Insurers are investing heavily in cloud infrastructure, artificial intelligence (AI) and digital transformation, but many are yet to see meaningful improvements in how quickly they make decisions. Pricing, underwriting and responses to market changes remain slow, raising questions about whether technology investments are delivering their intended benefits.
The issue was explored during a recent Insurtech Insights webinar on building the agile insurance enterprise, featuring Earnix vice president of global solutions Drew Lawyer, Bupa head of strategy Roddy Barnes and Prudential engineering leader Rohan Rayarikar.
Earnix argues that connected decisioning is the missing link between technology investment and operational performance. For insurers, the ability to connect data, analytics and workflows could have a direct impact on pricing accuracy, risk selection, combined ratios and distribution performance.
Rayarikar believes the sector’s main constraint is not a lack of technology, but the way decisions are made. Cloud migrations and AI pilots are expanding, yet insurers are still struggling to reduce the time required to respond to market movements, assess risks and meet the needs of customers and intermediaries.
He argued that technology has traditionally been treated as an addition to existing processes rather than being embedded into core workflows. The conventional approach was to say, “here is a system, here is technology that can help your life.”
Instead, Rayarikar advocates an integrated architecture that connects customer intent to decision-making. This would allow relevant customer information to be retained across underwriting, pricing and engagement, reducing the need for policyholders and advisers to repeatedly provide the same data.
The challenge becomes more pronounced at scale. Prudential’s distribution network includes more than 90,000 financial professionals, all of whom need timely access to relevant information when advising customers. Legacy systems and fragmented data make this difficult, highlighting the importance of a unified data and decisioning layer.
Lawyer examined the issue from an underwriting perspective, drawing on his experience at a mid-sized insurer. He challenged the assumption that underwriting should primarily determine whether a risk is accepted or declined, suggesting that where market pricing is broadly accurate, its role could instead focus on assessing confidence in the price assigned to each risk.
For example, a married couple insuring two Toyota Corollas might qualify for automated processing, while an 18-year-old seeking cover for three Ferraris could require manual assessment. Under this model, underwriting decisions become valuable inputs for pricing models, customer engagement and next-best-action strategies, rather than functioning solely as a gatekeeping mechanism.
However, improving technology infrastructure is only part of the challenge. Reflecting on Bupa’s cloud migration, Barnes described the process as an “unlock that moves the bottleneck”. Removing infrastructure constraints can expose organisational barriers, meaning insurers must also reconsider their operating models to realise the full benefits of digital investment.
Governance is another consideration. When pricing, underwriting and customer engagement teams influence the same customer interaction, insurers need clear decision-making responsibilities and processes for resolving competing priorities. Increasing AI spending alone will not address these structural challenges.
Earnix positions its AIOS platform as a foundation for connected decisioning, bringing together data, models, AI and workflows. Its pricing, underwriting and customer engagement solutions are designed to extend this approach across the insurance value chain.
For the InsurTech sector, the next stage of digital transformation will depend on more than adopting new technologies. Insurers will need to demonstrate that their investments translate into faster, more consistent and better-informed decisions. Those that connect customer data, analytics and workflows within robust governance frameworks, while maintaining human judgement and regulatory oversight, could gain a meaningful competitive advantage.
Copyright © 2026 FinTech Global
