
The Model Context Protocol (MCP) is poised to revolutionise how private banks, wealth managers, portfolio managers, risk offices, and advisers interact with financial data and intelligent systems.
By establishing a secure standard for integrating large language models (LLMs) and advanced AI agents with enterprise and market data, MCP delivers unprecedented automation, interoperability, and compliance capabilities – reshaping workflows across the financial industry.
“Agentic financial AI” is coming, which is why the Infront Innovation Lab has discovered several use cases on our test engines:
- Private banks and wealth managers: MCP will enable automated customer onboarding, cross-system KYC/AML checks, instant portfolio reporting, contextual advisory communications and dynamic client risk profiling – all with compliance-grade audit trails and seamless data connectivity.
 - Portfolio management: AI agents powered by MCP can query live market data, run trading and rebalancing strategies, validate asset allocations, and generate actionable compliance and instrument analytics on demand, minimising manual hand-offs.
 - Risk offices: MCP opens intelligent risk monitoring, regulatory reporting, and scenario analysis across fragmented sources, with real-time model-driven workflows that adapt as new risk factors emerge.
 - Relationship managers and advisers: AI-driven interactions become contextually rich and instant. MCP lets agents personalise advice based on real-time holdings, historical data, risk questionnaires, and integrated CRM insights.
 - General market data use case: firms gain the ability to plug any LLM into reference, real-time or alternative datasets, with the protocol enforcing standard, vendor-agnostic access and automated compliance, making complex analyses routine.
 
Disruption and market impact
MCP eliminates the need for custom APIs and brittle integrations, slashing integration time and enabling true plug-and-play interoperability. This standardisation radically reduces cost, complexity, and risk for financial institutions, while allowing secure, granular control over AI agent permissions and information flows. Infront envisions a fundamental reshaping of how banks source, apply, and monetise data – with operational, advisory, and reporting roles transformed.
So here at Infront, we are rapidly preparing our platforms for MCP compatibility. That is why you have seen us over the last three years integrating market data, risk, valuation, portfolio management and trading capabilities combined through API layers, with significant R&D investments.
Adoption timeline
Global adoption of MCP is accelerating, we are planning full integration for the next 12-24 months in phases. The protocol’s maturity (it is only one and half years since launch) is projected to reach adoption in 2026: major clouds (AWS, Azure, Google, Oracle) and platforms (OpenAI, Anthropic, Gemini, Microsoft Copilot) have announced or rolled out MCP features, and Infront on our data feeds, wealth management suites and risk systems have added support, while exploring more use cases.
How you can prepare
- Audit existing systems: assess which applications and data sources support MCP; catalogue readiness and identify high-value integration targets. Do your current systems and data feeds have APIs that can work with the MCP protocol?
 - Engage with us: let's work together to create a MCP roadmap and support in our products, onboarding and renewals, and evolve with your strategic priorities.
 - Pilot key use cases: start with targeted, high-impact MCP deployments (client onboarding automation, unified market data query, AI-driven compliance) to demonstrate value and also refine a security architecture.
 - Invest in security and governance: develop robust authentication, permissioning, and audit procedures to protect sensitive data and maintain regulatory control since AI agents gain cross-system access.
 - Focus on change management: train internal teams and foster a culture where intelligent agents, automation, and contextual protocols underpin core workflows, not just technical silos.
 
Why MCP is a strategic priority
The Model Context Protocol is far more than a technical upgrade – it is the bridge to a future in which financial institutions deploy context-aware, compliance-secured automation at scale. Those investing today are not just future-proofing technology stacks; they are repositioning themselves to deliver richer client experiences, accelerate innovation, and outperform in an AI-native market.
If you are interested to learn more about our MCP research and want to exchange experiences, reach out to Infront.
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