Credit decisioning in Swiss banking remains slow, inconsistent, and heavily manual despite strict regulatory demands. This LangGraph-powered multi-agent system automates the entire process while ensuring full sovereignty and compliance.
The Challenge of Slow and Inconsistent Credit Decisions
Business Challenge
Credit decisioning in Swiss banking is traditionally slow, inconsistent, and heavily manual, involving multiple departments and repeated data checks while struggling to keep pace with regulatory changes.
How Agentic AI Helps
A LangGraph-powered multi-agent system automates the entire credit assessment process while maintaining full sovereignty and regulatory compliance.
Detailed Automated Business Process
The workflow begins with an Intake Agent that gathers applicant data from multiple sources. A Risk Assessment Agent analyzes financial history and external signals using sovereign RAG. A Compliance Agent cross-checks against current EU AI Act and FINMA requirements. Only complex or high-risk cases are escalated to human underwriters for final approval.
Potential Business Impact
Credit decisions can be delivered significantly faster with higher consistency, reduced operational costs, and stronger auditability
Key Takeaways
