, and enabling real-time decision-making.