Insurers have access to increasingly sophisticated pricing technology, but a growing execution gap could be limiting the value they get from it. Earnix argues that the industry’s challenge is shifting from building better pricing models to having the capacity to deploy, govern and continuously refine them.

Predictive modelling, AI, automation and richer datasets have given insurers more tools to assess risk and respond to market changes. However, the ability to generate pricing insight does not necessarily mean carriers can act on it quickly enough.

According to Earnix Analysis, many insurers are investing heavily in pricing sophistication without giving enough attention to the operational resources required to put those capabilities into production. Pricing and actuarial teams continue to spend significant amounts of time maintaining legacy systems, managing regulatory changes, supporting deployments and overseeing models already in use.

This is creating what Earnix Analysis describes as the “status quo trap”, where insurers approach pricing transformation primarily as a modelling challenge rather than an operating-model challenge. Even highly advanced models can have limited commercial impact if operational processes prevent their recommendations from reaching the market efficiently.

The pressure on insurers to improve pricing speed is also increasing. Claims inflation, social inflation, changing regulatory requirements and competitive pressure are forcing carriers to reassess rates and pricing strategies more frequently across different lines of business.

At the same time, insurance leaders increasingly expect pricing teams to experiment, test new strategies and respond to changing market conditions with greater speed. Legacy workflows and manual processes can make that difficult, particularly when teams are already managing multiple priorities.

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