Earnix has introduced a new set of AI and automation capabilities aimed at helping insurers simplify regulatory filings, improve oversight of decision-making models and reduce friction between analysis and implementation. Its Q4 2026 release also expands tools for managing pricing changes, explaining premiums and supervising AI-driven workflows.
The latest updates focus on several operational challenges facing insurers, including preparing regulatory submissions, managing model complexity and making pricing decisions easier to explain and implement.
Earnix has enhanced its regulatory filing capabilities with improved rate manuals and reusable filing templates, designed to help insurers prepare and manage submissions more efficiently. The release also introduces more granular retention controls, expanded analytics and greater visibility into model structures and dependencies.
These capabilities are intended to give insurance teams more control over the data and processes underpinning their decisions, while helping them understand how changes to models may affect wider operations.
The release also expands Earnix’s AI capabilities, including tools for supervising AI agents, analysing documents and explaining premiums. These features aim to help insurers apply AI across their workflows while maintaining oversight of how decisions are made and communicated.
Further updates target pricing and rating processes across states and insurance products. Earnix has added support for base rate adjustments and integration with ISO Electronic Rating Content (ISO ERC), alongside testing capabilities designed to help insurers manage changes to rating systems.
The changes reflect the operational demands facing insurers as they look to modernise pricing processes while meeting regulatory requirements and maintaining transparency around decisions.
Earnix chief product and technology officer Be’eri Mart said, “Our customers are tackling challenges that span teams and functions, from adapting to changing risk to helping a policyholder understand their premium. That is driving us to expand both the breadth of our portfolio and how our capabilities work together. With Q4 2026, we’re removing practical barriers between analysis and execution, using AI and automation where they can make a meaningful difference, and giving insurance professionals more ways to apply their expertise to deliver better outcomes for their businesses and customers.”
The role of AI in insurance extends beyond developing more sophisticated models, with insurers also needing to ensure that insights can be translated into operational decisions. This includes giving teams the tools to implement changes, understand outcomes and maintain appropriate governance.
Celent’s Karlyn Carnahan said, “The next competitive battleground in insurance is how effectively insurers put intelligence to work on the decisions that affect business performance. Investing in more sophisticated models and AI will deliver limited value if teams still struggle to implement changes or explain outcomes. Insurers need capabilities that close those gaps, making better decisions easier to execute, govern, and communicate.”
Earnix has more than 25 years of experience in AI, risk, pricing, rating and analytics. Its AIOS platform is designed to coordinate intelligence across the decision-making lifecycle, supporting insurers as they connect analysis with business execution.
Copyright © 2026 FinTech Global
