01
EXPANDING
Client conversation
Start with the conversation, notes or scenario instead of a blank record.
FOR AGGREGATORS THAT WANT THEIR TECH PROPOSITION TO MATTER
Make AI a reason brokers stay.And new brokers join.
Brokers are adopting AI whether their aggregator leads the change or not. Give members practical AI tools for policy, servicing and file preparation — so your network stays at the front of the technology curve instead of leaving every broker to build their own stack.
Strengthen member value. Modernise the recruitment story. Give brokers practical AI tools. Reduce tool fragmentation. Keep member data boundaries explicit.
Honest limits Review stays human Sources stay visible
REALISTIC PRODUCT STORYA modern member AI proposition built around live broker work.
CreditPolicy · Network pilot reviewILLUSTRATIVEPILOT OVERVIEW
Did members use it on real work?
16 / 20used it on at least one file
43policy research sessions
18servicing scenarios
11files moved into preparation
The goal is not another portal tile. It is technology members would miss if it disappeared.CreditPolicy.ai
One connected journeyFollow the work, not a feature menu.
1Member joins
2AI toolkit
3Live deal
4Network support
5Ongoing value
A MEMBER AI STACK BROKERS CAN ACTUALLY USE
Give members practical AI capability — not another technology announcement.
Jack brings the member proposition to life: useful AI across the working day, a network-led rollout path, and a technology story that can help the aggregator stay relevant as brokers adopt AI faster.
Member AI stackPolicy + servicingPilot + rolloutRetention + growth
CreditPolicy.aiAggregator + broker member experience · illustrative rollout
THE MEMBER AI STACK
Give brokers an AI toolkit that follows the whole working day.
The proposition is bigger than policy search. CreditPolicy.ai is being built as a practical AI layer members can use from client intake and document collection through research, servicing, forms, automation and submission preparation.
02
EXPANDING
AI client creation + data extraction
Turn authorised notes and supplied information into structured, reviewable client context.
03
IN ACTIVE BUILD
Document portal + collection
Request, collect and organise client documents against the same file, with missing items visible.
04
AVAILABLE / EXPANDING
Lender panel + product research
Research a large and expanding lender panel across multiple product categories from one place.
05
AVAILABLE / EXPANDING
Policy AI
Ask the live scenario, inspect the source and keep uncertainty visible when lender judgement is still required.
06
EXPANDING
Servicing + lender calculations
Work through supported servicing and progressively reuse client data in lender-specific calculator workflows.
07
IN ACTIVE BUILD
AI lender-calculator filling
Use reviewed client facts to help populate supported lender calculators rather than rebuilding the scenario again.
08
EXPANDING
AI document creation
Prepare editable file notes, summaries, briefs and other broker documents from reviewed client context.
09
EXPANDING
AI Form Fill
Map reviewed information into supported forms while keeping unresolved fields and applicant-specific exceptions obvious.
10
IN ACTIVE BUILD
Browser automation + external form filling
Carry reviewed client information into supported external browser workflows and repetitive data-entry steps.
11
IN ACTIVE BUILD
Submission prep + handoff
Bring the reviewed scenario, documents, forms and open questions together for the broker or lender handoff.
What this becomes
A network can give members a coherent AI workflow instead of leaving every brokerage to assemble its own collection of public AI tools, point solutions and browser extensions.
Status varies by workflow, lender, form and account. “In active build” describes product direction under development, not a promise that the feature is already production-ready.
RETENTION, RECRUITMENT AND RELEVANCE
Your brokers will use AI. The question is whether your network leads it.
Member technology is part of the value equation. The network can either give brokers useful AI tools with clear boundaries — or watch them build their own disconnected stack outside the ecosystem.
01 · MEMBER VALUE
THE PROBLEMIf the useful technology is always somewhere outside the aggregator, members gradually learn that they do not need the network for the tools that shape their working day.
Give brokers an AI workspace they can actually use on the next file.
Provide practical access to Policy Chat, supported Residential Servicing, Client AI, document collection, Form Fill and AI Document Studio as part of a modern member proposition rather than another static resource library.
- Useful on live deals
- AI tools in one member proposition
- Existing CRM and lodgement systems can stay
WHAT CHANGESStrengthen the everyday value of belonging to the network and give recruitment teams a more credible technology story to tell prospective brokers.
CreditPolicy.ai · MEMBER VALUE
Policy ChatILLUSTRATIVE
Alex Morgan · Fictional scenario
Self-employed borrower. What should I check?
Start with the evidence.
Check the relevant lender’s income requirements, trading history and supporting documents.
Income evidenceIllustrative source
Trading historyIllustrative source
Keep the source with the question.Review the applicable product and policy version.
Research guidance. Not a lender approval.
02 · KEEP MEMBERS AT THE TECH FRONT
THE PROBLEMIndividual brokers are experimenting with public AI tools, point solutions and browser extensions because they want faster answers and less admin — but the quality, security and workflow fit can vary wildly.
Give members a more deliberate way to adopt AI instead of leaving every broker to figure it out alone.
Start with a supported CreditPolicy.ai workflow, clear product boundaries and agreed onboarding. Use the pilot to show members where AI can help and where broker judgement still matters.
- Central onboarding and support
- Defined AI use cases
- Human judgement stays explicit
WHAT CHANGESHelp the network remain relevant as AI changes broker workflows, while giving members a clearer path than an unmanaged collection of tools.
CreditPolicy.ai · KEEP MEMBERS AT THE TECH FRONT
Your network pilotILLUSTRATIVE
Proposed rollout · Not a live dashboard
START WITHA focused pilot.
01
Choose your broker cohortAgree access and priority workflows
02
Make getting started simpleProduct guidance and support plan
03
Review before you expandMember feedback and agreed measures
No automatic access to members’ client files.
03 · REDUCE NETWORK FRICTION
THE PROBLEMSupport teams keep answering recurring policy, workflow and ‘where do I find this?’ questions while every member develops a slightly different process and technology stack.
Create a stronger common starting point without forcing every system into one platform.
Use CreditPolicy.ai as the AI research and preparation layer, then scope SSO, CRM, reporting, branding or panel controls only where the member workflow proves there is value.
- Common broker workflow
- Specific integrations only where justified
- No automatic visibility into member client files
WHAT CHANGESGive support teams a clearer tool to point members toward, reduce unnecessary fragmentation and make enterprise investment follow proven member demand.
CreditPolicy.ai · REDUCE NETWORK FRICTION
Your connected workflowILLUSTRATIVE
Your portal
CreditPolicyApproved context
Your systems
Scoped access Agreed connection
Define which information may be shared
Review every enabled action and destination
Test the handoff with your technical team
Custom connections require agreed scope and validation.
WHY THIS MATTERS
A better aggregator technology proposition should help you retain, recruit and support brokers — not just add software licences.
The strategic question is whether members feel the network is helping them keep up with how broking is changing.
Give existing brokers more everyday value from the network.
Put useful AI capability inside the member proposition rather than leaving it entirely outside the ecosystem.
Tell a stronger technology story to prospective brokers.
Show a practical AI workflow, not another list of vendor logos in a portal.
Help members keep pace with rapidly changing AI tools.
Give them defined use cases, onboarding and support instead of unmanaged experimentation.
Give repetitive member questions somewhere useful to go first.
Use source-backed research and a common workflow before escalating to network support.
“If brokers are going to build an AI stack anyway, the aggregator should have a compelling reason to be at the centre of it.
Useful because the limits stay visible.Enterprise examples are proposed scoped deployments. Content, access, integrations, retention and reporting are agreed before implementation.
Information access is deliberate.Public, broker-only and internal information require different permissions. A network or lender relationship does not automatically expose client records.
QUESTIONS BEFORE YOU DECIDE
Does this solve a problem worth paying for?
The strategic question is whether members genuinely value the AI capability enough for it to strengthen your retention, recruitment and technology proposition — not whether they logged in once after launch.
Can this really help with broker retention or recruitment?
Technology can be part of why a broker values an aggregator, but retention or recruitment should never be guaranteed. The practical test is whether members repeatedly use the tools on live work and whether brokers say the AI capability strengthens the network proposition. Measure that in a defined pilot.
Why should the aggregator provide AI tools instead of letting every broker choose their own?
Brokers can and will experiment with their own tools. The network opportunity is to offer a more deliberate supported path: practical broker workflows, clear boundaries, common onboarding and a place for support — without forcing every broker to assemble and govern a fragmented stack alone.
Does the aggregator get access to every member's client files?
No. A network relationship does not automatically create access to client records, conversations or documents. Reporting and visibility must be explicitly scoped, authorised and appropriate for the information involved.
Does this replace our CRM, lodgement or member portal?
No. Start with CreditPolicy.ai as the AI research and preparation layer for brokers. Keep existing systems that already carry CRM, lodgement, identity or compliance responsibilities, then scope connections only where there is a proven member use case.
Can we offer SSO, branding, network pricing or a restricted lender panel?
Bring those requirements into the enterprise scoping discussion. They are not universal out-of-the-box promises. The right implementation depends on users, account structure, permissions, integration requirements, support and commercials.
How do we know whether members actually value it?
Look beyond registrations. Track repeat use on live files, which workflows brokers return to, support themes, member feedback and whether the technology changes how brokers describe the value of the network. Use that evidence before committing to a broader rollout.
START WITH ONE BROKER COHORT
Make AI part of why brokers value your network.
Start with a representative member cohort and the jobs they do every day. Prove which AI workflows members actually value, then build the wider network proposition around that evidence.
No implementation commitment from an enquiry. Scope, feasibility, permissions and commercials come first.