Author: Chandra Matam - Principal Data Architect
Every insurer I work with in the UK and across the broader market knows the feeling. The business wants to move at the speed of the market to respond to a competitor's pricing within the week, to flag an emerging claims trend before it becomes a reserving problem, to give the regulator a clear, current answer on demand. And yet the analytics estate underneath them is doing the opposite: batch jobs that run overnight, reports rebuilt by hand, a tangle of Oracle, on-premise warehouses, SSRS, and legacy BI tools that each made sense a decade ago and now collectively hold the organization back.
This is the gap between legacy chaos and real-time decisions. Closing it is the single most valuable modernization an insurer can undertake, and Microsoft Fabric has become the platform we use to do it.
The real cost of a legacy estate
Legacy analytics estates do not fail dramatically. They fail slowly, in ways that are easy to tolerate until you add them up. Reports take days to change because the logic is buried in tooling no one wants to touch. Licensing costs accumulate across overlapping platforms. Skilled people spend their time keeping the lights on rather than creating value. And the data is always, by definition, a little out of date because the architecture was designed to move data in batches overnight, not to support a decision someone needs to make this afternoon.
For UK insurers in particular, the pressure has intensified. Regulatory expectations around conduct and customer outcomes demand evidence that is current and traceable, not reconstructed weeks later. Competitive pricing in personal and commercial lines rewards the carriers who can react fastest. The London market's complexity makes data fragmentation especially expensive. A nightly batch and a stack of legacy reports are simply no longer adequate to the environment insurers operate in.
What modernizing on Fabric actually changes
Microsoft Fabric replaces that fragmented estate with a single, unified, software-as-a-service analytics platform and it does so in a way that directly attacks both halves of the problem: the chaos and the latency.
On the chaos side, Microsoft Fabric brings data integration, engineering, warehousing, and business intelligence into one environment, all built on OneLake, a single governed data foundation in an open format. Instead of maintaining a patchwork of tools and the integrations between them, the organization runs on one platform with one governance model. Power BI reads directly from the foundation through Direct Lake mode, which means fast, interactive analytics without yet another extract to manage.
On the latency side, Microsoft Fabric's Real-Time Intelligence capability is what turns overnight batch into live decision-making. Streaming data claims events, telematics, transactions, operational signals can be ingested, analyzed, and acted upon as it arrives. Data Activator can watch for defined conditions and trigger action automatically. For an insurer, that is the difference between learning about an emerging loss trend at month-end and seeing it form in real time; between detecting a suspicious claim after payment and flagging it before.
And because Fabric connects natively to Azure OpenAI and Copilot, the same modernization that delivers real-time analytics also lays the groundwork for AI copilots for analysts, natural-language access to governed data, and machine-learning models that run on current rather than stale inputs.
How we get there without breaking the business
The objection I hear most is reasonable: migrating a complex, business-critical analytics estate sounds risky. Reports are wrong, logic is lost, users are disrupted. That fear is exactly why so many organizations stay stuck.
The answer is to migrate with accelerators and discipline rather than by brute force. At KPI Partners we have spent close to two decades modernizing enterprise data estates, and we bring a suite of pre-built migration and analytics accelerators that automate the most time-consuming and error-prone parts of the work - scanning legacy metadata, converting pipelines, and rebuilding reports - reducing delivery effort substantially and compressing timelines from months to weeks. The transformation logic is preserved; the business is not asked to start over.
The proof that this works at enterprise scale is concrete. A Fortune 500 insurance and professional-services group operating in more than 120 countries ran its critical enterprise reporting on a legacy analytics platform with high licensing costs and little self-service. We delivered a full migration to a modern platform using our accelerators, automated the conversion of existing reports and logic, and rebuilt the dashboards with richer interactivity - all without disrupting operations. The outcome: roughly a 20% reduction in analytics operating costs, zero business disruption at cutover, and markedly improved self-service adoption across business units.
A second example sits closer to the data foundation itself. A global insurance advisory and risk-management firm with more than 58,000 employees engaged us to migrate an aging Oracle-based finance reporting environment to a modern, cloud-native platform. We rebuilt the pipelines with automation and stood up a governed model feeding executive dashboards with reliable, near-real-time data eliminating years of accumulated technical debt and commissioning a second phase off the back of the results.
The journey, sequenced sensibly
Modernization does not have to be a single, terrifying leap. The path we take with insurers is deliberate: assess the legacy estate and rationalize the report inventory so we modernize what matters and retire what does not; stand up the unified Fabric foundation on OneLake; migrate data platforms and BI with accelerators; layer in real-time capability where it changes decisions; and apply governance throughout so the result is audit-ready from day one. Each stage delivers value on its own, and each one compounds the next.
The destination is worth the journey. An insurer that completes it stops running its business on yesterday's data and starts making decisions on what is happening now - pricing faster, spotting trends sooner, satisfying regulators more easily, and standing ready for AI. That is the move from legacy chaos to real-time decisions, and for the carriers who make it, the gap between them and everyone else only grows.
Delivered, not promised: outcomes that match the ambition
Modernization is judged by outcomes, and the outcomes insurers want are clear: lower operating cost, faster decisions, evidence that satisfies the regulator in the UK, the currency of conduct and Consumer Duty - and a foundation ready for AI. Those are the outcomes KPI Partners is set up to deliver. With close to two decades of enterprise data experience, more than 300 clients, a dedicated insurance practice serving the UK and global markets, and a Microsoft alliance, we cover the full journey from legacy assessment to real-time analytics. Crucially, we deliver it with a suite of pre-built migration and analytics accelerators that take the risk and the timeline out of the work - converting pipelines, rebuilding reports, and preserving transformation logic rather than starting over.
The evidence is concrete. A Fortune 500 insurance and professional-services group operating in more than 120 countries ran critical reporting on a costly legacy platform with little self-service; we migrated it with our accelerators, achieving roughly a 20% reduction in operating costs, zero business disruption at cutover, and a marked rise in self-service adoption. A global insurance advisory and risk-management firm with more than 58,000 employees had us migrate its aging Oracle finance estate onto a modern, cloud-native platform with automated pipelines and a governed model feeding near-real-time dashboards eliminating years of technical debt and commissioning a second phase off the results.
The ambition is real-time decisions. The track record says we can get you there without breaking the business along the way.
