In excess insurance, building a tower has historically meant one thing: manually reconstructing it.

Underwriters piece together a complete view of a program by reviewing hundreds of documents across the primary layer, multiple excess layers, and often multiple carriers. Limits, attachments, breakpoints, pricing, and terms are extracted by hand and reconciled across sources just to understand the structure of the risk.

That reconstruction work is necessary — but it’s not where underwriting judgment adds the most value.

The hidden cost of rebuilding towers

Tower analysis is foundational to excess underwriting, yet the work required to assemble a tower is often fragmented and time-consuming. Information lives across submissions, endorsements, quotes, binders, and correspondence, rarely in a single standardized format.

As a result, underwriters spend significant time:

• Reconstructing structure instead of assessing risk
• Validating consistency across layers and carriers
• Manually checking limits, attachments, and pricing logic

The work is precise and detail-oriented, but largely mechanical.

Moving from reconstruction to evaluation

At FurtherAI, tower reconstruction is handled directly in the workspace.

Underwriters can drop the relevant documents into FurtherAI, and the platform assembles the full tower into a clean, reviewable format. Primary and excess layers are organized automatically, with limits, attachments, breakpoints, and pricing surfaced in a way that’s easy to validate.

Instead of rebuilding structure, underwriters can focus on:

• Evaluating how the tower is constructed
• Reviewing terms and consistency across layers
• Applying judgment to the risk itself

The output is transparent and reviewable — designed to support underwriting decisions, not replace them.

Designed for real underwriting workflows

Tower analysis inside FurtherAI reflects how underwriting actually works. It’s built to handle real submissions, real document variability, and real complexity — without forcing teams to change how they operate or rely on brittle templates.

The goal isn’t to automate judgment. It’s to remove unnecessary reconstruction work so underwriting expertise can be applied where it matters most.

A clearer view of the tower

When structure is assembled automatically and presented clearly, underwriting teams gain a faster, more reliable view of the risk. Reviews become more consistent. Decisions become easier to explain. And time previously spent stitching together documents can be redirected toward analysis.

That’s what tower analysis looks like inside FurtherAI — shifting underwriters from rebuilding structure to evaluating risk.

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