Insurance companies are under pressure to make decisions more quickly as risk, customer behaviour and market conditions change. But according to Earnix, reducing the time it takes to make a decision only creates value when those decisions also improve business performance.
In a recent Earnix analysis, the company said 78% of commercial lines companies are prioritising advanced analytics, predictive modelling and artificial intelligence (AI). The growing focus on these technologies is giving insurers new ways to accelerate decision-making, but Earnix argues that speed alone should not be the measure of success.
For example, a faster pricing decision made without the relevant underwriting context could improve one area of performance while weakening another. Likewise, an automated decision involving a customer may create problems if the reasoning behind it cannot be explained or challenged.
The importance of faster decisions comes from being able to respond to information before it becomes outdated. For insurers, this can apply to pricing, underwriting appetite and customer signals, where changing circumstances can affect the decisions being made across the business.
At the same time, the increased use of AI in consequential decisions creates a need for greater visibility and control. Insurers need to understand why a decision was reached, retain the ability to review it and ensure that decisions remain aligned with their business and regulatory requirements.
Earnix said this means governance needs to be considered as part of AI-enabled decision-making from the start. Insurers need to define how data can be used, what models and AI agents are permitted to do, when human involvement is required, how exceptions are dealt with and where accountability sits.
The company points to three characteristics that it says are important when AI is used for consequential insurance decisions: explainability, auditability and governance. Explainability helps businesses understand what influenced an outcome, while auditability provides a record of the data, models, rules, approvals and actions involved. Governance provides the boundaries within which those decisions are made, including permissions, escalation processes and human accountability.
Taken together, these elements can help insurers make decisions faster while retaining oversight of how those decisions are reached. Earnix argues that the focus should therefore move beyond the speed of individual decisions towards whether those decisions support profitability, retention, customer outcomes and portfolio performance.
This also requires insurers to consider how different areas of the business work together. Pricing, underwriting and customer engagement can involve separate decision-making processes, even though they can affect the same overall business outcomes. Coordinating the intelligence used across these areas could help insurers respond to changing conditions more consistently.
Earnix has developed its AI Orchestration System, Earnix AIOS, around this approach. The system builds on the company’s 25 years of intelligent decisioning expertise and brings together intelligence, workflows, governance and human expertise.
According to the Earnix analysis, the aim is not simply to automate insurance decisions. Instead, the company focuses on using AI to support better-coordinated decision-making while maintaining the governance needed around those decisions.
Copyright © 2026 InsurTech Analsyt
