This research introduces a Standardised Financial Risk Score (SFRS) Agentic Pipeline to address the aggregate confusion and subjective drift inherent in decentralized climate-risk reporting. It proposes a Policy-as-Code (PaC) framework that leverages autonomous regional agents (London and Istanbul) governed by a deterministic Standardised Financial Risk Scoring (SFRS) mandate. To measure and correct the divergence between qualitative agent narratives and a canonical mathematical ground truth, the paper used a Pydantic-based Validation Interceptor. The results obtained show that the pipeline successfully identified and corrected initial subjective drifts of 47% and 37% in high-volatility scenarios. The result offers a scalable blueprint for asset management to achieve Mandated Convergence, ensuring that climate disclosure remains mathematically standardized and economically nuanced.
Keywords: RegTech, SFRS, agentic AI, climate-risk, mandated convergence, policy-as-code
