De-Risk Insurance Modernization with Quality Assurance

For insurance technology leaders, core modernization is a non-negotiable mandate for 2026. With vast investment and zero tolerance for disruption, it has become the ultimate high-wire act: a necessary evolution that must not destabilize the very business it aims to future-proof. To achieve this, insurers require a clear understanding of the nature and scope of the risk inherent in the process. This article brings to light where modernization risk truly accumulates and explains how a strategic focus on Intelligent Quality Engineering provides the control layer needed to move forward with both speed and confidence.

Modernisation risk is rising in 2026 as expectations tighten

Core platforms for policy, claims, and billing are changing rapidly. Yet customers expect continuity, regulators require control, and boards demand certainty. This is why nearly seven out of ten insurance leaders are unwilling to put core business stability at risk in pursuit of transformation.  

Nevertheless, as Gartner reminds us, legacy core systems constrain agility and innovation, which reinforces the reality that modernisation is a strategic business initiative, not a technical exercise. To remain competitive, insurers must evolve platforms that sit at the heart of revenue, risk, and trust. The margins for error are smaller than ever. Even minor instability risks cascading consequences: disrupted customer journeys, financial leakage, delayed benefits realisation, and reputational damage at executive level.

The scale of investment raises the stakes further. Insurance companies in the US alone are expected to spend more than USD 229 billion on modernisation by 2029. That level of spend leaves little room for missteps. CIO agenda research reflects this pressure, showing that insurers increasingly expect digital investments to deliver measurable operational outcomes rather than long-term experimentation. 

Looking toward 2026, those pressures intensify. Economic constraints demand sharper cost discipline. Data and AI ambitions depend on dependable core behaviour. Climate-related uncertainty is reshaping underwriting assumptions. Meanwhile, expectations around platform stability, release predictability, and audit readiness continue to rise. The question is no longer whether to modernise, but how to do so without betting the business.

Where does modernisation risk actually accumulate?

In practice, modernisation failures rarely originate inside the new core system itself. The greater risk accumulates around how the platform behaves once it is live, how it interacts with surrounding systems, and how change is introduced over time. It's less like replacing a car's engine and more like re-routing traffic in a busy city: the new system must work seamlessly with the existing ecosystem. 

Policy administration, billing, and claims platforms sit at the centre of complex value chains. A release that appears successful in isolation can still trigger downstream issues in customer experience, financial processing, or reporting. For technology leaders, this shifts the focus from feature delivery to end-to-end behavioural confidence.

This is where quality assurance must extend beyond individual applications and protect critical business journeys across the platform landscape.

Why business rules parity is a financial risk, not a technical detail

Insurance cores rely on decades of underwriting logic, pricing rules, coverage definitions, billing cycles, and claims outcomes. These rules define how risk is priced and how money moves through the organisation.

Modernisation risk materialises when new platforms behave differently from legacy systems in subtle but material ways. Premium calculations change. Renewals behave inconsistently. Claims outcomes diverge from historical patterns without clear explanation.

In this context, quality assurance is not about confirming that requirements were implemented. It’s about validating that business behaviour remains predictable, explainable, and financially correct as platforms evolve. Risk-based test automation focused on critical insurance journeys plays a central role in maintaining that confidence.

Data migration and reuse amplify modernisation risk

Data is often treated as a one-time migration activity. In reality, it’s a long-term risk factor that shapes future outcomes.

Inaccurate or poorly understood historical data affects renewals, claims handling, financial reporting, and regulatory submissions. When that same data is reused for analytics and AI-driven decisioning, the impact compounds. CIO research highlights that data-driven automation and AI are among the most anticipated outcomes of digital investment in insurance, increasing the consequences of poor data quality across modernised core platforms. Outcomes become harder to explain, and corrective action becomes more costly.

Data quality and data integrity across core platforms therefore becomes foundational. It provides confidence that data is complete, consistent, and fit for purpose, not only at cutover but throughout the modernisation journey.

Intelligent Quality Engineering functions as a control layer for change

For CIOs and CTOs operating in highly regulated environments, such as insurance, quality has a broader role than defect detection. Intelligent Quality Engineering functions as a control layer that supports predictable delivery, defensible release decisions, and confidence in platform behaviour.

Rather than slowing transformation, this approach enables informed decision making. Leaders gain evidence that change is under control, that risks are understood, and that trade-offs are deliberate rather than accidental.

This shift from testing as a phase, to quality as a continuous discipline, is increasingly critical during multi-year modernisation programs.

Confidence consistently proves more valuable than speed

But what happens when speed becomes the only KPI? While often considered the primary objective, uncontrolled speed actually increases exposure. This is why CIO and risk leaders’ priorities are shifting. OSFI executive director, Jacqueline Friedland, put it plainly:  operational resilience is financial resilience.  Frequent releases without sufficient assurance create instability, rework, and loss of momentum. CIOs are increasingly measured on operational resilience rather than delivery velocity. The tolerance for disruption has collapsed, and leadership incentives have shifted accordingly.

Predictable delivery supported by risk-based automation allows insurers to move forward without sacrificing control. Confidence in outcomes enables sustained progress. Hope is not a strategy. A solid QA foundation is.

Hybrid modernisation states demand continuous assurance

Core modernisation rarely happens in a single step. Legacy and modern platforms often run in parallel for extended periods, increasing regression risk and operational complexity.

Sustained assurance across these hybrid states requires quality practices that span old and new systems simultaneously. Managed Quality Engineering capabilities help maintain confidence across modernisation waves, ensuring that critical journeys continue to perform as expected as platforms change incrementally.

Modernising with confidence in 2026

Insurers that succeed in core modernisation are reframing it as a risk-managed journey rather than a delivery milestone. With most insurance leaders signalling that the business cannot absorb unnecessary risk, successful transformation increasingly depends on evidence, control, and confidence, not optimism or speed. They embed quality into transformation governance, treat data as a strategic asset, and use Intelligent Quality Engineering to support leadership decision making.