Insurers could be sacrificing years of commercial gains by tying pricing modernisation to large-scale core system replacements, according to Earnix, which argues that a phased approach could help providers reduce transformation risks and deliver value sooner.

Insurance modernisation programmes are often judged by their technology milestones and long-term promises of greater agility. However, Earnix principal solutions consultant for agentic and predictive AI Brian Shipley warns that some of the biggest costs are less visible, including delayed returns, pressure on internal teams and the risks associated with replacing multiple systems at once.

As core technology becomes increasingly standardised, insurers have more reason to focus on the capabilities that differentiate their businesses, including product development, pricing strategies and decision-making. Shipley argues that modernisation should therefore begin with the operating model insurers want to achieve, rather than simply replacing existing systems with newer versions.

Replacing a policy administration system (PAS) without rethinking the processes around it can carry legacy limitations into a new environment. By contrast, introducing a dedicated pricing and rating engine ahead of a wider transformation could allow insurers to update rates more quickly, run advanced simulations and streamline regulatory filings without waiting for an entire core replacement programme to finish.

Data migration presents another challenge. Insurers may hold substantial proprietary pricing data and embedded business logic within legacy systems, with dependencies that are not always apparent until migration begins. Moving information into platforms such as Snowflake or Databricks does not automatically resolve inconsistent field definitions or undocumented data lineage.

These issues can surface during reconciliation, when outputs from a new system fail to match those produced by the legacy environment.

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