The intelligence gap in banking
Financial institutions are no longer just experimenting with AI, they're actively building autonomous agents to handle loan processing, customer onboarding, and fraud prevention, and more. The direction of travel is clear: 78% of organisations now use AI in at least one business function, up from 72% in early 2024 and 55% a year earlier (nCino, "AI Trends in Banking 2025: The Strategic Transformation of Financial Services"), and agentic AI tools are predicted to save 20–40% in software investments by 2028.(Deloitte, "FSI Predictions 2025") On top of that, agentic AI could unlock 40% productivity gains in core operations by automating multi-step workflows that previously needed significant human effort. (McKinsey & Company, insights on Agentic AI's impact on core banking operations and productivity)
But there's a critical gap.
Traditional core systems typically capture only a fragmented 20–30% view of your customer journey. That forces your teams into costly, manual processes to complete high-value workflows. And your AI agents? They're only as good as their access to the underlying systems, traditional APIs lack the contextual, executable framework agents need to make decisions and take action.
This is the problem the Mambu MCP solution solves.