Rating Agencies

Rating agencies—whether focused on Cyber Security, ESG, or Credit—face a dual challenge: they must ingest vast quantities of unstructured data while maintaining a rigorous, defensible scoring methodology.

Fluvial Diligence provides the operating system for modern rating agencies. It combines a sophisticated data collection engine with advanced scoring capabilities and a headless content management system, allowing agencies to focus on their proprietary methodologies rather than software maintenance.

The Rating Agency Challenge

Agencies typically rely on a patchwork of spreadsheets, survey tools, and custom-built databases. This fragmentation makes it difficult to:

1. Evolve scoring methodologies without rebuilding software.
2. Maintain audit trails of why a specific rating was assigned.
3. Scale analyst throughput without linear headcount growth.
4. Integrate qualitative analyst judgement with quantitative data feeds.

How Fluvial Supports Rating Workflows

1. Advanced Scoring Methodologies

Fluvial goes beyond simple weighted averages. It supports the complex, hierarchical models required for professional ratings.

Hierarchical Weighting - Define scoring models with unlimited nesting depth. A “Governance” score can be composed of “Board Structure” and “Policy” sub-scores, each with their own weightings that roll up to the top-level rating.

Pairwise Comparison - For subjective criteria (common in ESG and qualitative risk), absolute scoring is notoriously inconsistent. Fluvial includes an Elo-based pairwise comparison engine. Analysts compare two entities against a specific criterion (“Which company has the stronger anti-bribery policy?”), and the system mathematically derives a robust relative ranking.

LLM-Assisted Analysis - To scale coverage, Large Language Models can perform the initial pass of pairwise comparisons or document analysis, providing a rationale for human analysts to review. This “Human-in-the-Loop” approach dramatically increases the number of entities an agency can rate.

2. Data Ingestion & Integration

Ratings are rarely based on questionnaire responses alone. Fluvial acts as a central hub for all rating data.

Multi-Channel Ingestion - Collect data via direct API submission, structured questionnaires sent to rated entities, or by scraping public disclosures.

3rd Party Feeds - Use Webhooks and APIs to pull in external signals—such as vulnerability scan data for cyber ratings or controversy news feeds for ESG scores. These signals can automatically trigger rating reviews.

3. Governance and Audit

In a regulated environment, the process of rating is as important as the result.

Strict Workflows - Define approval gates using CEL guard expressions. Ensure that a rating cannot be published until it has been reviewed by a senior analyst and approved by a committee if it deviates significantly from the previous rating.

Immutable Audit Trails - Every data point change, score adjustment, and approval decision is logged. You can reconstruct exactly what information was available to an analyst when a rating decision was made.

4. Headless Publishing

Fluvial is a “headless” platform. It does not dictate how you present your ratings to subscribers.

Structured Data Output - Your ratings, rationale, and underlying data are stored as structured JSON documents.

API Delivery - Feed your client portal, Bloomberg terminal integration, or data feed products directly from Fluvial’s API.

Document Generation - Generate PDF reports or factsheets on-demand using the document automation engine, mapping the latest rating data into branded templates.

Use Cases

ESG Rating Agencies

Challenge: ESG ratings rely heavily on qualitative assessment of policy documents and disclosures. Consistency between analysts is a major issue.

Fluvial Solution:

• Use Pairwise Comparison to rank companies on “Social” factors, ensuring consistency across the coverage universe.
• Use Document Management to map corporate CSR reports into structured data fields.
• Use Workflows to manage the “issuer feedback” process, allowing companies to review factual data before the rating is published.

Cyber Risk Ratings

Challenge: Cyber ratings must combine automated scan data with inside-out questionnaire data.

Fluvial Solution:

• Ingest scan data (open ports, patching status) via API.
• Send detailed security questionnaires to the rated entity.
• Use Hierarchical Scoring to blend the technical scan score (40%) with the governance questionnaire score (60%) for a holistic view.
• Automatically trigger a re-assessment workflow if a new CVE affects the entity’s technology stack.