Pricing, underwriting, customer engagement and retention used to be treated as fairly distinct parts of the insurance business. Increasingly, the decisions made in one area have consequences across the others, while changing risk, customer behaviour and regulation add further pressure.
Earnix has expanded from its roots in pricing and rating into a broader focus on how insurers use data and AI across those decisions. CEO Robin Gilthorpe says the focus now is on making those capabilities practical enough to use in live insurance workflows, with the governance and transparency required around them.
In this week’s Behind the Idea, Gilthorpe reveals all about moving AI into day-to-day insurance operations, why connected decision-making is becoming more important, and where Earnix is heading next.
Tell us more about your company and its offering
Earnix works with insurers on the business decisions that most directly affect growth, profitability, and customer trust. In insurance, that often means pricing, underwriting, customer engagement, and retention: deciding what to offer, at what price, to which customer, through which channel, and under what conditions.
Those decisions are becoming harder to manage because the assumptions behind them are changing more often and with greater consequence. Pricing, underwriting, and engagement are more connected than ever: a change in price can affect retention, an underwriting decision can shape the customer experience, and the way an insurer engages a customer can influence both risk and profitability.
That is why our technology focuses on connecting decision-making across the business, so insurers can respond to change more cohesively rather than asking each team to work around the same pressures separately. The goal is to make the business more responsive without losing control, transparency, or accountability.
What problem was your company set up to solve?
Earnix was set up to solve a problem that has always sat at the center of insurance: how to make better decisions in a business where risk is constantly changing. Insurers have never lacked expertise; they have deep actuarial, underwriting, product, and analytical talent. The challenge was that insight often moved more slowly than the market, trapped in models, committees, or systems that were hard to change. We were built to close the gap between what insurers know and what they can act on, giving them a more practical way to apply intelligence in live decisions, explain those decisions, govern them properly, and adjust as conditions change.
Since launch, how has your company evolved?
Earnix began with a focus on pricing and rating, one of the most technically demanding and commercially important areas of insurance. That work shaped how we think about the industry, because pricing depends on a clear view of risk, customer value, profitability, and market response. Over time, it became clear that underwriting, portfolio management, and even call center teams needed access to the same insights. Our evolution has followed that need — from improving decisions within individual functions to giving teams a more connected view of the signals and consequences shaping decisions across the business.
What has been the biggest challenge or most ‘tricky moment’ to overcome?
The biggest challenge has been getting useful technology out of controlled tests and into the daily work of insurance. A single AI use case can look compelling, but insurers then have to answer harder questions: who reviews the output, how it fits into existing processes, how it is governed, and whether it can be repeated across the business. Those details matter in an industry where decisions affect customers, regulators, risk, and profitability. The tricky part is making AI practical enough for business teams to use and controlled enough for the organization to trust.
What are your biggest achievements or ‘proudest moments’ so far?
The proudest achievement is seeing our technology used in the daily decisions insurers depend on, at real scale. It is one thing to build advanced analytics; it is another to see those capabilities trusted in live pricing, underwriting, and customer decisions where the business needs speed, accuracy, and control.
That is also why the AI agents already in production with carriers are important: they show that this work is moving beyond pilots and into practical use across real insurance workflows. We are especially proud when customers can move more quickly from identifying a change in the market, risk, or customer behavior to making a decision they can explain and stand behind.
How would you describe the culture of your company?
Earnix has a practical, customer-focused culture, and people here are energized by difficult technology problems. Our customers are trying to keep pace with markets that are moving faster and becoming harder to predict. They need to make decisions with more confidence, explain them more clearly, and adapt as risk, customer behavior, and regulation change. There is a seriousness to that work, but not a heavy culture – people take the challenge seriously, enjoy solving it together, and take pride in seeing the impact with customers.
What’s in store for the future?
Looking ahead, the opportunity is to make the intelligence insurers already have easier to use in the decisions they make every day. The industry has spent years modernizing systems, improving data, and experimenting with AI; the next step is turning that investment into better decisions while the opportunity, the risk, or the customer need is still live.
For Earnix, that means continuing to build out AIOS and insurance-native AI so pricing, underwriting, portfolio, and customer teams can see what is changing, understand what it means, and act with confidence. The bigger ambition is to support a more adaptive and resilient insurance industry – one where intelligence is not trapped in reports, pilots, or disconnected systems, but becomes part of how insurers respond to change every day. That is what will matter as risk becomes more dynamic, customers expect more relevance, and the industry continues to play its essential role when people, businesses, and communities need it most.
Answers provided by Earnix
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