Insurance is arguably the most data-rich industry in the world. It collects, stores, and processes trillions of data points on everything from driving habits and weather patterns to consumer behaviour and asset usage. In theory, it has the raw materials to fuel thousands of high-value business models. In practice, it funds just one.
Data is imperative and vital to insurance. It’s the lifeblood of the actuarial muscle that makes it all possible. For example, calculating weather risk, a typical catastrophe model might attempt to use 150 years’ worth of meteorological data. That represents ~30 terabytes of data, over 100M locations, while simulating approximately 100,000 atmospheric and hydraulic scenarios. This in turn yields 200 billion records to feed the financial models.
However, while it’s clear that insurers are adept at utilising data to assess risk, it also highlights how narrow the dominant approach to data has been: collate, analyse, extract insight, and feed the model mostly for underwriting and pricing.
Vital, but single-minded and massively constraining the insurer’s ability to truly shape propositions.
Data velocity is becoming evermore vital —
90% of the world’s data has been generated and gathered in the last two years. A result of the commercial and political world recognising us more as individuals and the importance of shaping life experiences to suit specific interests and activities. This is set to accelerate massively. Especially with AI.
Big Data has the ability to change the way we see people, which impacts on insurance and risk pricing. It should also change how insurers operationalise and use data to create better relationships, to build risk mitigation, to orchestrate claims ecosystems and more.
But there’s a problem. Legacy technology has split data into silos, creating a fracture at the very heart of insurance. Data for analytics is separate from operating data models that treat data as a perishable asset, constantly mine it for insight and act on that insight.
This separation means that by the time insights are surfaced, they are often out of date. Decision-making becomes retrospective rather than anticipatory, leaving insurers reacting to risk and customer needs instead of shaping them. What’s more, these fragmented systems prevent data from flowing across the enterprise, trapping valuable intelligence in isolated silos.
Until insurers can unify these environments, bringing analytics, operations, and experience design closer together, the industry will continue to leave a huge amount of value on the table. Fixing this disconnect isn’t about collecting more data. It’s about creating an entirely different relationship with data itself.
From data hoarding to data harnessing —
Nearly 80 percent of enterprise data is unstructured, coming in the form of emails, text documents, research, legal reports, voice recordings, videos, social media posts and more. For insurers looking for answers, this unstructured data is a goldmine. However, compared to structured data, it’s much more difficult to analyse.
Fortunately, evolving technologies, such as natural language processing, can enable insurers to unlock the value. Natural language processing, a component of artificial intelligence (AI) that can understand human language as it is spoken, has evolved to a point where it can be used to understand a user’s questions (text or speech) and, through training models, mine insights from vast amounts of unstructured data.
This can now also be added to vast amounts of connected and real-time data. Like your car telematics. Your connected home. Your commercial building’s “Building Management System” and so on. Outside of risk, pricing etc., insurers could be using unstructured customer data to shape better experiences and services.
However, the tech stack and operating model needs to transform to make this and any meaningful use of AI a reality.
Building an adaptive data ecosystem —
Operationalising data requires insurers to think differently.
Insurers can use large volumes of data to improve pricing strategies, streamline the claims process, and make better underwriting decisions. Yet they typically struggle to make any changes to product, services and experiences beyond this. Make no mistake, insurance is a data product and a data-lead service. The industry just keeps pretending it still produces documents it calls policies, only that concept is now defunct.
Instead, what consumers want to buy is an adaptive personalised cover typically adjusted somewhat to our risk tolerances and bank balances. Insurers just make this super hard to achieve because they don’t fundamentally address the underlying way the business operates, and in turn, how this allows it to operate around data.
Delivering on this vision requires a different operating system for insurance. One that changes how products are imagined, built, and delivered.
- Start with the customer, not the policy: For decades, products have been built around policy structures – static “document”. The future flips this on its head. Propositions will be designed around the evolving needs, behaviours, and circumstances of the individual or business, creating experiences that feel relevant, human, and personalised.
- Make data fluid and frictionless: Data can no longer sit in static databases, updated in batch processes. It must flow freely across the organisation, instantly available to inform decisions, power automation, and personalise services the moment they are needed.
- Adopt a MACH-based, cloud-native architecture: Composable, API-first, cloud-native and headless systems remove the shackles of legacy IT. They allow insurers to innovate at speed, integrate seamlessly with partners, and continuously evolve their offerings without the burden of slow, monolithic systems.
- Enable adaptivity at speed, across any product, any market: When the business model is flexible by design, insurers gain the ability to pivot quickly – whether launching new lines of business, entering new geographies, or rapidly adjusting offerings in response to emerging risks. This agility unlocks entirely new growth opportunities.
Unlocking new engines of growth —
The time has come to challenge the industry’s dependence on a single, inflexible revenue model. From risk mitigation services to value-added digital ecosystems, through to the monetisation of the rich operational, behavioural, and environmental data coursing through the industry’s veins, the untapped potential in insurance is staggering.
This new DNA for insurance makes insurers look more like eCommerce businesses in the way they operate and in the way they conceive and build product & experiences. However, a transformation that unlocks data utilisation and monetisation requires a fundamental cultural shift and a reimagining of the entire operating model. It’s a big ask, but a journey worth taking.
The insurers who act now to break free from their data debt won’t just improve efficiency, they’ll redefine the very role of insurance. By harnessing the full value of their data, they can move from reactive risk carriers to proactive value creators, building ecosystems that protect, predict, and partner with their customers.
The question is no longer whether the industry can afford to modernise. It’s whether it can afford not to. The real growth engine of insurance isn’t risk. It’s data, and the clock is ticking.
Rory Yates is the Global Strategic Lead at digital insurance platform provider EIS.
