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Carrington Labs Launches First MCP Server Bringing Compliant Credit Models into AI Lending Workflows
Agentic AI workflows are gaining momentum across financial services — 53% of executives report experimenting with them, according to a Google Cloud survey — but lenders can’t quantify credit risk without compliant, explainable models, which hinders their AI implementation. Carrington Labs, a leading provider of credit risk analytics and cash flow underwriting models, has removed that barrier by launching the first Model Context Protocol (MCP) server designed to allow lenders to access Carrington Labs credit risk models outputs — built specifically for their institution and regulatory requirements — directly within agentic flows.
Carrington Labs’ MCP server delivers both speed and confidence to lenders investing in automation through two distinct capabilities. First, AI agents can access Carrington Labs’ compliant model outputs in real time to receive deterministic credit risk assessments, unlike the probabilistic responses generative AI alone would offer, allowing lenders to build end-to-end automated workflows without reverting to manual processes. Second, credit officers can use large language models connected to the MCP server to ask questions in natural language and receive clear explanations of complex risk factors.
Jamie Twiss, the CEO of Carrington Labs, said “The launch of the Carrington Labs MCP solution is a significant step forward, allowing AI agents to safely access our risk models and enabling credit officers to understand and query model outputs. This supports lenders who are looking to deploy AI in their origination processes but still want the reliability of rigorous credit risk analytics, facilitating the broader adoption of AI in financial services in a safe and responsible way.”
While much of the AI innovation in banking has focused on chatbots and internal copilots, the Carrington Labs MCP server is a production implementation of agentic AI that enables lenders to deploy AI in compliant credit models, providing a direct benefit to the core business of the bank. Each response can include a score, model features, and explainability of key factors, allowing credit teams to see the most influential features and understand promoters and detractors of creditworthiness.
The solution provides improved transparency for underwriting teams, who can see exactly how the model reached each result. The MCP server supports Carrington Labs’ Cashflow Score and Credit Risk Model products. Client data remains secure — responses contain no personally identifiable information and reference a unique record ID only.
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