AI for insurance brokers · Sydney

AI for insurance brokers: renewals prepared before they are due

In most brokerages the calendar runs the team. Renewals bunch up at the end of the month, client details are retyped into submissions for three underwriters, and policy schedules are checked against the quote by eye. I help brokerages turning over one to ten million take that load off, one small step at a time, with a broker approving everything that goes to a client or an insurer.

Where an insurance brokerage’s week actually goes

Talk to any broker with a busy book and the story is the same. The advice and the relationships are under control. The work around them is not: a renewal pack that needs updated turnover and claims history from the client, a submission rewritten for each market, a schedule that came back from the insurer with the wrong sum insured, and a claim waiting on one more document.

None of it is hard. All of it is constant, and it falls on account managers and brokers whose time decides how many clients the business can look after properly. That is exactly the kind of work AI is now good at: reading documents, comparing them against each other, drafting in your format, and putting a short list in front of a person to approve.

This is not about a new broking system. You keep Winbeat, Sunrise or iBais, the insurer portals and your shared drive. The job is to connect AI to what you already run, so the preparing and checking is done for you and your people review it instead of building it.

What I’d take off your plate first

Usually Winbeat, Sunrise or iBais for clients and policies, insurer and underwriting agency portals for quotes, Xero or MYOB for the business, and Microsoft 365 or Google Workspace for everything else. I connect AI to those, rather than asking you to replace them.

Renewals started early

Sixty days out, the renewal questionnaire drafted from last year’s file with the changes to confirm, sent to the client once someone has checked it, and the answers read back into the record when they arrive.

Fact-finds and underwriter submissions

Client information gathered once and turned into a submission in each market’s preferred format, with the gaps listed for the broker. Nobody retypes the same business three times.

Policy schedules checked against what was quoted

Every schedule and certificate read when it comes back, compared against the quote and the client’s instructions, and any difference in cover, excess or sum insured flagged before it reaches the client.

Quote comparisons for the client

Terms from each insurer pulled into a side-by-side summary of premium, cover, exclusions and excesses, in plain English for the broker to check and use in the recommendation.

Claims paperwork

Claim notifications drafted from the client’s email and photos, documents tracked against what the insurer asked for, and a polite chaser drafted when anything stalls, on either side.

Invoicing and premium funding follow-up

Debit notes and invoices checked against the policy, unpaid premiums followed up on a schedule before cover is at risk, and commissions reconciled against what insurers actually paid.

And the admin every office has

The same work turns up in every brokerage: email, spreadsheets, documents, and a Microsoft or Google setup that grew without a plan.

Invoicing and accounts payable

Supplier bills read, coded and matched to the order or the job before they reach Xero or MYOB. Mismatches drafted into an email for someone to approve. Overdue invoices chased politely, on a schedule.

Email that answers itself, nearly

The inbox triaged each morning, routine replies drafted in your tone, attachments filed to the right folder, and a short list of what actually needs you today.

Spreadsheets you stop rebuilding

The weekly report that someone copies and pastes together every Monday, produced before you arrive, with a sentence on why the number moved.

Documents and slides

Proposals, letters, reports and board slides drafted from your own templates and your own past work, so the first draft is eighty per cent there rather than a blank page.

Microsoft 365 or Google Workspace, set up properly

Shared drives that make sense, permissions that match who you are now, and AI connected to mail, calendar and files the same way for everyone instead of five people doing it five ways.

Project and job tracking

Status updates written from what actually happened in email and the job system, tasks pulled out of meeting notes, and a morning brief per person of what is due.

How it works: audit, roadmap, implementation, training, support

Sold one step at a time. Each step is quoted before it starts, stands on its own, and you decide after each one whether to take the next. Most businesses your size go from the audit to a working, trained setup in three to six months.

  1. Audit

    Two weeks, fixed price. A map of every system you run, a ten-minute staff survey, a few five-minute screen recordings of the work that eats the week, and short conversations with the people who run the business. It costs your team minutes, not hours.

  2. Roadmap

    A ninety-day plan written from what the audit found: which processes first, ranked by admin removed against cost and risk, which AI plan and accounts your team should be on, and a two-page policy on what may go in. Every item has its own price.

  3. Implementation

    I build the first one or two automations inside your own Microsoft 365 or Google Workspace, connected to the systems you already run. AI drafts, a person approves anything that leaves the building, and it runs beside the manual way until you trust it.

  4. Training

    Your team learns on their own work, not on demos. One standard setup for everyone, a short session per group, and one-to-one time with the two or three people who will carry it once I step back.

  5. Support

    A light monthly retainer: one call, a one-page summary, fixes, and the next routine your team worked out promoted into something the business runs. I read the AI news so your people do not have to.

Use AI without handing over your clients’ data

A brokerage holds detail its clients would never want shared: claims histories, financial statements, payroll and turnover figures, property and security details, and sometimes personal health information. None of it needs to leave your own systems for AI to be useful.

The work happens inside your Microsoft or Google tenant and your broking system, on a business AI plan that does not train on your data, with company accounts for every person who uses it. Nothing goes into a free chatbot, and anything that goes to a client or an insurer waits for a broker to approve it.

The basics, every time

  • Company accounts on a business AI plan, never personal logins. Business plans do not train on your data.
  • AI connected to your own Microsoft or Google tenant, so files stay where they already live and access is revoked in one place.
  • A two-page policy your team can actually remember: which accounts, what may go in, what never does.
  • Everything I build lives in your accounts and is logged. I work from a staff login, not the master key.

Where most start

A typical first project: policy schedules checked against the quote

Most audits in broking land on a quick win like this one. Every schedule that comes back is read and compared against what was quoted and instructed, with any difference flagged and a query to the insurer drafted. It runs beside the manual check for a fortnight until you trust it. From there, renewal preparation is usually next.

Frequently asked questions

Will AI recommend cover to our clients?

No. It prepares the file, summarises the quotes and drafts the documents. The recommendation, and the judgement about what a client actually needs, stays with the broker, who reads everything before it goes out.

We use Winbeat (or Sunrise, or iBais). Do we need to change?

No. The point is to connect AI to what you already run. Where your system has a way in, I use it. Where it does not, I start from exports and documents and keep everything filed back to the client, so a slow vendor never holds the project up.

Can it fill in insurer portals for us?

Sometimes, and only where the portal allows it. More often the quick win is preparing every answer in one place so the person entering it copies rather than hunts. I will tell you honestly which portals are worth automating and which are not.

Is this worth it for a brokerage our size?

If renewals are a monthly scramble or account managers spend their days retyping, almost certainly. The audit will tell you honestly, and if a better renewal checklist would do the job, I will say so.

How much of my team’s time does this take?

Minutes, by design. Ten for the survey, ten for an optional screen recording, an hour with the key people. Whoever runs operations spends two or three hours across the first fortnight.

Do we have to commit to the whole thing?

No. Every step is quoted on its own and you decide after each one. Plenty of businesses take the audit and one project, and stop there until they see it working.

Are you tied to a particular AI vendor?

No. I lead with Claude because I think it is the strongest all-rounder for business work today, and I work just as happily with Microsoft Copilot, ChatGPT or Gemini if that is what your team already uses. Everything is built so the model is one part you can swap.

Running a brokerage and doing the admin at night?

Tell me what you run, how many people, and what eats the most time. I will tell you honestly whether an audit is worth it.

Tell me about your business

Tell me what you're dealing with

Three lines is plenty. I reply personally, usually within a day, and the first call is free.