Earnix says insurers will compete on decision-making

Earnix has set out its case that competitive advantage in insurance will be defined by decision-making, a theme it will place at the centre of its Excelerate London event.

The gathering is expected to bring together more than 350 insurance executives, practitioners, technology specialists and partners in London. Discussions will focus on how insurers make decisions across pricing, underwriting, customer engagement and other parts of the business as market conditions shift and use of artificial intelligence spreads.

Earnix frames the debate around a change in how insurers respond to pressure on performance. Firms now have broader access to data, analytics and AI tools, but face a tougher operating environment shaped by changing risk patterns, shifting customer expectations and a growing need to oversee automated systems.

That reflects a broader question for the sector: whether advantage now lies less in simply having more information and more in how quickly and consistently insurers act on it. In practice, that means connecting decisions that have often been handled in separate parts of the organisation, particularly when pricing, underwriting and customer interactions affect the same commercial outcome.

The challenge, in Earnix's view, is no longer just improving individual decisions in isolation. Insurers need to connect decisions across the customer journey, apply different forms of intelligence to different contexts and build governance into the process as AI moves from recommendation to action.

Risk pressure

The backdrop is a risk environment that is becoming harder to model using historical patterns alone. Climate, cyber and AI-related exposures are changing what insurers need to assess, how quickly conditions can shift and how far ahead underwriting and pricing teams need to look.

In some lines of business, the historical data insurers have traditionally relied on is either limited or less useful than before. That puts more weight on combining established actuarial methods with newer data sources and decision systems that can be adjusted as conditions change.

Commercial underwriting is one area where those pressures are especially visible. A dedicated panel at the London meeting will examine how underwriting is changing as risk grows more complex and technology takes on a larger role in assessment and action.

Practitioners from Generali, Hiscox, Industrial Alliance and ManyPets are due to discuss how they use data and decision systems in pricing, underwriting, claims and customer engagement. Their participation suggests an effort to ground the discussion in current operating practice rather than a purely technical debate.

AI governance

Another part of the discussion will focus on governance, an increasingly pressing issue as insurers test generative AI and more autonomous software tools in operational settings. Explainability, permissions, human oversight, traceability and accountability need to be built into decisions themselves, not added after the fact, Earnix argued.

The company linked that point to the development of AIOS, its AI orchestration system for insurance, introduced at an earlier event in North America. In London, the product and technology agenda is due to include updates in underwriting and broader use of the system to organise models, agents, applications, data, workflows and human input around insurance decisions.

That emphasis reflects a shift in how software suppliers to the insurance sector are presenting their case. Rather than focusing only on analytics or automation in single functions, vendors are increasingly stressing how multiple tools are managed together, especially where regulatory scrutiny and operational accountability are involved.

A session featuring Deloitte and the Earnix product team will also address responsible AI design in financial services. The discussion is expected to examine how regulatory requirements can be embedded into working systems as predictive, generative and agentic AI are used more deeply in insurance operations.

Earnix argues that insurers will need different forms of intelligence for different tasks. In that view, predictive AI, generative AI, intelligent agents and human expertise each have distinct roles, and the key commercial question is how to match them to the decision at hand.

Robin Gilthorpe, Chief Executive Officer at Earnix, outlined that argument in a statement on the event's theme.

"Insurers have more data, analysis and AI at their disposal than ever before," he said. "What matters now is how effectively they turn that intelligence into better decisions, and those decisions into action. Doing that with speed, precision and confidence increasingly defines competitive advantage - and it is at the heart of the conversation at Excelerate London."