How AI and Modern Platforms Are Transforming Manuscript Insurance at Scale

By Nitin Agrawal, AVP – Head of Architecture Practice at Xceedance

If you work in specialty or complex commercial insurance, you already know: manuscript products are powerful, but they’re hard to scale.

Bespoke wording means more negotiation, more interpretation, more exceptions – and more pressure on underwriting, operations, and claims teams.

In Part 1, I talked about why traditional platforms struggle with manuscript business. In Part 2, let’s look at how AI and modern platforms are changing the game.

Can AI really help with manuscript wording?

Short answer: yes – if it’s implemented with the right guardrails.

Manuscript policies are full of unstructured text. That’s exactly where Natural Language Processing (NLP) and related AI techniques shine.

AI can help insurers:

• Identify and extract key definitions, obligations, exclusions, and triggers from custom wordings.
• Compare a newly negotiated clause against a library of prior versions.
• Highlight what’s changed – and where risk or ambiguity might have increased.

Underwriters still make the calls. AI simply does the heavy lifting in the background.

How AI supports underwriters, not replaces them

Here’s how AI can free up underwriting capacity in manuscript-heavy books:

• Clause comparison and redlining support – instantly show how a proposed clause differs from standard or previously agreed versions.
• Guided risk assessment – surface relevant exposures and conditions that may need attention.
• Coverage consistency checks – flag potential conflicts between sections of a manuscript contract.

Underwriters spend less time hunting through documents and more time making informed decisions.

What about claims?

Claims teams often face the toughest end of manuscript policies: they must interpret bespoke wording under time pressure, in real-life loss scenarios.

AI can help by:

• Reading policy documents and extracting coverage triggers, deductibles, sub-limits, and conditions.
• Classifying incoming documents (reports, correspondence, evidence) against the relevant parts of the policy.
• Surfacing potential coverage issues or conditions that may apply to the loss.

Again, the goal is not to replace claims professionals – it’s to give them faster, more accurate context.

AI in testing and change management

One of the quietest pain points in manuscript business is testing.

Every variation in wording, coverage structure, or rating logic can impact multiple system flows. AI can:

• Generate test scenarios based on policy wording.
• Identify which flows and integrations are likely impacted.
• Help validate whether outputs (documents, calculations, workflows) align with the contract.

This can compress UAT cycles and reduce dependency on scarce SMEs.

Modern platforms: the foundation AI needs

AI is powerful, but it needs the right underlying platform. Modern manuscript-capable environments share some common traits:

• Low-code/no-code configuration – so business teams can adjust product logic without large IT projects.
• Extensible data models – to store bespoke attributes and triggers from manuscript wording.
• API-first design – allowing AI services, workflow tools, and document systems to plug in cleanly.
• Advanced clause libraries – with version control, approvals, and AI-powered search.
• Dynamic document generation – combining rules and AI checks to ensure accuracy.

How Xceedance helps insurers bring this to life

At Xceedance, we work with clients to combine AI, modern platforms, and deep insurance domain expertise for manuscript business. That includes:

• AI-powered clause analysis and comparison for underwriters.
• Intelligent workflow orchestration to route exceptions and approvals.
• Automated test scenario generation for frequent product variations.
• Document intelligence for claims – so adjusters get faster insight into coverage.
• Designing data and ML architectures that support long-term AI adoption, not just point solutions.

The result: insurers can offer highly tailored coverage without overwhelming their teams or compromising on speed and compliance.

The future of manuscript insurance: human + machine

Manuscript products will always require expert human judgment. That’s the nature of complex risk.

But the insurers who pair that expertise with AI and flexible platforms will:

• Shorten cycle times
• Reduce friction
• Improve consistency
• Unlock scalable growth in complex, high-value segments

Bespoke coverage doesn’t have to mean bespoke chaos.

With the right operating model, technology choices, and partners, manuscript insurance becomes a space where human insight and machine intelligence work together.