---
title: "AI for underwriting: let it do the reading"
description: Title and transactional risk underwriting runs on documents. How AI can do the reading while underwriters keep the decision, with a real example.
image: https://wehelpyougrow.io/hubfs/insights-cover-ai-for-underwriting.png
---

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 October 20, 2026

# AI for underwriting: let it do the reading

![Picture of William Brooks](https://wehelpyougrow.io/hs-fs/hubfs/Dise%C3%B1o%20sin%20t%C3%ADtulo%20(10).png?width=50&name=Dise%C3%B1o%20sin%20t%C3%ADtulo%20(10).png) By  [William Brooks](https://wehelpyougrow.io/insights/author/william-brooks)  ·   2 minute read

Title and transactional risk underwriting runs on documents. Every enquiry arrives with a pile of them: legal papers, property details, surveyor reports, transaction histories and long email trails. Before an underwriter can decide anything, someone has to read it all and pull out what matters.

That reading is where AI earns its place. Not in the decision. In the reading.

We first wrote about this idea in February 2024, as a proposal. Since then we have been building it with a UK specialty insurer in title and legal indemnity, so this is an updated version with what we have learned along the way.

## Hours lost to re-keying

At the insurer we work with, submissions, specialist reports and email trails were spread across inboxes and a legacy system. Underwriters were spending hours reading and re-keying information before they could look at the risk itself.

None of that work needs an underwriter's judgement. It needs someone to find the right facts and put them in the right place. That is a job for software.

## What we built

The work has gone in stages, and each stage is useful on its own:

- Incoming email recorded automatically against the right file, so nobody has to search inboxes for the latest message on a deal.
- CRM extensions for new lines of business, so each enquiry has one record with everything attached.
- AI-drafted underwriting memoranda, so the underwriter starts from a first draft rather than a blank page.
- An assistant that answers questions across years of project files.
- Claims notification workflows.
- An AI parser that drafts risk summary forms from surveyor reports. This one is in build now.

## AI prepares, people decide

Every one of these tools prepares work for a person. None of them binds a risk, sets a premium or declines an enquiry. The underwriter reads the draft, checks it against the documents and makes the call.

This matters for three reasons:

- **Authority stays where it belongs.** Underwriting decisions sit with the people who hold the authority to make them, as they always have.
- **Mistakes get caught.** A draft that misses something is picked up when the underwriter reads it, before anything goes to a broker or a client.
- **People trust it sooner.** Underwriters can see exactly what the tool did and correct it. A tool that drafts is easier to accept than one that decides.

## How to start in your own team

You do not need a large programme. Start with one document your underwriters read every day and one form they fill in from it. Then ask three questions:

- Where does the document arrive, and who files it?
- Which facts does someone copy out of it?
- Where do those facts end up?

If the answers are "an inbox", "the same handful of fields every time" and "a spreadsheet or the CRM", you have a good first candidate. A first working version can be live within weeks, and then it gets better month by month as your team uses it.

## The takeaway

Let AI do the reading. Keep the decision with your underwriters.

*If your underwriters still re-key submissions by hand, tell us which process hurts most: [william.brooks@wehelpyougrow.io](mailto:william.brooks@wehelpyougrow.io)*

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