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Why AI is the Future of Expertise in Specialty and Re-Insurance

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Specialty and Re-Insurance Needs Experts, Not Just Data—AI Finds Them


Navigating complexity is paramount in the dynamic and often unpredictable insurance landscape, particularly within the specialty and reinsurance sectors. Success isn't just about processing vast amounts of data; it increasingly hinges on effectively leveraging the deep, nuanced expertise held by experienced professionals. In a world defined by uncertainty and rapid change, the insurance sector stands at the forefront of managing complexity.

Despite significant investments in cutting-edge technology, many insurers face a persistent challenge: their most valuable institutional knowledge often resides within the minds of a select few seasoned experts. This reliance on individual experience creates systemic risks that can hinder performance and expose the organisation to vulnerability.

Over the next 15 years, 50% of the current insurance workforce will retire. It’s a jarring number. This leaves more than 400,000 open positions unfilled… The combined result of these trends is an unprecedented loss of insurance knowledge, one that is bound to get worse. (Insurance Journal, March 2024)


The Challenge: Managing Internal Knowledge For Insurers

Despite significant investment in technology, many insurers remain constrained by a critical limitation: the most valuable institutional knowledge lives in the minds of a few experienced professionals. This presents three systemic risks:

  • Knowledge Silos: Expertise is fragmented across departments and geographies, limiting cross-functional collaboration.
  • Inefficiency and Lost Revenue: When insights aren’t accessible in real time, it slows risk assessment, pricing, and claims resolution, leading to missed opportunities and delayed outcomes.
  • Operational Vulnerability: Organizations reliant on a handful of experts face heightened risk from turnover, retirement, or absence.
  • High financial leverage and impact in decision making for complex risks

In addition, the insurance industry is still in the early stages of digitization, with 80% of direct written premiums in the U.S. running on legacy systems. Furthermore, the Specialty and reinsurance sectors are inherently more complex, more collaborative, and more reliant on human expertise than standard insurance.

As a result, this highly specialized sector requires significant consideration when applying new tech solutions to solve age-old problems. 

The Solution: Combining Human and Artificial Intelligence

To thrive in this environment, insurers must rethink how they capture and apply institutional knowledge. This is where Starmind comes in, a platform that integrates Human Intelligence (HI) with Artificial Intelligence (AI) to unlock expertise in real time, across the enterprise.

By analyzing internal communications, documents, and updates from core systems like Guidewire or Confluence, Starmind builds a dynamic, self-updating expertise network. It identifies who knows what, and ensures that critical insights are immediately accessible to those who need them.

This combination of human and artificial intelligence directly impacts key functional areas:

  • Underwriting: Accessing insights from peers who have handled similar complex risks enables faster and more informed pricing decisions. This leads to improvements in both the speed and accuracy of decision-making, crucial for competitive advantage.
  • Risk Engineering: Field intelligence and data on emerging threats, such as cyber risks or climate impacts, can be surfaced in real time. This supports more proactive and consistent risk evaluations, allowing the organisation to anticipate and mitigate potential issues more effectively.
  • Claims Management: Historical knowledge and specific situational experience can be tapped into instantly. This reduces the dependency on the memory or availability of individual claims adjusters and significantly improves resolution times, enhancing customer satisfaction and operational efficiency.

Starmind: Bridging Complex Knowledge Clusters

Unlike generic knowledge platforms, Starmind’s technology is trained on the language, workflows, and real-world complexity of the insurance sector. The result is a living knowledge graph that grows as people contribute, delivering relevance, accuracy, and measurable business outcomes.

The benefits of such a system are compelling. Starmind offers a practical way to scale human expertise without adding headcount or increasing complexity. It enables:

  • Faster, smarter decision-making
  • Reduced risk exposure from knowledge loss
  • Improved productivity across critical functions
  • Stronger collaboration between departments and regions


Crucially, this approach transforms often hidden, difficult-to-access institutional knowledge into a tangible, renewable asset – one that actively grows and evolves alongside your business. 

While many insurers have correctly focused on modernizing systems and automation in their digital transformation efforts, the next frontier isn't solely about processing data efficiently. It's about effectively capturing human intelligence and making it actionable at scale throughout the organisation.

Successfully implementing AI in commercial insurance means empowering teams to navigate complexity with speed and confidence. Starmind helps break down those detrimental silos and future-proof the organisation's most valuable asset: the collective wisdom of its people.

 

- By Charlie Haendel and Joerg Ruetschi

 

Want to learn more about how Starmind can connect your teams to the right internal experts to improve underwriting, risk, and claims decisions? Take a look at our Insurance page.

 

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We’re always ready to help, with support tailored to your business needs. Schedule a call with one of our team to:

  • Learn more about how Starmind can connect knowledge across your business.
  • Discover the use cases that best fit your needs.
  • See how you can bring all of your company’s knowledge into one central platform.
  • Discuss your bespoke pricing package.

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