Complete AI Training

AI app for insurance · no coding needed

Broker commission reconciliation

Commission differences traced to statement evidence.

Made for: Independent broker finance teams

What Broker commission reconciliation looks like
Open the demo For members · a working demo with sample data

What it does for you

The problem

Carrier commission statements cannot be matched to agency records.

What it gives you

Commission reconciliation report

What you give it

Commission statementsapproved policy registers

How it works, step by step

  1. Extract statement lines
  2. Match policy identifiers
  3. Compare expected amounts
  4. Flag unexplained deductions
  5. Collect corrections
  6. Export carrier queries

What you see on screen

  • Statement import
  • Match exceptions
  • Query pack

Build it yourself with your AI system

Build this app yourself, no coding needed

Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.

Sign in to see how to build it yourself

Build a quick version to try, or get the full app pack for Broker commission reconciliation with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.

Sign in Become a member

4 Have it built for you days to a few weeks

Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Broker commission reconciliation with you.

Have Nexibeo build it

What's in the app pack

Included in the Complete AI Training membership.

  • The building instructions your AI follows, step by step
  • The questions your AI will ask you about your business before it starts
  • A clickable demo you can open in your browser, to see how it should work
  • A detailed blueprint of the screens, the information it keeps and the checks it runs

Become a member to get the app packAlready a member? Sign in

The files, for the technically curious
  • START-HERE.mdHow to build it with your own AI (read first)3 KB
  • README.mdOverview and links1 KB
  • questions.mdQuestions to answer before you build3 KB
  • prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare25 KB
  • prompt-vps.mdThe same build on your own server (Docker)25 KB
  • spec.jsonData model, API, AI pipeline, acceptance criteria15 KB
  • demo/index.htmlThe working demo on sample data197 KB

Questions

Do I need to know how to code?

No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.

What does it cost?

The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.

How long does it take?

The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.

Can I change it to fit my business?

Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.

More detailsHow the AI works, safeguards and what to build first

For independent broker finance teams, turn commission statements and approved policy registers into commission reconciliation report. Address this specific problem: carrier commission statements cannot be matched to agency records. The aim: commission differences traced to statement evidence. The pilot tests whether that benefit holds up against reviewer effort and real operating costs.

The buyer creates a project, supplies commission statements and approved policy registers, and confirms scope and access. Users correct extracted facts, resolve flagged uncertainties and approve the final commission reconciliation report before use. Retain source links and a version history for the next cycle.

How the AI works

Propose matches while deterministic arithmetic calculates differences. Keep model suggestions separate from verified facts. Link factual outputs to authorized input evidence and show missing information explicitly. Use deterministic checks for counts, dates, identifiers and arithmetic where applicable. A designated reviewer validates consequential outputs and signs off the delivered result.

Safeguards

Separate document preparation from coverage, underwriting and claims decisions. Authorized professionals review policy meaning and customer commitments. Read-only matching; contractual interpretations reviewed separately. Require appropriate access and publication approval. Preserve source material, label AI drafts and make corrections traceable. Measure false positives and missed cases alongside speed.

What to build first

Costed pilot: Read-only matching; contractual interpretations reviewed separately. Start with one buyer organization and a bounded set of representative inputs. Implement the first two modules: extract statement lines; match policy identifiers. Support the third task through an assisted review queue: compare expected amounts. Handle the remaining required functions manually until validated. Include input upload, source references, user correction, a reviewer approval step and export of commission reconciliation report. Authentication, account isolation, deletion controls and basic operational logging are included. Specialized production certification, live write integrations and broader rollout are not included unless explicitly stated.

What it can connect to

Broker-approved policy documents, case records and carrier requirements. Read-only business data exports, reporting databases and task trackers. Reconcile source totals before scheduling recurring data refreshes. Begin with uploads and exports of commission statements and approved policy registers. Any named system or connector is a candidate requiring current access and compatibility checks; no live connection is included by default.

The screens in detail

Open with a compact overview and filters for the relevant period or segment. Let users drill from each theme or metric into underlying records. Keep source definitions and missing-data notes near the result. Use an action panel to assign investigations and record what was learned. Open with statement import; move into match exceptions for the detailed task; finish in query pack for review and handoff. Show the source record, uncertainty and approval status beside each proposed output.