Earnix
Real-time rating, pricing, and dynamic decisioning platform for insurers and banks. Deployed alongside Guidewire PolicyCenter and other PAS systems to externalise pricing logic from the core policy system. The modern-rung incumbent in rating-and-pricing.
earnix.com ↗Score
- Traction (named carrier deployments)4 carrier deployment(s) with public source.
- 2/5
- Maturity (years since founding)Founding year not publicly documented.
- n/a
- Coverage (insurance lines supported)4 line(s) supported: auto, home, commercial, life.
- 4/5
- Analyst recognition (Celent / Gartner / Forrester / Everest / ISG)2 mention(s).
- 2/5
What it does
Earnix is the modern-rung rating-and-pricing platform for insurers and banks. The product externalises pricing logic from the PAS, allowing carriers to deploy rate changes in hours rather than months and to run real-time pricing decisioning at the point of quote. Deployed alongside Guidewire PolicyCenter in multiple public reference architectures.
Named customers. Co-operators (Canada) is the marquee named customer, with public materials describing the externalisation of pricing and rating into Earnix integrated with Guidewire PolicyCenter. Gore Mutual, Domestic & General, and Link4 appear in Earnix's own customer references. The platform also serves major Fortune 500 financial-services groups, though Earnix's financial-services customer list is less systematically published than its insurance list.
Analyst presence. Earnix appears in Gartner Peer Insights' Rating Engines category, an aggregated buyer-review surface rather than a flagship product like the Magic Quadrant. A Capgemini capabilities brochure from 2022 describes Earnix as a partner in insurance product-management modernisation.
Where it sits in old → new → AI. The legacy rung is actuarial work in SAS and R plus rate tables embedded in the PAS. Earnix is the modern rung: a dedicated pricing-and-decisioning SaaS deployed alongside the PAS. The AI-native rung above Earnix is Akur8, founded 2018 — and Earnix itself has been adding generative and agentic AI features to the platform, positioning the product as a bridge rather than a static incumbent.
Named deployments
Known limitations
- Founding year not cleanly sourced in publicly indexed materials; some sources cite 2013, others 2001, and Earnix's own About page is not prescriptive. Maturity score on this fiche is consequently excluded until a primary source settles the question. (Earnix)