Insurance Data Transformation in 2026: Why Data Readiness Defines the 360-Degree Customer View

What was once framed as a strategic differentiator – the “single customer view” – has become crucial for insurers in 2026. As Consumer Duty expectations rise and AI-driven decisions become more common across pricing, claims, and service, regulators and customers alike now expect insurance firms, like yours, to ensure every customer interaction is informed by a complete, joined-up understanding of the individual. Without this, fragmented data and departmental siloes continue to create inconsistent experiences, awkward customer interactions, and growing regulatory risk.

As Sheldon Mills, Executive Director of the Financial Conduct Authority (FCA), has emphasised in their long-term AI review, firms need to design systems that work for consumers even “when the path ahead isn’t fully visible,” recognising that good outcomes depend on how data and technologies are used in practice.

Today, a 360-degree customer view represents a practical capability: the ability for insurance teams across claims, underwriting, marketing, and service to operate from the same trusted data, recognise the full customer journey across every interaction, and demonstrate that decisions are informed, fair, and joined up.

 Why Consumer Duty Has Changed the Role of Customer Data

Consumer Duty represents one of the most significant regulatory shifts the insurance industry has seen in recent years. Introduced to elevate protection standards across financial services, it focuses on ensuring ”good outcomes for retail customers throughout the customer journey”. This creates a direct line between data maturity, regulatory risk, and brand trust at board-level, while ensuring customers receive fair-value pricing and products that genuinely meet their needs – driving informed choice, confidence, trust, and long-term loyalty.

The need for a single, 360-degree customer view, free from fragmented systems and siloes, therefore becomes crucial. By bringing together data from across the organisation, insurance firms can design journeys and interactions that reflect real customer experiences rather than isolated touchpoints.

How Do Siloed Systems Compromise Customer Experience and Create Risk?

Siloed operating models are a natural consequence of how some insurance systems have evolved. Claims, marketing, underwriting, and service platforms were built to solve different problems, often at different times.

Worryingly, nearly 4 in 10 insurance leaders say they aren’t sure if their organisation has a comprehensive view of key business data – a sign that these organisational siloes are ever-prevalent and affecting decision-making.

This can deeply affect the customer journey. For example, a customer navigating a complex or sensitive claim may still receive generic marketing communications that fail to reflect their situation. While subtle, these disjointed interactions are not just frustrating for customers; they signal a lack of joined-up oversight and undermine trust at critical moments.

Under Consumer Duty, these disconnects also take on greater regulatory significance. The FCA expects firms to understand, monitor, and respond to customer needs across the full lifecycle, using insight drawn from across their operations rather than isolated functions. However, when the key customer information sits across siloed systems, that understanding becomes harder to maintain and demonstrate consistently. Fragmented data directly increases the risk of inconsistent experiences and weakens a firm’s ability to stand behind the decisions it makes.

Breaking down silos between claims, underwriting, marketing, and service is therefore paramount to maintaining a single, consistent view of the customer, ensuring that interactions feel informed, appropriate, and aligned – subsequently reducing unnecessary friction, customer dissatisfaction, and regulatory exposure.

Data Readiness: The Constraint Beneath the Strategy

Ambitions around AI and advanced analytics are now common across insurance strategies yet progress often stalls at the data layer. As the FCA’s AI review suggests:

“Advancing AI technology could reshape finance markets, alter consumer behaviour and disrupt existing business models, while also introducing new risks.”    

Fragmented data and siloed systems make this challenge tangible: more than 75% of UK underwriters cite poor data quality as the main barrier to accelerating AI adoption in pricing and risk assessment, and organisations with significant data silos also see around 65% of AI initiatives fail to deliver expected value.

The lesson is clear. Insurers need a single, trusted view of the customer, curated with well-governed customer data, to support confident decision-making and regulatory assurance. Without this, strategic ambitions stall; not because of a lack of intent, but because the organisation cannot reliably act on insight across the business.

Data readiness therefore becomes the inflection point: the moment where insurers either continue managing complexity through disconnected systems, or establish the conditions required to operate with consistency, control, and scale.

Building a Practical Foundation

Turning that readiness into progress requires deliberate changes to how customer data is brought together and governed. Insurers today have a growing range of options when it comes to modernising their data landscape. The right platform depends on existing architecture and strategic goals, but the objective is consistent: to simplify how data is accessed and shared so teams can act on the same information at the same time.

Rather than replacing every system, modern data platforms enable insurers to connect existing estates, reduce dependency on departmental data ownership, and create a common analytical layer that supports insight, oversight, and execution across the firm.

Platforms such as Microsoft Fabric and Databricks are commonly used to achieve this.

Microsoft Fabric provides a unified analytics environment that connects policy, claims, and customer interaction data, supporting consistent reporting and near real-time insight. When paired with Microsoft Purview, insurers gain governance and clearer visibility over data lineage, quality, and access – supporting confidence in how data is used.

Databricks is another strong approach for insurers built around a lakehouse architecture that unifies structured, unstructured, and streaming data, including claims, telematics, and customer interactions. This unified approach helps eliminate departmental blind spots, enabling insurers to create a holistic view of data and apply advanced analytics and AI at scale, supporting use cases such as fraud detection, underwriting insight, churn prediction, and more personalised engagement.

Whichever route is taken, a modern data foundation is essential for breaking down silos, supporting Consumer Duty expectations, and delivering outcomes with confidence.

Looking Ahead

As 2026 progresses, the gap between insurers that are data-rich and those that remain insight-poor will continue to widen. While many firms are exploring advanced analytics and AI, insurance leaders are recognising that sustainable advantage comes from consistency, governance, and trust in decision-making. The differentiator will not be who adopts the most sophisticated models, but who has built the strongest data foundation beneath them.

A single, trusted view of the customer is central to that foundation. Without it, AI initiatives struggle to scale, insights remain isolated, and decision-making becomes fragmented. Fixing the data layer that connects claims, marketing, and service is therefore the first meaningful step toward unlocking value from emerging technologies.

You can’t build tomorrow’s capabilities on yesterday’s fragmented data. Which will it be? Fix the foundation, break down silos, strengthen governance and create that single source of truth or accept that your competitors are already ahead.

How Simpson Associates Can Help You?

We help insurance firms, like yours, harness the power of their data to create a joined-up, Consumer Duty-ready view of the customer. As a data transformation partner with over 3 decades of deep, technical expertise – and a Microsoft Fabric Featured Partner, alongside established Microsoft, Databricks and IBM partnerships – we support insurers in unifying complex data estates, strengthening governance, and unlocking trusted insight.

Whether you’re connecting claims and marketing data or building a scalable foundation for analytics and AI, we help insurers eliminate siloes, reduce regulatory risk, and deliver consistent, customer-centric outcomes at scale. Explore how we work with insurance organisations or get in touch with us via email or live chat.