Banking has a protocol problem.
A risk analyst at a tier-one bank submits a credit decision request. The answer requires querying the core banking system, pulling transaction history from the data warehouse, checking the sanctions database, retrieving the customer's KYC documents, running the credit scoring model, cross-referencing the regulatory capital requirements, and coordinating with the compliance agent to verify the decision is within policy bounds.
Eight systems. Multiple AI agents. Dozens of custom API integrations — each built separately, each maintained separately, each a point of failure in a regulatory environment where failures have legal consequences.
This is the integration debt that most BFSI AI initiatives are currently buried under. And it is exactly what MCP and A2A were built to solve — at the protocol level, not the application level.
This is the complete implementation guide for deploying MCP and A2A in production BFSI agentic systems — from the architecture rationale to the compliance considerations to the specific patterns that work in regulated financial environments.
