Transforming Underwriting With a Data-Driven Rating Engine

A next-generation MGA serving more than 47,000 certified physicians relied on a fragile, spreadsheet-driven pricing system with no single source of truth. Myridius implemented a data-driven, systemized rating engine on Origami Risk, replacing spreadsheets with automated, governed workflows that enable scalable multi-state pricing and audit-ready underwriting decisions.

Key Outcomes

• A centralized, scalable pricing platform replacing spreadsheets.
• Faster market response through automated calculations.
• Stronger data governance with audit-ready pricing decisions.

Overview

A next-generation MGA serving more than 47,000 certified physicians relied on a fragile, spreadsheet-driven pricing system with no single source of truth. Multiple spreadsheets, inconsistent logic, and manual processes created scalability issues, slow underwriting turnaround, data integrity risks, and limited ability to support multi-state products or complex pricing. Myridius implemented a data-driven, systemized rating engine on Origami Risk, replacing spreadsheets with structured, automated workflows including effective-dated tables, multi-state variables, underwriting guardrails, and audit-friendly logs. As a result, the organization shifted from fragmented spreadsheets to a centralized, scalable pricing platform, improved operational efficiency, accelerated market response, strengthened data governance with audit-ready decisions, and gained a future-proof architecture supporting new states, endorsements, and reinsurance workflows.

Client Context

The client is a next-generation managing general agent (MGA) serving more than 47,000 certified physicians.

A systemized, governed rating platform mattered here because spreadsheet-driven pricing with no single source of truth created scalability, speed, and data integrity risks as the business expanded. What was at stake was the organization's ability to make confident pricing decisions and grow across new states, endorsements, and reinsurance workflows.

The Challenge

The MGA relied on a fragile, spreadsheet-driven pricing system with no single source of truth. Multiple spreadsheets, inconsistent logic, and manual processes created scalability issues, slow turnaround, data integrity risks, and limited support for multi-state products or complex pricing. The desired state was a unified, system-driven pricing platform with governance and auditability.

Consider pricing a multi-state product. Logic lived across multiple spreadsheets with inconsistencies, manual processes slowed turnaround, and there was no reliable audit trail. As the business expanded, this legacy model hindered efficiency, confident pricing, and growth.

Transformation Goals

The engagement focused on north stars that connected systemized pricing to multi-state scalability, accuracy, and governance.

• Systemized, Multi-State Pricing: Replace spreadsheet-based rating with a unified, system-driven platform enabling consistent multi-state pricing through variables and effective-dated logic.

• Accuracy and Scalability: Improve underwriting accuracy with guardrails, subjectivities, and centralized controls, and enhance scalability for complex risks, schedules, pools, and reinsurance.

• Governance and Speed: Strengthen governance, data integrity, and auditability while delivering faster market response through automated calculations and loss-run ingestion.

The Solution

The engagement implemented a data-driven, systemized rating engine on Origami Risk, replacing spreadsheets with structured, automated workflows. Myridius orchestrated the rating platform foundation, embedded automation and guardrails into pricing, and reimagined underwriting as governed and audit-ready. The progression moved from deploying data-driven rating on Origami Risk, to embedding bulk processing and underwriting guardrails, to reimagining pricing governance with audit-ready, future-proof workflows.

• Orchestrated the foundation: Built data-driven rating using effective-dated tables, multi-state variables, and automated logic, with an enhanced UI using custom HTML, CSS, and dynamic JavaScript screens.

• Embedded intelligence into the journey: Implemented a bulk processing engine for loss runs, weighted schedule and pool consolidation, smart defaults and dynamic toggles, and underwriting guardrails with subjectivity tracking.

• Reimagined the operating model: Established save and bind controls with exception handling and audit-friendly append-only logs, and a unified workflow for direct and reinsurance proposals using catalog-driven forms.

Governance and Trust

Because this engagement governed insurance pricing decisions, data integrity and auditability were central. Save and bind controls with exception handling and audit-friendly, append-only logs ensured that every pricing action was traceable, while underwriting guardrails and subjectivity tracking enforced compliance and reduced errors.

Effective-dated tables and centralized, system-driven logic replaced inconsistent spreadsheet calculations with a single source of truth, strengthening data governance and producing reliable, audit-ready pricing decisions. This governed foundation also supported confident expansion across new states, endorsements, and reinsurance workflows.

Results

The engagement transformed fragile, spreadsheet-based pricing into a centralized, automated, governed rating platform. The result was scalability, speed, and audit-ready governance.

The result:

• Shifted from fragmented spreadsheets to a centralized, scalable pricing platform, improving operational efficiency and reducing manual underwriting effort.

• Accelerated market response through automated calculations and consolidated workflows, with clearer, more accurate pricing signals.

• Strengthened data governance with reliable, audit-ready pricing decisions and a future-proof architecture supporting new states, endorsements, and product growth.

Technology Stack

For an expanding MGA, spreadsheet pricing is a scalability and integrity risk that compounds with growth. This case shows how a systemized, governed rating engine turns pricing into a growth advantage. This was not a spreadsheet cleanup. It was a systemized, governed, audit-ready rating engine built for multi-state scale.