EXAMPLE · 01
Self-employed refinance file
The borrower uploads tax returns, bank statements, and BAS inconsistently. The employee flags the missing BAS period, extracts income evidence, and drafts the borrower chase for processor approval.
AI for mortgage brokers
AI for mortgage brokers that gets loan files ready before the lender asks
Mortgage brokers do not need another generic chatbot. The repeated bottleneck is the loan file: borrower documents arrive slowly, files need renaming, income evidence needs checking, credit notes need drafting, and lender conditions surface late. Rebotify builds a named AI employee that works inside your inbox, CRM, document store, and broker workflow. It prepares the file, drafts borrower chases, flags likely missing items, and queues the next broker decision. You keep the client relationship and credit judgment; the AI employee owns the admin loop.
Send the loan-file bottleneck. Mia maps the first borrower chase, file-readiness, or stip-monitor loop.
Runs inside
- ApplyOnline
- Salestrekker
- BrokerEngine
- Outlook
- Gmail
- SharePoint
- Google Drive
- Excel
If this is your week
The work that bleeds time.
- 01
Borrowers drip-feed documents for days
Payslips, bank statements, IDs, tax returns, and living-expense evidence arrive across email, portals, and shared folders. The broker or processor keeps checking what is still missing.
- 02
The file enters the system before it is clean
A wrong document, vague filename, undisclosed transaction, or missing page can become part of the permanent file trail. The team needs a review layer before lodgement, not just storage.
- 03
Lender conditions appear too late
Each lender has quirks. Self-employed income, overtime, rental income, credit-card limits, and policy exceptions create likely stips that could have been flagged before the file reached assessment.
- 04
Credit notes are written from scratch
The broker already knows the story, but the support team still turns notes, docs, and calculations into the same file summary again and again.
What changes
Every file gets cleaner before it reaches the lender.
The outcome is a brokerage queue where missing docs, file naming, likely stips, and credit-note prep are handled before the broker opens the file.
Borrower chases are ready from the current file state
The employee compares uploads against the checklist and drafts the exact missing-doc request for broker or processor approval.
Submission packs carry source links
Renamed docs, file notes, and readiness checks point back to the email, upload, fact-find answer, or broker note behind them.
Broker judgment stays intact
Credit advice, lender selection, and submission decisions stay with the broker or credit rep. The AI employee prepares the work.
The role
AI for mortgage brokers works best when it prepares and routes the loan file, not when it gives credit advice. A managed AI employee watches borrower uploads, email, CRM notes, and file storage; classifies documents; drafts missing-document chases; checks the file against broker rules and lender quirks; prepares credit-note sections; and flags likely stips before submission. The broker or credit rep approves every client-facing message and every submission decision.
In production
What it looks like on the queue.
Three jobs the AI employee runs from week one, drafted for review before send.
EXAMPLE · 02
Pre-submission readiness brief
Before lodgement, the broker receives a one-page brief: missing items, unusual transactions, likely lender questions, and the source document behind each point.
EXAMPLE · 03
Post-approval conditions queue
Approval arrives with conditions. The employee turns each condition into borrower chases, internal tasks, and source-linked status so the broker sees progress instead of inbox noise.
48-hour build
What ships in the first window.
01
Borrower document chase queue
The AI employee compares the current file against the checklist, drafts missing-document messages, and routes them for broker or processor approval before anything reaches the borrower.
02
File classification and naming
Uploads are read, classified, renamed to your rules, and linked back to source. Incorrect or partial documents are flagged for reject-and-revise before the pack is lodged.
03
Likely stip and lender-condition monitor
Broker rules, lender quirks, and prior condition patterns become checks. The employee flags likely gaps before submission and drafts the internal note for review.
04
Credit-note draft pack
Income evidence, expense notes, loan purpose, structure, and file context become a draft credit note. The broker edits, approves, and owns the final decision.
Human control
The employee prepares the work. People keep judgment.
No credit advice without the broker
The employee can prepare summaries, checklists, and drafts. It does not recommend products, assess suitability, or send advice to a client without broker approval.
Source-backed file readiness
Every checklist item links to the document, email, fact-find answer, or broker note used. The reviewer can verify the source before approving the file.
Clean-room before lodgement
Missing items, wrong files, privacy concerns, and unusual transactions can be reviewed before they enter the aggregator, lender portal, or permanent audit trail.
Sensitive-data handling mapped first
Before connecting borrower documents, we define where files live, what the model can see, retention rules, and which human owns approval.
Choose another workflow if
- Replacing broker best-interest judgment, credit advice, or lender recommendation.
- A standalone borrower portal only for document collection and file naming.
- Sending client chases, lender notes, or submission decisions without broker approval.
Good first week looks like
- Borrower missing-doc chases are drafted from the current checklist and file state.
- Uploaded documents are classified, renamed, and linked before they enter the submission pack.
- Likely lender conditions and file gaps surface before the broker submits.
Controls that make this safe to run.
Mortgage-broker automation has to respect best-interest duty, responsible-lending context, and borrower privacy. The useful frame is file preparation under broker control, not automated credit advice.
Safeguards we design around
- Broker or credit rep reviews every borrower chase, lender note, and file-readiness recommendation.
- Every readiness flag links back to the borrower upload, email, fact-find answer, or broker note used.
- Borrower document access, retention, and model visibility are mapped before the workflow touches live files.
Claim boundary
We do not claim autonomous credit advice, lender recommendation, responsible-lending assessment, or replacement of broker best-interest judgment.
Reference point
ASIC RG 273 mortgage brokers best interests duty
ASIC guidance frames the broker duty around acting in the consumer best interests, so product recommendation and credit judgment stay with the broker.
Reference point
ASIC RG 209 responsible lending conduct
Responsible-lending guidance makes verification, suitability, and borrower circumstances central to credit work.
Reference point
Australian Privacy Principles
OAIC guidance sets privacy obligations for handling personal information, including sensitive borrower documents.
What will Rebotify take off the team first?
AI for mortgage brokers works best when it prepares and routes the loan file, not when it gives credit advice. A managed AI employee watches borrower uploads, email, CRM notes, and file storage; classifies documents; drafts missing-document chases; checks the file against broker rules and lender quirks; prepares credit-note sections; and flags likely stips before submission. The broker or credit rep approves every client-facing message and every submission decision.
Who is AI for mortgage brokers best for?
AI for mortgage brokers is best for Australian mortgage brokerage owners, credit reps, loan processors, and broker support teams with a repeated workflow, a clear human owner, and enough examples to teach the AI employee what good work looks like.
What does Rebotify deliver in the first 48 hours?
Rebotify maps the workflow, writes the first operating playbook, connects the minimum tools, and puts useful drafts, checks, or summaries into a human approval queue.
Do humans still approve the work?
Yes. Rebotify normally starts with human approval for customer-facing, financial, legal, or policy-sensitive actions. The AI employee prepares the work and escalates uncertainty.
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48-HOUR START
Bring us one workflow. Leave with a 48-hour plan.
Get one loan file unstuck
Send the loan-file bottleneck. Mia maps the first borrower chase, file-readiness, or stip-monitor loop.