Enabling the Pivot: Unstructured insurance data and the shift from indemnification to prevention

Information + Collaboration = Transformation

The shift from indemnification to prevention is on. If insurers, customers, and partners can collaborate on ways to reduce and avoid risk before it occurs, it’s a win-win for everyone. But the insurance industry has been talking about this for a long time as an ideal end state–so what’s changed?

You probably already know that answer: data and AI. In reality, it's slightly more complex than that, but it all comes down to information.

• Technology, both hardware and software, is now embedded in more places, including previously ‘forbidden zones’ such as operational technology (OT) environments. This means every asset is now a sensor.

• As a result, individuals and organizations are collecting insanely huge volumes of data, and technology is (so far) keeping up with our appetite for collecting as much as possible.

• For insurers, this means numerous new pathways to valuable data, much of which is unstructured, including everything from claims notes and emails to photos, videos, and real-time sensor feeds.

• Finally, the rise of AI, including the recent development of GenAI, presents insurance data teams with additional opportunities to leverage all that information.

  
  

It all adds up to a significant turning point.

The Proactive Imperative

Forward-thinking insurers can now use insights from unstructured data to spot risks early. Imagine analyzing adjuster notes and property photos to flag fire hazards, or using IoT data to predict water leaks before they cause damage.

This isn’t just a vision; we know leaders are already partnering with customers to bring the vision to life. But with so much unstructured data in play, protecting sensitive data is more important than ever. Unstructured data, in particular, is messy and full of sensitive details, making it a prime target for cyber threats and regulatory scrutiny.

How Data Security and Compliance Matter

Insurers are awash in unstructured data. Every claim, customer email, and uploaded image adds to the pile. Gartner estimates that over 80% of enterprise data is unstructured, and most traditional cybersecurity tools aren’t designed to handle it all.

At the same time, regulations are getting stricter. GDPR, HIPAA, CCPA, and the NAIC Model Law all set tough standards for handling, storing, and reporting on sensitive insurance data. 

This puts insurers in a bind. How can you unleash sensitive unstructured data without compromising data protection or compliance?

Unstructured Data Requires Next-Level Data Security Practices

Let’s be real: unstructured data security is hard work across several different workloads. First, there’s discovery and classification. Sensitive data is scattered across cloud and on-prem systems, making it hard to find and tag. Manual processes simply can’t keep up with the scale and complexity.

Second, controls are often inconsistent. Encryption and access management can be patchy, leaving PII, PHI, and intellectual property exposed to both hackers and insider threats. These gaps can lead to costly breaches and regulatory fines.

Data sprawl and shadow IT (and shadow AI) make things worse. Employees store files everywhere - Dropbox, email, personal devices - creating blind spots for compliance and security teams. This fragmentation makes it nearly impossible to maintain full visibility and control over the process.

Finally, regulatory complexity adds pressure. The NAIC Model Law, for example, requires insurers to notify regulators and customers of breaches within varying deadlines by state. Keeping up with these evolving requirements is a major challenge.

Data Security Must Protect the Crown Jewels While Enabling the Pivot

So, what’s the answer?

1. It begins with a security framework and governance strategy built and optimized for unstructured data. Annual risk assessments and a robust information security program, as required by the NAIC Model Law, are foundational.

2. Next, AI-driven tools are essential. Modern insurers use AI to automatically classify, mask, and encrypt sensitive data based on context, not just keywords. This ensures protection wherever the data lives or moves.

3. Policy-driven retention and disposal are also critical. Data needs to be managed throughout its lifecycle, from secure storage to compliant deletion. This reduces liability, cuts costs, and aligns with privacy laws such as GDPR’s right to erasure.

4. Continuous monitoring and audit trails round out the framework. Real-time monitoring and end-to-end audit logs enable easier demonstration of compliance and allow for quick response to incidents. Regulators want proof that policies are enforced, not just written down on paper.

The Payoff: Smarter Insurance and Stronger Bottom Lines

Embedding strong security and compliance into unstructured data management lets insurers confidently deploy proactive solutions. The payoff? Fewer claims, lower losses, and a more resilient regulatory posture. It’s not just about avoiding fines, but building trust and unlocking new insights for smarter business.

The future of insurance is proactive, data-driven, and secure. However, achieving this requires both strategic vision and practical, reliable tools that keep sensitive information protected at every step.

Confidencial: Enabling the Pivot with Selective Encryption

Confidencial is purpose-built to help insurers turn sensitive unstructured data from a liability into a competitive advantage. It automatically discovers, classifies, and encrypts sensitive information across claims, policies, and communications—no matter where it lives.

With granular access controls, end-to-end audit trails, and seamless integration into existing workflows, Confidencial ensures compliance with evolving regulations while empowering teams to securely collaborate and innovate. By centering data security and privacy, insurers can confidently embrace proactive risk prevention and digital transformation.

Ready to see how Confidencial can future-proof your unstructured data strategy? Learn more.